Zoeken op trefwoord in de kennisvragen:

 

De meest bekeken kennisvragen:

DEPLOYMENT-Business models

Regarding making PT more flexible:

Such a transformation of the system could also breathe new life into ideas of financing basic public-transportation services—on the one hand in the form of pay-as-you-drive, but also on a flat-rate basis financed via taxes or levied on all citizens, as is often debated for cities. Also, a high service density in suburban and even rural areas would justify a flat-rate levy and could in the process help to reduce private car use.”

Regarding offering new service options for PT:

Concerning intermodality, possibilities include more public transport services, even in the suburban and rural areas mentioned above (for urban areas, see Chap. 11). The benefits resulting from the use of autonomous vehicles are equally true in spatial and temporal terms, that is both for districts on the outskirts and off-peak hours. An economic lower limit resulting from frequency of use also applies here, however, even in view of the saved labor costs. This also means that a spatially highly dispersed use can only be covered to a limited extent by providing larger fleets. In any case, operating these vehicles would have to pay for itself in terms of initial outlay and operating costs.”

Gevonden in (p. 186 & 187): New Mobility Concepts and Autonomous Driving: The Potential for Change

There are multiple models/players:

The Branded Integrated Life-Style Model

It’s a sleekly designed experience, riding in this self-driving car. As elegantly designed as the sleekest smart phone.You use an app on your phone to summon your car when you need it or to program a daily pick-up. It’s as simple as setting the alarm on your phone.Your windshield doubles as a screen, synching seamlessly with your other connected devices. As you ride along, you swipe through applications and web sites, checking your progress and the local weather on a digital dashboard, uploading photos to your favorite web site or watching a video. When you arrive at your destination, the screens you’ve opened are synched and waiting for you on whatever device you pick up next.

In this model, perhaps a company with no traditional presence in the auto industry that is already an integral part of the consumer’s life outside the vehicle could become a key participant in the ecosystem. Since self-driving vehicles will no longer need the same level of rigorous testing and validation, and manufacturing could potentially be outsourced, their emphasis would be on consumer research, product development, and sale of integrated lifestyle experiences.

The Branded Lifestyle Value Proposition: Design, Technology, Software, Consumer experience

The Open System Model

It’s all about the data and how to use these data to customize the consumer value proposition.The market for big data

is growing exponentially. Market intelligence provider IDC predicts that by 2015 the “Big Data” market will be $16.9 billion, up from $3.2 billion in 2010.35 A major player in the data market might not want to manufacture vehicles, but could

well design a vehicle operating system. With more than a billion cars serving up trillions of data points about consumer behavior, traffic patterns, and topography, an operating system (OS) developer could afford to give away the OS but accrue significant value from the data they could aggregate. Who would manufacture the vehicle? The OS provider could partner with any of the world’s vehicle manufacturers—and not just the traditional automotive manufacturers. Partnerships could be established with one or more new players who might compete in the branded technology arena.

The Open System Value Proposition: Utility, Technology, Customization

Mobility On Demand Model

Zipcar was the pioneer in the shared-vehicle field, but other players are breaking into the market. Whereas current mobility on demand providers must make vehicles easily accessible for customers in urban areas, their vehicle maintenance and parking fees are high. With self-driving vehicles, proximity to end-users would no longer be necessary. Vehicles could be dispatched by taxi and car service companies.

Giant retailers with a core competence in managing complex distribution channels or fleet providers with the capability

to manage the complexity of renting and allocation of fleets could enter the fray and accrue significant value in the new ecosystem. New entrants in the market might compete at either end of the spectrum—with generic, low-cost utilitarian transportation on demand at one end (the low-cost airline model) and super-luxury mobile executive suites and sleeping pods at the other (the first class or private jet experience). Success will be determined by efficiency, reliability, flexibility, vehicle maintenance, customer service, ease of human-vehicle interface, and integration with existing consumer devices—and all the other psychographic factors that determine consumer behaviors and brand preferences.

The Mobility on Demand Value Proposition: Flexibility, Reliability, Convenience, Cost

The OEM Model

Traditional automotive manufacturers have decades of experience in designing and manufacturing vehicles, and shaping an emotional connection with consumers. But will they move fast enough to maintain their brand dominance? Smart automotive manufacturers should be planning now, thinking about how to restructure their organizations and what potential strategic investments they should be making. History has not been kind to those who get stuck protecting the status quo in the face of disruptive change. In fact, collaboration is already taking place across the ecosystem as companies strive to stay relevant.The joint project between Intel and DENSO36 to develop in-vehicle communication and information systems exemplifies the new cross-industry synergistic relationships.

Vertical integration is an option for companies looking to bring a critical skill or technology in house. Some vehicle manufacturers have established venture capital subsidiaries to invest in promising new technologies as a means of bridging any skill or technology gaps. Doing so may provide a competitive advantage in this rapidly evolving ecosystem.

The OEM Value Proposition: Design, Technology, HMI, Supply Chain Management “

Gevonden in (p.32-33): Self-Driving Cars, The Next Revolution

The automotive industry is a global industry in which value is generated predominantly by suppliers to automakers. The Dutch automotive industry is no exception to this rule. Within specific areas in the automotive industry, the Netherlands even plays a significant role with leading innovative companies that are involved in automotive activities worldwide. In these areas, the Dutch automotive sector is highly innovative and possesses a considerable knowledge base. To further strengthen its role, the Dutch automotive sector has developed a vision supported by a strong ambition of the Dutch automotive industry to increase its annual revenues from Eur 12 bn to Eur 20 bn.

The Dutch automotive sector has two responses to the opportunities and challenges of today’s automotive industry: innovation and cooperation. Innovation is vital in the continuous struggle for cost reductions alongside increasing levels of quality, individuality, and personalisation, and legal requirements (e.g., noise, safety and emission). Effective cooperation is becoming more and more crucial as competitive advantage will gravitate towards those that discern their strengths and move quickly to build or join appropriate new collaborative networks.”

 

Gevonden in (p.7): Vision for the Dutch automotive sector

 

  • Use of existing and public infrastructure:
  • The concept of truck platooning combines automation with the usage of existing public infrastructure. This increases the compatibility of the concept. New infrastructure is often expensive and it may not be clear who is responsible for the infrastructure.
  • Realization of fuel savings:
  • Truck platooning has the potential to significantly save fuel. This also results in less emissions. Though, the order of fuel savings in practice is still uncertain. It was found that truck platooning is probably not feasible when only fuel savings are taken into account.
  • Larger truck driver productivity:
  • Drivers in following trucks may be in a standby mode at highways or even disappear for high levels of automation. It can be concluded that coordinated platoon formation is needed to benefit from larger trip distances that may be possible due to platooning. Labor cost savings may largely contribute to the adoption of platooning as many flows become feasible for platooning when labor costs drop.

 

 

Gevonden in (p. 49): https://www.dropbox.com/s/wnl33x2zqwwe5jy/MScThesisBakermans2016.pdf?dl=0

 

70% Driverless future A policy roadmap for city leaders Page 3 report Encourage adaptable parking.Fewer cars means fewer parking spaces, especially in city centers. Parking garages need to be built with housing or office conversion in mind and include level floors, higher ceiling heights and centralized ramps. These future-proof garages are already being contemplated in Boston and Nashville.

DEPLOYMENT-Samenwerking

Key players:

 

  • Evolutionary: auto industry (OEMs)
  • Revolutionary: non-automotive technology companies (google, apple, etc)
  • Transformative: high-tech start-ups

 

Gevonden in (p. 206):

https://www.dropbox.com/s/91n2z7i19wfgzu6/Beiker%2C%20S.%20%282016%29%20Deployment%20Scenarios%20for%20Vehicles%20with%20Higher-Order%20Automation.pdf?dl=0
Note Joop: In het onderzoek van Surf STAD is voor Nederland door Bart Stoffels een mooi overzicht van stakeholders opgenomen.

https://www.dropbox.com/s/vvb3xj5m1d4ntkp/zelfrijdende%20stad_20%20maart_BS.pptx?dl=0

Vehicle-to-X connectivity (V2X): Connectivity is an important element of the automated vehicles especially secure V2X communication requiring low latency. V2X technologies encompass the use of wireless technologies to achieve real-time two-way communication among vehicles (V2V) and between vehicles and infrastructure (V2I). The convergence of sensor-based solutions (current advanced driver assistance – ADAS) and V2X connectivity will promote automated driving. “

 

“Digital infrastructure: Digital infrastructure (for road automation) includes static and dynamic digital representations of the physical world with which the automated vehicle will interact to operate. Issues to address include: sourcing, processing, quality control and information transmission. “

Gevonden in: https://www.dropbox.com/s/4hor6dyblxeeinb/15CPB_AutonomousDriving.pdf?dl=0

Innovatie bevorderende wetgeving ontwikkelen

  • Om (testen met) zelfrijdende auto’s op de openbare weg juridisch mogelijk te maken, wordt de bestaande AMvB (Besluit ontheffing verlening exceptionele transporten) voor ontheffingverlening door de RDW aangepast. Ik verwacht dit voorstel begin 2015 aan uw Kamer te sturen. Tot die tijd is testen op kleinschalig niveau mogelijk. De RDW verleent dan ontheffing en beoordeelt samen met de wegbeheerders de veiligheid. Hierbij kijken we uiteraard naar wat er in de rest van de wereld gebeurt op dit terrein, bijvoorbeeld naar de regelgeving die in Californië is ontwikkeld.
  • Ik streef daarnaast naar (inter)nationale regelgeving die marktintroductie van zelfrijdende voertuigtechnologie mogelijk maakt. Daarvoor nemen we het initiatief in internationale overleggen (EU en VN) en steunen we relevante voorstellen. Ter voorbereiding op het EU-voorzitterschap van Nederland inventariseer ik welke regelgeving/kaders ten behoeve van zelfrijdende auto’s op Europees niveau zouden moeten worden aangepast of waar een gezamenlijk kader wenselijk is. Uiteraard werk ik hierbij samen met andere landen.
  • Grootschalige testen in de praktijk faciliteren en kennisontwikkeling:
  • Ik geef na de zomer uitsluitsel over de voorwaarden en de locatie waaronder eerder genoemde testaanvraag kan worden uitgevoerd. Hierbij betrek ik eventuele andere aanvragen.
  • Deze test gebruiken we om in de praktijk een basisprocedure en voorwaardenset voor het structureel testen van automatische voertuigtechnologie te ontwikkelen. Doel is veilig testen en de kennis structureel borgen voor volgende initiatieven en projecten. Hierbij werk ik samen met kennisinstellingen, bedrijfsleven, de RDW en wegbeheerders
  • We gaan actief deelnemen aan internationale initiatieven. Zo nemen we deel aan het World Economic Forum waarbij met de auto-industrie en andere relevante partijen barrières en mogelijke oplossingsrichtingen voor de zelfrijdende auto in kaart worden gebracht. Te denken valt aan vraagstukken rondom data (eigendom, beheer, uitwisseling en beveiliging) en aansprakelijkheid. Op nationaal niveau zal ik ook onderzoeken laten uitvoeren naar deze onderwerpen, daarbij neem ik ook privacy en rijvaardigheidseisen mee.

Gevonden in: https://www.dropbox.com/s/ze5qzm20upsqlye/grootschalige-testen-van-zelfrijdende-auto-s-4.pdf?dl=0

 

DEPLOYMENT-Toekomstverkenningen-en-Transitiepaden

“Automated driving, with its minimal space requirements and rather equal speed levels, could at least double the existing average road infrastructure capacity. “

Gevonden in (p.380): Autonomous Vehicles and Autonomous Driving in Freight Transport

 

There are multiple models/players:

The Branded Integrated Life-Style Model

It’s a sleekly designed experience, riding in this self-driving car. As elegantly designed as the sleekest smart phone.You use an app on your phone to summon your car when you need it or to program a daily pick-up. It’s as simple as setting the alarm on your phone.Your windshield doubles as a screen, synching seamlessly with your other connected devices. As you ride along, you swipe through applications and web sites, checking your progress and the local weather on a digital dashboard, uploading photos to your favorite web site or watching a video. When you arrive at your destination, the screens you’ve opened are synched and waiting for you on whatever device you pick up next.

In this model, perhaps a company with no traditional presence in the auto industry that is already an integral part of the consumer’s life outside the vehicle could become a key participant in the ecosystem. Since self-driving vehicles will no longer need the same level of rigorous testing and validation, and manufacturing could potentially be outsourced, their emphasis would be on consumer research, product development, and sale of integrated lifestyle experiences.

The Branded Lifestyle Value Proposition: Design, Technology, Software, Consumer experience

The Open System Model

It’s all about the data and how to use these data to customize the consumer value proposition.The market for big data

is growing exponentially. Market intelligence provider IDC predicts that by 2015 the “Big Data” market will be $16.9 billion, up from $3.2 billion in 2010.35 A major player in the data market might not want to manufacture vehicles, but could

well design a vehicle operating system. With more than a billion cars serving up trillions of data points about consumer behavior, traffic patterns, and topography, an operating system (OS) developer could afford to give away the OS but accrue significant value from the data they could aggregate. Who would manufacture the vehicle? The OS provider could partner with any of the world’s vehicle manufacturers—and not just the traditional automotive manufacturers. Partnerships could be established with one or more new players who might compete in the branded technology arena.

The Open System Value Proposition: Utility, Technology, Customization

Mobility On Demand Model

Zipcar was the pioneer in the shared-vehicle field, but other players are breaking into the market. Whereas current mobility on demand providers must make vehicles easily accessible for customers in urban areas, their vehicle maintenance and parking fees are high. With self-driving vehicles, proximity to end-users would no longer be necessary. Vehicles could be dispatched by taxi and car service companies.

Giant retailers with a core competence in managing complex distribution channels or fleet providers with the capability

to manage the complexity of renting and allocation of fleets could enter the fray and accrue significant value in the new ecosystem. New entrants in the market might compete at either end of the spectrum—with generic, low-cost utilitarian transportation on demand at one end (the low-cost airline model) and super-luxury mobile executive suites and sleeping pods at the other (the first class or private jet experience). Success will be determined by efficiency, reliability, flexibility, vehicle maintenance, customer service, ease of human-vehicle interface, and integration with existing consumer devices—and all the other psychographic factors that determine consumer behaviors and brand preferences.

The Mobility on Demand Value Proposition: Flexibility, Reliability, Convenience, Cost

The OEM Model

Traditional automotive manufacturers have decades of experience in designing and manufacturing vehicles, and shaping an emotional connection with consumers. But will they move fast enough to maintain their brand dominance? Smart automotive manufacturers should be planning now, thinking about how to restructure their organizations and what potential strategic investments they should be making. History has not been kind to those who get stuck protecting the status quo in the face of disruptive change. In fact, collaboration is already taking place across the ecosystem as companies strive to stay relevant.The joint project between Intel and DENSO36 to develop in-vehicle communication and information systems exemplifies the new cross-industry synergistic relationships.

Vertical integration is an option for companies looking to bring a critical skill or technology in house. Some vehicle manufacturers have established venture capital subsidiaries to invest in promising new technologies as a means of bridging any skill or technology gaps. Doing so may provide a competitive advantage in this rapidly evolving ecosystem.

The OEM Value Proposition: Design, Technology, HMI, Supply Chain Management “

Gevonden in (p.32-33): Self-Driving Cars, The Next Revolution

The automotive industry is a global industry in which value is generated predominantly by suppliers to automakers. The Dutch automotive industry is no exception to this rule. Within specific areas in the automotive industry, the Netherlands even plays a significant role with leading innovative companies that are involved in automotive activities worldwide. In these areas, the Dutch automotive sector is highly innovative and possesses a considerable knowledge base. To further strengthen its role, the Dutch automotive sector has developed a vision supported by a strong ambition of the Dutch automotive industry to increase its annual revenues from Eur 12 bn to Eur 20 bn.

The Dutch automotive sector has two responses to the opportunities and challenges of today’s automotive industry: innovation and cooperation. Innovation is vital in the continuous struggle for cost reductions alongside increasing levels of quality, individuality, and personalisation, and legal requirements (e.g., noise, safety and emission). Effective cooperation is becoming more and more crucial as competitive advantage will gravitate towards those that discern their strengths and move quickly to build or join appropriate new collaborative networks.”

 

Gevonden in (p.7): Vision for the Dutch automotive sector

80% Driverless future A policy roadmap for city leaders Page 12 report AVs will reduce demand for parking, gas stations, and other auto-related land uses. Some uses, particularly those in highly desirable areas, may be reused and repurposed over time. AVs are highly likely to reduce parking demand by taking personally owned automobiles off the street. Past studies estimate that, depending on the success of merging AV into city infrastructure, parking demand may be reduced by up to 90%. Parking, roads and other auto-related uses occupy a significant amount of land. The U.S. contains as many as two billion parking spaces, occupying up to 16,000 square miles of land (the equivalent of Connecticut and Vermont combined). The quantity of parking spaces in the country amounts to as many as eight parking spaces for every car. Parking consumes a significant amount of land, especially in suburban areas where auto use is highest and surface lots are more common than multi-story garages. At a typical suburban mall, parking or driveways make up 80% of the land, while only 20% is used for the mall. Even in denser, more urban areas, parking requires significant land area. For example, streets and parking take up 45% of land in downtown Washington, D.C. and up to 65% in downtown Houston.

80% Driverless future A policy roadmap for city leaders Page 3 report Prioritize and modernize public transit. The role of transit will evolve as AVs and shared mobility become widespread. Transit agencies should focus on high-frequency, high-capacity services in dense urban corridors (such as rail, bus rapid transit), provide first and last-mile connections through driverless shuttles, and expand kiss-and-rides/mobility hubs.

IMPACT-Digitale Infrastructuur

50% 

Zoeken naar strepen op het asfalt

Page 4 of document : Jene van der Heide, Senior adviseur Strategie en Beleid bij het Kadaster: ‘Voor kaartenmakers is het te duur om ook de afgelegen wegen in het buitengebied in kaart te brengen. En de overheid verzamelt uitsluitend informatie die nodig is voor het onderhoud van zulke wegen. Rijd je zo’n gebied binnen, dan vraagt een zelfrijdende auto waarschijnlijk aan zijn bestuurder om het even van hem over te nemen. Het kan zomaar 10 jaar duren voordat dit verschil tussen buitengebied en snelweg is weggewerkt.’

70%

State of Art on Infrastructure for Automated Vehicles

Chapter 6

This  section  summarizes,  based  on  insights  from  the current scientific literature, projects, test sites, and  initiatives,  the  implications  of  vehicle  automation  on  the  infrastructure  for  each  SAE  level  of automation (in each case assuming 100% penetration level). According to Shladover (31) level 5 will not be here until 2075, while level 3 is problematic because of the difficulty to attain drivers’ attention after  being  out  of  the  loop  and  because  some  automakers  simply  will  not  attempt  level  3.  However, level 4 automation will probably be realized within the coming decade. In Table 6 a first attempt was made to summarize the requirements from the physical infrastructure to facilitate vehicle automation, followed by Table 7 which summarizes the requirements from the digital infrastructure. These results should  be  considered  with  caution,  as  many  of  the findings  from  the  scientific  literature  were  not explicitly based on empirical data and results, but on experts’ opinions.

 

50%

ROAD SAFETY WITH SELF-DRIVING VEHICLES: GENERAL LIMITATIONS AND ROAD SHARING WITH CONVENTIONAL VEHICLES

Chapter 3.2.1

Gomes(2014) argued that, “all 4 million miles of U.S. public roads will need to be mapped, plus driveways, off-road trails, and everywhere else you’d ever want to take the car” and this information would need to include “locations of street lights, stop signs, crosswalks, lane markings, and every other crucial aspect of a roadway.”

70%

Zoeken naar strepen op het asfalt

Page 5 report: Welke rol is weggelegd voor de overheid?

‘Past de definitie die de overheid hanteert voor een wegvak op de definitie die de automobielindustrie heeft van een wegvak? Dat loopt waarschijnlijk scheef. Want geautomatiseerde auto’s onderscheiden wegvakken in verband met verschillen in rijgedrag, en de overheid onderscheidt wegvakken in verband met de planning van beheer- en onderhoudswerkzaamheden.

Het Kadaster kan kaartenmakers helpen bij het opbouwen van een statisch wereldbeeld. Maar kaartenmakers hebben behoefte aan meer detail. Die extra nauwkeurigheid is niet alleen handig voor geautomatiseerd rijden, maar ook voor het beheer van de openbare ruimte. De afweging waar de overheid voor staat, is of ze zelf gaat investeren in de extra nauwkeurigheid, of dat ze het overlaat aan de markt.’ ‘Zeker als het gaat om statische informatie die ‘in advance’ beschikbaar is voor zelfrijdende auto’s, kan de overheid als leverancier een grote rol spelen. Andersom kan het voor wegbeheerders handig zijn om van autofabrikanten informatie af te nemen die met sensoren en camera’s ‘on the fly’ is verzameld, bijvoorbeeld over kuilen in de weg.

‘Ik zie een verschuiving in de rol van de overheid, van producent van kaartinformatie naar platform voor kaartdiensten, ook de betaalde diensten van kaartenmakers. De vraag is welke investeringen we moeten doen om die rol goed in te vullen? En we moeten nu alvast nadenken over de consequenties van de nieuwe verhoudingen. Gaat de overheid betalen voor de kaarten die ze voor haar eigen doelen nodig heeft?’ Stephen

T’Siobbel, Sr. Project Manager Advanced Driving bij TomTom Maps: ‘Ik denk niet dat TomTom ooit  kadasterkaarten gaat maken. Ik ga er van uit dat de overheid voldoende eigen use cases heeft om zelf topografische en kadastrale kaarten te beheren en te onderhouden. Net zomin als overheden kaarten zullen samenstellen die direct geschikt zijn voor private kaartenmakers, zullen kaartenmakers producten leverden die direct geschikt zijn voor overheden. Daarvoor zijn de verschillen te groot. Wel zullen onze kaarten voor Automated Driving over specifieke attributen beschikken die ook voor overheden relevant kunnen zijn, bijvoorbeeld informatie over het type van vangrails, of de exacte breedte van een rijstrook.’

IMPACT-Infrastructuur

90%

Rapport Zelfrijdende auto’s, verkenning van implicaties op het ontwerp van wegen

Chapter 3.3
– Als  begrenzing  van  rijstroken  is fysieke  markering belangrijk, naast de eventueel al toe te passen   digitale  markering.   Dat   geldt  voor   alle   wegonderdelen.   De   markering  moet   goed waarneembaar  zijn,  door  in-car  sensoren  (camera’s)  en door  de  menselijke  bestuurder,  bij verschillende weers- en lichtcondities.

-Naarmate  de  automatiseringsgraad  toeneemt,  zijn  er steeds  meer  voertuigen  die  op smallere rijstroken kunnen rijden. Echter bestuurders van voertuigen die nog niet geautomatiseerd koers houden, zijn gebaat bij de huidige rijstrookbreedte (vrees marge en vetergang). Rijstroken kunnen dus   nog   niet   overal   smaller   gemaakt   worden.   Als   tussenoplossing   kunnen smallere doelgroepstroken voor de hogere SAE level voertuigen worden geïntroduceerd.

-Aanpassingen van het dwarsprofiel en de berminrichting (redresseerstrook, obstakelvrije zone, vluchtstroken) kunnen nog niet plaats vinden.

-Boogstralen kunnen ook nog niet aangepast worden. Wel zou overwogen kunnen worden om in bogen  met meer  stroken  de manueel  bestuurde voertuig en  alleen  in  de  buitenste  strook/stroken toe  te  staan  en  de  binnenste  strook/stroken  te  reserveren voor  automatische voertuigen  die  hun snelheid   kunnen   optimaliseren   op   de   infrastructuurkenmerken   en   de   voorkeuren   van   de inzittenden.  Een  risico  is  dat  manueel  bestuurde  voertuigen  het  gedrag  van  automatische voertuigen gaan imiteren, wat ertoe zou kunnen leiden dat ze met een te hoge snelheid de bocht in gaan. Ook de korte volgtijden van automatische voertuigen zouden overigens door menselijke bestuurders geïmiteerd kunnen worden. Dat geldt ook op andere wegonderdelen.

-Over  het  algemeen  geldt  dat  de  mix  van  verschillende voertuigtypen  een  aanvankelijk  wat onvoorspelbaar  verkeersbeeld  kan  geven.  Dat  heeft  met name invloed op de dimensionering van  uitwisselpunten. (in- en uitvoeger, weefvak, kruispunt, rotonde). De mix van voertuigen van verschillende  SAE  levels  kan  zorgen  voor  interactie  tussen  de  verschillende  voertuigtypen  die tegen  de  intuïtie  van  menselijke  bestuurders  ingaat. ZRA’s  gedragen  zich  anders  dan  de bestuurders van niet-ZRA’s, of bestuurders van voertuigen met een lager SAE level, op basis van hun intuïtie verwachten. De uitwisseling op sommige plaatsen is mogelijk te complex voor ZRA’s, die   nog   niet   met   elkaar   communiceren   en   meer   tijd   nodig   hebben,   door   de   grotere veiligheidsmarges  dan  die  die menselijke  bestuurders aanhouden  en vroegtijdig  remmen.  Dit  zal ertoe   kunnen  leiden   dat   uitwisselpunten   (in-   en   uitvoegstroken,   weefvakken)   eerst   ruimer gedimensioneerd  moeten  worden.  Dat  sluit  aan  bij  de praktijkobservatie  dat  ACC in  zijn huidige vorm leidt tot grotere volgafstanden.

-Voor onderliggende wegen geldt dat met name de interactie  met  langzaam  verkeer  (fietsers  en voetgangers) veel dilemma’s oplevert. Daardoor wordt de situatie veel complexer en daarvoor zijn op  dit  moment  nog  geen  (veilige)  oplossingen  beschikbaar.  Op  gebiedsontsluitingswegen  met gescheiden verkeersstromen gelden dit ook (op kruispunten en rotondes).

-Bij gemengd verkeer dient nog vastgehouden te worden aan het originele kruispuntontwerp en voorrangsregels.  De  ZRA  moet  zich  zoveel  aan  de  menselijke  bestuurders  aanpassen,  zodat verwarring voorkomen wordt bij bestuurders van niet-automatische voertuigen. Mogelijk heeft het automatische voertuig meer tijd  nodig  om  de  situatie op  een  kruispunt  in te  schatten,  als  er  niet met alle voertuigen in de buurt gecommuniceerd kan worden.

-Doorzicht op een rotonde is voor een ZRA, die communiceert met het overige verkeer, geen probleem, voor menselijke bestuurders wel.

– (truck) platooning brengt nog de nodige vragen met zich mee, als het streven is om vrijwel continu te  kunnen  platoonen  (dus  niet  moeten  opsplitsen  bij ieder  knooppunt)  om  de  voordelen  vanplatooning te kunnen behalen

Uit  het  bovenstaande  ontstaat  het  beeld  dat  de  mogelijke  consequenties  voor  het  wegontwerp  in  de situatie  met  gemengd  verkeer  waarschijnlijk  nogal  beperkt  zullen  zijn  (ofwel  dat  je  niet  veel  kunt veranderen  aan  het  wegontwerp  zolang  er  gemengd  verkeer  is).  Bij  gemengd  verkeer  kan  er  in  eerste instantie niets veranderd worden aan het ontwerp, dat gebaseerd is op wat menselijke bestuurders nodig hebben  om  veilig,  vlot  en  comfortabel  te  rijden.  Alleen  op  wegen  met  veel  capaciteit/rijstroken  kan overwogen  worden  een  deel  hiervan  voor  ZRA’s  te  reserveren en dit deel ook een nieuw wegontwerp te geven (scheiding in het dwarsprofiel van ZRA en niet-ZRA).

Smart Infra, Eerste schetsonderzoek naar level 4 snelwegen en kruispunten voor zelfrijdende auto’s

Chapter 5

Voor de transitiefase geldt dat zowel de zelfrijdende voertuigen als de conventionele voertuigen gebruik maken van dezelfde rijbaan. Zolang de conventionele voertuigen gebruik maken van de rijbaan zullen deze, ten behoeve van de verkeersveiligheid, maatgevend z

ijn voor de ontwerpcriteria aan de rijbaan. In de transitiefase is het daarom naar verwachting niet wenselijk versoberingen aan het ontwerp van autosnelwegen door te voeren.

Bij een gescheiden transitie zal er een doelgroepenstrook aan de linkerzijde van de rijbaan worden aangewezen voor de zelfrijdende voertuigen. In het geval dat de doelgroepenstrook als extra strook wordt toegepast, zullen de overige stroken versmald moeten worden en wellicht dat de vluchtstrook moet worden opgeofferd. Beide maatregelen leiden tot een

afwijking van de vigerende richtlijn (ROA 2014) en hebben mogelijk een negatief effect op de

verkeersveiligheid van met name de conventionele voertuigen. Met de extra strook wordt de totale capaciteit van de weg wel vergroot.

 

“Automated driving, with its minimal space requirements and rather equal speed levels, could at least double the existing average road infrastructure capacity. “

Gevonden in (p.380): Autonomous Vehicles and Autonomous Driving in Freight Transport

 

80% Driverless future A policy roadmap for city leaders Page 12 report AVs will reduce demand for parking, gas stations, and other auto-related land uses. Some uses, particularly those in highly desirable areas, may be reused and repurposed over time. AVs are highly likely to reduce parking demand by taking personally owned automobiles off the street. Past studies estimate that, depending on the success of merging AV into city infrastructure, parking demand may be reduced by up to 90%. Parking, roads and other auto-related uses occupy a significant amount of land. The U.S. contains as many as two billion parking spaces, occupying up to 16,000 square miles of land (the equivalent of Connecticut and Vermont combined). The quantity of parking spaces in the country amounts to as many as eight parking spaces for every car. Parking consumes a significant amount of land, especially in suburban areas where auto use is highest and surface lots are more common than multi-story garages. At a typical suburban mall, parking or driveways make up 80% of the land, while only 20% is used for the mall. Even in denser, more urban areas, parking requires significant land area. For example, streets and parking take up 45% of land in downtown Washington, D.C. and up to 65% in downtown Houston.

70% State of Art on Infrastructure for Automated Vehicles

 (See figure in Chapter 6))

This  section  summarizes,  based  on  insights  from  the current scientific literature, projects, test sites, and  initiatives,  the  implications  of  vehicle  automation  on  the  infrastructure  for  each  SAE  level  of automation (in each case assuming 100% penetration level). According to Shladover (31) level 5 will not be here until 2075, while level 3 is problematic because of the difficulty to attain drivers’ attention after  being  out  of  the  loop  and  because  some  automakers  simply  will  not  attempt  level  3.  However, level 4 automation will probably be realized within the coming decade. In Table 6 a first attempt was made to summarize the requirements from the physical infrastructure to facilitate vehicle automation, followed by Table 7 which summarizes the requirements from the digital infrastructure. These results should  be  considered  with  caution,  as  many  of  the  findings  from  the  scientific  literature  were  not explicitly based on empirical data and results, but on experts’ opinions.

80%

Automated Vehicles. The Coming of the Next Disruptive Technology

Benefits page 17 report

With AVs, the demand for parking will decrease substantially because an AV can relocate itself to an area of free parking. Or, as an automated taxi, it can pick up its next ride. In some cases, a commuter can send the car home for his/her spouse to use.

 

Besides changes in parking spots Urban land use is expected to change as well with the implementation of AV’s. This Autonomous Driving and Urban Land Use report discusses the possible effects.

IMPACT-Veiligheid

60%

ROAD SAFETY WITH SELF-DRIVING VEHICLES: GENERAL LIMITATIONS AND ROAD SHARING WITH CONVENTIONAL VEHICLES

Chapter 3/ Conclusion

Self-driving vehicles could compensate for some but not all crashes caused by other traffic participants (Pedestrian error could be compensated by AV). Lighting failures might turn out to be irrelevant to safety from the perspective of being able to control one’s vehicle at night, because self-driving vehicles might not rely on visual input. / (1) The expectation of zero fatalities with self-driving vehicles is not realistic. (2) It is not a foregone conclusion that a self-driving vehicle would ever perform more safely than an experienced, middle-aged driver. (3)During the transition period when conventional and self-driving vehicles would share the road, safety might actually worsen, at least for the conventional vehicles.

Safety Benefits of Automated Vehicles: Extended Findings from Accident Research for Development, Validation and Testing

17.4  Significance of Possible Predictions based on Accident Data

 

60% 

Zoeken naar strepen op het asfalt

Introduction page 4 of document

Van de 33.000 verkeersslachtoffers die de VS jaarlijks betreurt, zijn er volgens deskundigen 22.000 te voorkomen als we de mens achter het stuur vandaan halen.

Tomorrow’s Road Infrastructure for Automated Driving

Slide 11

Point made by an online respondent of a survey:

“I am extremely concerned that proponents have little regard to or understanding of the level of reliability required to class any of these systems as safe . For example in regard to Google cars : ‘Ultimately, Google aims to provide a solution for the millions of car accidents that occur worldwide – 93 percent due to human error .’Statement is misleading/ wrong . Human factors contribute to 93 percent of crashes but many other factors also contribute. And the most responsible drivers cause a crash where someone is injured around once in 2,000,000 Miles. And public would expect autonomous cars to have a much lower rate-say once in 20,000,000miles.That requires a system that will not fail/malfunction more than once in ~ 80 vehicle lives or once in 1250 years of average driving.”

The Release of Autonomous Vehicles

Chapter 21.1

70%

Automated Vehicles, Are we ready ?

Chapter 3.3

AVs are capable of providing large amounts of data that could assist investigation in case of a crash. By recording the actions and forces involved in the minutes before and after a crash, they may help determine the cause of the crash and assist in resolving any liability dispute.

Motoring of the future

Point 33, page 15 in report

Telematics also known as ‘black boxes’ monitor the location of a driver and driving performance.

Safety Benefits of Automated Vehicles: Extended Findings from Accident Research for Development, Validation and Testing

However, a safety prognosis of highly or fully automated vehicles depends on assumptions, as so far no series applications of such features exist. For testing methods in order to develop and validate safe automated vehicles with reasonable expenditure, the author recommends combining area-wide traffic, accident, weather, and vehicle operation data as well as traffic simulations.

Two questions discussed in paper:

–What significance do analyzes and findings from road-accident research hold for the introduction of automated vehicles?

–How can the potential safety benefits of automated vehicles be established?

The validity of accident data regarding potential safety benefits varies considerably depending on the collection method.

70%

Safety Benefits of Automated Vehicles: Extended Findings from Accident Research for Development, Validation and Testing
17.1 introduction

→ report goes into more detail
For testing methods in order to develop and validate safe automated vehicles with reasonable expenditure, the author recommends combining area-wide traffic, accident, weather, and vehicle operation data as well as traffic simulations. Based on these findings, a realistic evaluation of internationally and statistically relevant real world traffic scenarios as well as error processes and stochastic models can be analyzed (in combination with virtual tests in laboratories and driving simulators)to control critical driving situations in the future.

Self-Driving Regulation, Pro-Market Policies Key to Automated Vehicle Innovation
50%
One important challenge, which is expected to be met by late 2014 or early 2015 , is providing sufficient evidence that road – tested autonomous vehicles are in fact safer than manually driven vehicles. As Bryant Walker Smith of Stanford Law School has noted, a high degree of statistical confidence must be reached in order for automakers and component developers to begin scaling up technology deployment beyond testing.

Google’s self- driving cars have logged over 500,000 miles on U.S. public roads to date. To demonstrate their safety over manually driven vehicles with 99 percent confidence, Google will need to log approximately an additional 200,000 miles of crash-free automated driving (see Table 2).

60%

The Release of Autonomous Vehicles

21.3  Requirements for a Test Concept

In order to discuss in the following section why full automation poses a particular challenge for safety validation, we will first describe the requirements for test concepts to assess safety. These are divided into effectiveness and efficiency criteria.

21.5.1 Validity of the current test concept for autonomous driving

At present, real driving is the most important method for the approval; the reason for this, in particular, is the validity combined with the justifiable economic overhead. However, along with the economic overhead, autonomous driving also presents a systematic challenge for the known methods. At present, real driving stands for driving in public road traffic with test drivers. The task of the test driver is to drive or supervise the vehicle in every situation in accordance with the task of the vehicle user. Transferred to autonomous driving, the use of a test driver in the driver’s seat would be non-real behavior of a user, as the user does not have to supervise the vehicle and the environment anymore and intervene.

Motoring of the future

Point 64, page 27 in report

50%

Witnesses discussed the research evidence for the effectiveness of different systems. Professor Sampson said that it was very difficult to research which technologies were most effective in terms of reducing accidents, because of the difficulties in running controlled trials of different features, with sufficient numbers of vehicles. Professor Carsten explained that the key struggle was with the continual monitoring and evaluation of technology, and developing an understanding of how casualty rates were affected over time by different technologies.

He explained that while it was statistically possible to show the safety benefits arising from car impact regulations, it was “really hard” to do this in relation to other safety approaches.

IMPACT-Verkeersafwikkeling

70%

The Effect of Autonomous Vehicles on Traffic

Chapter 16.4.2

The models developed for traffic flow and capacity, assuming a given share of autonomous vehicles, show that capacity increases disproportionately highly as the share of autonomous vehicles increases. It should be noted that the shortening of the time gaps comes into effect as early as the first autonomous vehicle; the speed increase at high densities, however, will only be possible for purely autonomous traffic. The introduction of autonomous vehicles will succeed, in the opinion of the author, only in their ability to move safely in mixed traffic, as reserved transit areas would not be socially or economically acceptable, particularly with a low share of autonomous traffic. However, once a sufficient number of vehicles with autonomous capabilities are participating in traffic, it will be very beneficial to the transport efficiency to create reserved lanes for autonomous driving. The benefits of autonomous vehicles can be maximized by separation due to the nonlinear course of the capacity once non autonomous vehicles are added to autonomous traffic. In conjunction with specially dedicated lanes, the column speed could also be increased even when traffic demand is higher, which would lead to further significant capacity gains. This is not possible in mixed traffic, since even in trafficwith only a few human-driven vehicles, these would dictate the speed.
50%

Autonomous Driving: Disruptive innovation that promises to change the automotive industry as we know it

Page 7 report

Looking forward, we project “Level 3: limited self-driving automation” to be available by 2018-2020 with features such as highway chauffeur (automated driving on highways). Furthermore, we expect “Level 4: full self-driving automation” to be first offered for low speed situations by 2020-25 (e.g., in parking lots or low-speed areas) and eventually, including more complex operations to be offered by 2025-30 (e.g., city driving). Even with the introduction of new technologies, we do not expect global adoption of full self-driving automation with “door-to-door” capabilities across all vehicle segments before 2030-40.

 

50%

Methodische Verkenning Zelfrijdende Auto’s en Bereikbaarheid

Hoofdstuk 2.6

ACC kan zowel een klein negatief als een klein positief effect hebben op de capaciteit (~ -5% -+10%). Voor CACC rapporteren de meeste studies een kwadratische toename van de capaciteit als penetratiegraad toeneemt met een maximale theoretische toename van 100% (verdubbeling). ACC en CACC hebben een positief effect op de stabiliteit. Bij hogere penetratiegraden ontstaan minder schokgolven en isde duur van de schokgolven aanmerkelijk korter.

 

The Effect of Autonomous Vehicles on Traffic

16.3 Gives theory for why capacity increases of purely AV traffic

80% Driverless future A policy roadmap for city leaders Page 3 report Prioritize and modernize public transit. The role of transit will evolve as AVs and shared mobility become widespread. Transit agencies should focus on high-frequency, high-capacity services in dense urban corridors (such as rail, bus rapid transit), provide first and last-mile connections through driverless shuttles, and expand kiss-and-rides/mobility hubs.

50%

Methodische Verkenning Zelfrijdende Auto’s  en  Bereikbaarheid
Chapter 2.2.1 (Capacity with and without bottlenecks mixed AV non AV)

Arnaout en Bowling (2011) vonden voor een weg met 4 rijstroken in een scenario met en zonder oprit dat CACC een positief effect op de capaciteit heeft (tot +60% bij een penetratiegraad van 100%) als de penetratiegraad groter is dan 40% en de instroom hoog genoeg is. Bij lagere penetratiegraden was het positieve effect klein. Als de instroom laag is (vrije doorstroming), vonden ze geen effect op de capaciteit. Ze veronderstelden dat CACC voertuigen een volgtijd van 0,5 seconde aanhouden als ze achter een ander CACC-voertuig rijden en 0,8 tot 1,0 seconde (uniform verdeeld) als ze achter een ander voertuig rijden. Of men in praktijk deze korte volgtijden durft aan te houden is een grote uitdaging volgens hen (Shladover, Su, & Lu, 2012).

De CACC-voertuigen kunnen hun voorliggers volgen zonder dat de bestuurder gas hoeft te geven of hoeft te remmen; de bestuurder moet wel het voertuig in de strook houden. Er werd een overbelaste snelweg in gemodelleerd, met een lengte van 6,5 km en een snelheidslimiet van 105 km/uur zonder bottleneck . In de simulaties waren vier voertuigtypen aanwezig:

70%

Traffic Control and Traffic Management in a Transportation System with Autonomous Vehicles

Chapter 15.8 Conclusion

It was demonstrated in Sect.15.4, for example, that the capacity of a traffic signal can certainly be doubled. If the demand is low at the corresponding signal,this doubling is scarcely noticeable. But if the signal is working at the limits of its capacity, by contrast, even a minor increase in its capacity can lead to a dramatic

Improvement.

This can be observed quite clearly in the scenario in Sect.15.5: here the demand runs the values from very low to (temporary) over-saturation. Although the introduction of autonomous vehicles has little impact on green times and delays when demand is low, it yields major improvements when the system is operating beyond capacity. Nevertheless, the magnitude of these improvements does depend on the details of the scenario being examined. If the peak value for demand were just a bit lower, the benefit would also be significantly diminished. That notwithstanding, it may be asserted with confidence that at least in the urban context, the introduction of autonomous vehicles has the potential to generate substantial time gains at traffic signals which would then be available for other road users—if the introduction of these vehicles does not lead to an increase in demand for automotive transportation

LEGAL-Privacy

De concrete vraag die daarbij hoort is: kunnen de gegevens direct of indirect, bijvoorbeeld via hetncombineren van data, worden herleid tot een persoon?nBijvoorbeeld: voertuigidentificatiegegevens (Voertuig Id Nummer en kenteken) worden alsnpersoonsgegeven beschouwd, omdat zij via de registers in veel gevallen aan een natuurlijk persoonnkunnen worden gekoppeld. Als er geen sprake is van persoonsgegevens dan is de Wetnbescherming persoonsgegevens (Wbp) en vanaf 25 mei 2018 de AVG niet van toepassing.nIn de AVG, waarbij de Europese wetgeving rechtstreeks in de lidstaten van toepassing is, is hetnbegrip persoonsgegevens uitgebreid. Locatiegegevens worden expliciet als persoonsgegevensnaangemerkt. Bovendien is door de Europese Autoriteiten Persoonsgegevens een interpretatie vannhet begrip persoonsgegevens gekozen die ertoe leidt dat het niet meer van belang is of iemandnuiteindelijk geïdentificeerd zal kunnen worden. Ook als een anoniem persoon geïsoleerd (singlednout) kan worden uit een groep, bijvoorbeeld een willekeurige weggebruiker op een bepaaldenlocatie, dan is het feit dat deze weggebruiker individueel benaderbaar is voldoende om dengegevens als persoonsgegevens aan te merken. Het is immers mogelijk om bijvoorbeeld op dienbepaalde locatie een locatie gebonden reclameboodschap aan de weggebruiker te zenden.nIn feite komt het erop neer dat de verwerkte gegevens van een gepersonifieerde smart mobilitynapp in beginsel als persoonsgegevens zullen moeten worden aangemerkt, tenzij kan wordennaangetoond dat het isoleren van personen niet mogelijk is.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

In geval van een datalek moet de verwerkingsverantwoordelijke dit zo spoedig mogelijk, maarnuiterlijk binnen 72 uur melden bij de AP, tenzij het niet waarschijnlijk is dat het lek de rechten ennvrijheden van de betrokkenen kan schaden. Tevens worden de betrokkenen zo snel mogelijkngeïnformeerd. Bij de melding aan de AP moeten de volgende meldingen worden gedaan:n• Aard en categorieën van persoonsgegevens,n• Naam en contactgegevens van de FG,n• Waarschijnlijke gevolgen van de inbreuk,n• Getroffen maatregelen.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

Als uit het antwoord op het verzoek om informatie aan de verwerkingsverantwoordelijke blijkt datner meer gegevens worden verzameld dan voor het doel van de verwerking noodzakelijk is, dannmoeten deze onmiddellijk worden verwijderd.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

De eerste voorwaarde is dat de verwerkingsverantwoordelijke moet kunnen aantonen dat erntoestemming conform de wettelijke definitie is verleend. Dat wil zeggen dat de toestemming eennvrije, specifieke, geïnformeerde en ondubbelzinnige wilsuiting van de betrokkene moet zijn. Hij/zijnmoet door middel van een verklaring of een ondubbelzinnige actieve handeling aangeven dat hij/zijnde verwerking van persoonsgegevens aanvaardt. Een ander voorwaarde is dat de betrokkene dentoestemming op ieder moment moet kunnen intrekken. Deze mogelijkheid moet voorafgaand aannde toestemming worden meegedeeld aan betrokkene. Ook moet de verwerkingsverantwoordelijkennagaan of de toestemming vrijelijk kan worden gegeven. Dit is bijvoorbeeld niet het geval bijntoestemming gegeven door werknemers in het kader van hun dienstverband.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

Dat hangt af van de omvang en de aard van de verwerking. Bijvoorbeeld of dengegevensverwerking regelmatige observatie vereist, of als er sprake is van bijzonderenpersoonsgegevens. In dat geval is een FG op grond van de AVG verplicht. Ook een vereniging ofnander orgaan dat categorieën verwerkingsverantwoordelijke vertegenwoordigd kan namens dezenbedrijven een FG in dienst nemen die vervolgens deze rol voor de desbetreffende bedrijven speelt.nDaarbij is van groot belang dat de FG onafhankelijk is van het management van de betrokkennbedrijven en van het bestuur van de vereniging.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

TECHNICAL-(Cyber)Security

50% Adviesrapport Cybersecurity Autonoom rijdende voertuigen Fox IT (2014)nnDit rapport geeft inzicht in kwetsbaarheden van moderne voertuigen, risico’s bij introductie van autonoom rijdende voertuigen en mogelijke maatregelen om deze risico’s tegen te gaan.nOndanks de dreiging die klein is, is het toch ontzettend belangrijk om goede maatregelen te nemen.Voor de korte termijn is een zestal generieke maatregelen voorgesteld waarmee het op korte termijn mogelijk is een beeld te krijgen van de beveiliging van systemen voor autonoom rijdende auto’s, daarmee van de veiligheid van het rijden erin en de beveiliging te verbeteren. Deze 6 maatregelen richten zich op het onderzoeken van autonoom rijdende voertuigen op kwetsbaarheden, deze op te lossen en op het klaar zijn voor een aanvalnmiddels een gevonden kwetsbaarheid. Gezien de verwachting dat cybercrime voor autonoom rijdende voertuigen sterk zal groeien en dat niet alle problemen van tevoren te voorspellen zijn, wordt voor de lange termijn geadviseerd te streven naar een framework waarin maatregelen zich kunnen ontwikkelen.nn10% Whitepaper Cybersecurity and PrivacynnWhite-paper about the security and reliability of connected and cooperative mobility, the interoperability between road infrastructure managers, the different brands, suppliers and systems, and the protection of personal information which is collected and used.nThe seven subjects are:n- Connected and cooperative communicationn- Standardisationn- Security by designn- The need of system (component) certificationn- PKIn- Privacyn- Behaviournn10% ERTRAC Automated Driving RoadmapnnThe main objective of the ERTRAC Roadmap is to provide a joint stakeholders view o n the development of AUtomated Driving in Europe, The Roadmap starts from common definitions and a listing of available technologies, and then identifies the challenges for the implementation of higher levels of automated driving functions. Development paths are provided for the different categories of vehicles.nThe Key CHallenges identified should lead to efforts of Research and Development: ERTRAC calls for pre-competitive collaboration among European industry and research providers. The key role of public authorities is also highlighted: for policy and regulatory needs, with the objective of European harmonisation.

90% Adviesrapport Cybersecurity Autonoom rijdende voertuigen , Fox IT (2014)nnDit rapport geeft inzicht in kwetsbaarheden van moderne voertuigen, risico’s bij introductie van autonoom rijdende voertuigen en mogelijke maatregelen om deze risico’s tegen te gaan.nOndanks de dreiging die klein is, is het toch ontzettend belangrijk om goede maatregelen te nemen.Voor de korte termijn is een zestal generieke maatregelen voorgesteld waarmee het op korte termijn mogelijk is een beeld te krijgen van de beveiliging van systemen voor autonoom rijdende auto’s, daarmee van de veiligheid van het rijden erin en de beveiliging te verbeteren. Deze 6 maatregelen richten zich op het onderzoeken van autonoom rijdende voertuigen op kwetsbaarheden, deze op te lossen en op het klaar zijn voor een aanvalnmiddels een gevonden kwetsbaarheid. Gezien de verwachting dat cybercrime voor autonoom rijdende voertuigen sterk zal groeien en dat niet alle problemen van tevoren te voorspellen zijn, wordt voor de lange termijn geadviseerd te streven naar een framework waarin maatregelen zich kunnen ontwikkelen.nn60% Comprehensive Experimental Analyses of Automotive Attack SurfacesnnGeeft inzicht in manieren van digitale inbraak van autos.n‘’We discover that remote exploitation is feasible via a broad range of attack vectors (including mechanics tools, CD players, Bluetooth and cellular radio), and further, that wireless communications channels allow long distance vehicle control, location tracking, in-cabin audio exfiltration and theft.’’nn50% Security Challenges for Cooperative andInterconnected Mobility SystemsnnIdentificeert en kwantificeert risico’s van Interconnected Mobility Systems.nn‘’The biggest security risk factors foreseen are application data integrity validation, the usage of insecure position information and systems that are currently not secure by design. These risk factors will have to be addressed in the coming years, to pave the road for successful introduction of cooperative and interconnected mobility systems’’nn20% Roland Berger Global Automotive Supplier Study 2018nnReport for the automotive industry about disruptive technology and future prospects. What is the current situation, what can we expect in the the future and what challenges and consequences does that future bring. With the focus on security of connected vehicles the following threads and accompanying tips are found:n n- Internet based attacksn- Hardware attacksn- Sensor attacksn- Near-field wireless attacksn n- Threat vectors span all connected vehicle components and systemsn- Suppliers must design E/E architectures to prevent component-level attacks and understand the design implications for integration into vehicle sub-systems.n- Organization structures and design processes must adapt accordingly.n- Evolving legal and regulatory requirements for data security & protection and product safety must be addressed as well.nn20% Veiligheidsrisico’s van Automated/Connected MobilitynnIn this paper the innovation possibilities for the Dutch state on the field of cyber security of automated/connected mobility are mapped.

ALLE KENNISVRAGEN IN DE FAQ

DEPLOYMENT-Business models

Another deployment scenario for automated driving involves implementing transportation paradigms that provide slow-moving passenger vehicles, for example in urban areas. Consumers could summon such vehicles using a smartphone app and ride them over relatively short distances (see the use case “vehicle on demand”). nnIn particular, companies from unrelated sectors can use image processing, object recognition, and route planning systems—which are already in widespread modular use—to implement transportation models with higher-order automation within a limited geographical range. The arrangements often proposed for market introduction are slow-moving and limited-area vehicles intended to serve what is known as the “first or last mile,” complementary to private automobiles or public transportation. To name one concrete example, these types of solutions could be used to reach bus and urban rail networks in areas where a regular schedule is not feasible due to inadequate infrastructure or financial limitations. nnDue to the generally rather favorable conditions, it is anticipated that various individual city governments and operators of amusement parks, shopping malls, and other large-scale facilities will introduce automated transportation systems in the short term.”nnGevonden in (p.199-200): https://www.dropbox.com/s/91n2z7i19wfgzu6/Beiker%2C%20S.%20%282016%29%20Deployment%20Scenarios%20for%20Vehicles%20with%20Higher-Order%20Automation.pdf?dl=0

 nn n

    n

  • Taxing fuel at a level that reflects these impacts could make fuel- efficient vehicles more economically attractively to buyers. Automated driving could conceivably increase fuel efficiency by reducing crashes, smoothing speeds and flows, and enabling drag-reducing platoons.
  • n

n

    n

  • Reducing parking subsidies is the second way that governments— particularly local governments—can better align the individual and social costs of motor vehicle travel. More precisely, many cities subsidize private vehicle ownership by providing free on-street parking (especially in residential areas) and by requiring new buildings to include more parking spots than the market demands.148 Cheap and plentiful parking encourages both vehicle ownership and vehicle usage.149 Conversely, making parking more expensive and less convenient could encourage the use of driverless systems that forgo parking altogether or, perhaps, advanced driver assistance systems that automate the driving task in part (such as park assist) or in whole (such as automated valet).
  • n

n

    n

  • raising insurance minimums may help to translate safety gains from automated driving into financial terms that are obvious to vehicle owners and drivers.
  • n

n nn nnGevonden in (p.35): https://www.dropbox.com/s/4xefqqbpiaid71t/Smith%2C%20B.W.%20%282016%29%20How%20Governments%20Can%20Promote%20Automated%20Driving.pdf?dl=0nn 

70% Driverless future A policy roadmap for city leaders Page 3 report Encourage adaptable parking.Fewer cars means fewer parking spaces, especially in city centers. Parking garages need to be built with housing or office conversion in mind and include level floors, higher ceiling heights and centralized ramps. These future-proof garages are already being contemplated in Boston and Nashville.

The automotive industry is a global industry in which value is generated predominantly by suppliers to automakers. The Dutch automotive industry is no exception to this rule. Within specific areas in the automotive industry, the Netherlands even plays a significant role with leading innovative companies that are involved in automotive activities worldwide. In these areas, the Dutch automotive sector is highly innovative and possesses a considerable knowledge base. To further strengthen its role, the Dutch automotive sector has developed a vision supported by a strong ambition of the Dutch automotive industry to increase its annual revenues from Eur 12 bn to Eur 20 bn.

The Dutch automotive sector has two responses to the opportunities and challenges of today’s automotive industry: innovation and cooperation. Innovation is vital in the continuous struggle for cost reductions alongside increasing levels of quality, individuality, and personalisation, and legal requirements (e.g., noise, safety and emission). Effective cooperation is becoming more and more crucial as competitive advantage will gravitate towards those that discern their strengths and move quickly to build or join appropriate new collaborative networks.”

 

Gevonden in (p.7): Vision for the Dutch automotive sector

There are multiple models/players:

The Branded Integrated Life-Style Model

It’s a sleekly designed experience, riding in this self-driving car. As elegantly designed as the sleekest smart phone.You use an app on your phone to summon your car when you need it or to program a daily pick-up. It’s as simple as setting the alarm on your phone.Your windshield doubles as a screen, synching seamlessly with your other connected devices. As you ride along, you swipe through applications and web sites, checking your progress and the local weather on a digital dashboard, uploading photos to your favorite web site or watching a video. When you arrive at your destination, the screens you’ve opened are synched and waiting for you on whatever device you pick up next.

In this model, perhaps a company with no traditional presence in the auto industry that is already an integral part of the consumer’s life outside the vehicle could become a key participant in the ecosystem. Since self-driving vehicles will no longer need the same level of rigorous testing and validation, and manufacturing could potentially be outsourced, their emphasis would be on consumer research, product development, and sale of integrated lifestyle experiences.

The Branded Lifestyle Value Proposition: Design, Technology, Software, Consumer experience

The Open System Model

It’s all about the data and how to use these data to customize the consumer value proposition.The market for big data

is growing exponentially. Market intelligence provider IDC predicts that by 2015 the “Big Data” market will be $16.9 billion, up from $3.2 billion in 2010.35 A major player in the data market might not want to manufacture vehicles, but could

well design a vehicle operating system. With more than a billion cars serving up trillions of data points about consumer behavior, traffic patterns, and topography, an operating system (OS) developer could afford to give away the OS but accrue significant value from the data they could aggregate. Who would manufacture the vehicle? The OS provider could partner with any of the world’s vehicle manufacturers—and not just the traditional automotive manufacturers. Partnerships could be established with one or more new players who might compete in the branded technology arena.

The Open System Value Proposition: Utility, Technology, Customization

Mobility On Demand Model

Zipcar was the pioneer in the shared-vehicle field, but other players are breaking into the market. Whereas current mobility on demand providers must make vehicles easily accessible for customers in urban areas, their vehicle maintenance and parking fees are high. With self-driving vehicles, proximity to end-users would no longer be necessary. Vehicles could be dispatched by taxi and car service companies.

Giant retailers with a core competence in managing complex distribution channels or fleet providers with the capability

to manage the complexity of renting and allocation of fleets could enter the fray and accrue significant value in the new ecosystem. New entrants in the market might compete at either end of the spectrum—with generic, low-cost utilitarian transportation on demand at one end (the low-cost airline model) and super-luxury mobile executive suites and sleeping pods at the other (the first class or private jet experience). Success will be determined by efficiency, reliability, flexibility, vehicle maintenance, customer service, ease of human-vehicle interface, and integration with existing consumer devices—and all the other psychographic factors that determine consumer behaviors and brand preferences.

The Mobility on Demand Value Proposition: Flexibility, Reliability, Convenience, Cost

The OEM Model

Traditional automotive manufacturers have decades of experience in designing and manufacturing vehicles, and shaping an emotional connection with consumers. But will they move fast enough to maintain their brand dominance? Smart automotive manufacturers should be planning now, thinking about how to restructure their organizations and what potential strategic investments they should be making. History has not been kind to those who get stuck protecting the status quo in the face of disruptive change. In fact, collaboration is already taking place across the ecosystem as companies strive to stay relevant.The joint project between Intel and DENSO36 to develop in-vehicle communication and information systems exemplifies the new cross-industry synergistic relationships.

Vertical integration is an option for companies looking to bring a critical skill or technology in house. Some vehicle manufacturers have established venture capital subsidiaries to invest in promising new technologies as a means of bridging any skill or technology gaps. Doing so may provide a competitive advantage in this rapidly evolving ecosystem.

The OEM Value Proposition: Design, Technology, HMI, Supply Chain Management “

Gevonden in (p.32-33): Self-Driving Cars, The Next Revolution

Het antwoord kan indirect gevonden worden:

“There have been numerous predicted monetary advantages linked to the adaptation of Autonomous Vehicles for daily commuting and travelling. First estimations state that self-driving cars can contribute up to $1.3 trillion in annual savings to the United States economy alone, and an expected sum of $5.6 trillion for global savings (Bartl 2015). “

Gevonden in (p.30): Impact of Autonomous Vehicles on Urban Mobility

 

Regarding making PT more flexible:

Such a transformation of the system could also breathe new life into ideas of financing basic public-transportation services—on the one hand in the form of pay-as-you-drive, but also on a flat-rate basis financed via taxes or levied on all citizens, as is often debated for cities. Also, a high service density in suburban and even rural areas would justify a flat-rate levy and could in the process help to reduce private car use.”

Regarding offering new service options for PT:

Concerning intermodality, possibilities include more public transport services, even in the suburban and rural areas mentioned above (for urban areas, see Chap. 11). The benefits resulting from the use of autonomous vehicles are equally true in spatial and temporal terms, that is both for districts on the outskirts and off-peak hours. An economic lower limit resulting from frequency of use also applies here, however, even in view of the saved labor costs. This also means that a spatially highly dispersed use can only be covered to a limited extent by providing larger fleets. In any case, operating these vehicles would have to pay for itself in terms of initial outlay and operating costs.”

Gevonden in (p. 186 & 187): New Mobility Concepts and Autonomous Driving: The Potential for Change

OV & Personenauto:

“Transport is an expression for the satisfaction of mobility needs with different means of transportation—for everyday travel, people walk, cycle, drive or take public transport. There are two main groups here: people with a distinct preference for using private vehicles, and people who prefer so-called “ecomobility”—the combination of public transport with walking and cycling [1]. In addition, a group has been emerging for some years of “multimodal” users, who no longer restrict themselves to a particular mode or mix of modes, but rather exhibit a wide range of modal use in their personal repertoire [1, 2]. This gradual transformation in behavior has coincided with the development of new mobility concepts that, firstly, involve a further development of conventional carsharing [3], but also supplement established ridesharing with new forms. New concepts already in operation include flexible carsharing fleets, such as those of Car2Go, DriveNow and Multicity, that are available as mobility services in cities in Germany, and across Europe and the USA. In parallel to this has been the emergence of so-called peer-to-peer services, where private owners make their vehicle available to a community of members via an internet platform. On online platforms such as Mitfahrzentrale and Zimride, private individuals offer rides on routes and at times when they themselves will travel in any case. Additionally, more and more services such as Uber and Lyft are currently starting up, where the distinction between (semi-)professional individual transportation, comparable to taxi services, and “standard” ridesharing is not always so clear-cut. The new forms of car and ridesharing services have primarily arisen in the major cities and metropolitan areas of industrialized countries.

What is new, and also special, about these mobility concepts is the high degree of flexibility they offer users. Flexible carsharing vehicles are available at any time and for any duration, with no pre-planning. The new ridesharing services are similarly flexible, although in this respect they resemble conventional taxis. One essential prerequisite for the emergence of all new mobility concepts is the possibilities that information and communications technology now offer for networking vehicles, users, and operators. This is what makes fundamentally fast and easy access to vehicles or services via the internet or smartphone apps possible in the first place. Access, in the sense of the physical distance between the user’s location and the vehicle, is still a hurdle, however, particularly in areas where vehicle density is not very high.

With the introduction of autonomous vehicles, it seems possible to appreciably extend and diversify existing mobility concepts. Accessing and egressing a vehicle is changing, in that the user no longer goes to the vehicle, but the vehicle comes to the user. Vehicles themselves are becoming usable for a wider section of the population, e.g. those with impaired mobility. New forms of public transport are possible, also in the sense of further blurring the boundaries between private and public transport.”

Gevonden in (p. 174): New Mobility Concepts and Autonomous Driving: The Potential for Change

 

Vracht & Logistiek:

Een tabel met details tav truck platoon businesscases (box 5, voor carriers): Gevonden in (p.25): Truck-Platooning-Driving-the-future-of-Transportation

 

“Transport data analysis revealed that most feasible platooning trips have their origin and destination relatively close to each other (less than 100km).  
When fuel consumption saving is only benefit:. The shorter the distance the more bennefit, see tabel 4.2 in (p. 34 & 36): Truck Platooning – Enablers, Barriers, Potential and Impact

 

Google has no intention of challenging the automakers on their playing eld. It will change the game and introduce a disruption in the auto industry by providing various technologies and services rather than selling cars. It plans to release the following four technologies within four years:

  • Autonomous mobility services such as “robo-taxi” (this has the potential of reducing the car owner- ship by a factor of three)
  • Producing and selling specialized maps and software
  • Technology for monitoring systems to reduce congestion
  • Technology for robotics (probabilistic inference, planning & search, localization, tracking and control) “

Gevonden in (p. 10): Self-Driving Cars: Disruptive or Incremental?

 

N.B. Hier wordt gerefereerd naar “communication” en “sensor” technologien, echter, heeft grote overlap met de termen coöperatief en autonoom.

The convergence of communication- and sensor-based technologies could deliver better safety, mobility, and self- driving capability than either approach could deliver on its own. As Pri Mudalige, staff researcher for General Motors’ Global R&D, puts it, “V2V technology…may simplify the all-sensor- based automotive advanced driver-assist systems, enhance their performance, and make them more cost effective.”

Convergence would help reduce the cost and complexity of stand-alone solutions. Adding DSRC would eliminate the need for the more expensive sensors and bring down the cost of the overall package.”

Gevonden in (p. 14): https://www.dropbox.com/s/fwrk6zjze93x7ri/KPMG%2C%20Self-Driving%20Cars%20Next%20Revolution.pdf?dl=0

In Nederland wordt de samenwerking vanuit het Ministerie van IenM geregeld.

Another deployment scenario for automated driving involves implementing transportation paradigms that provide slow-moving passenger vehicles, for example in urban areas. Consumers could summon such vehicles using a smartphone app and ride them over relatively short distances (see the use case “vehicle on demand”).

In particular, companies from unrelated sectors can use image processing, object recognition, and route planning systems—which are already in widespread modular use—to implement transportation models with higher-order automation within a limited geographical range. The arrangements often proposed for market introduction are slow-moving and limited-area vehicles intended to serve what is known as the “first or last mile,” complementary to private automobiles or public transportation. To name one concrete example, these types of solutions could be used to reach bus and urban rail networks in areas where a regular schedule is not feasible due to inadequate infrastructure or financial limitations.

Gevonden in (p.199-200): https://www.dropbox.com/s/91n2z7i19wfgzu6/Beiker%2C%20S.%20%282016%29%20Deployment%20Scenarios%20for%20Vehicles%20with%20Higher-Order%20Automation.pdf?dl=0

 

Note Joop: in Nederland  zijn er proeven bekend met de verbinding naar het station Ede vanuit de Campus Wageningen (WEPODS), en in 2018 met de WEPOD naar airport Weeze in Duitsland. In de regio MRDH bij Airport Rotterdam.

De meningen zijn verdeeld en afhankelijk van aannames over de toekomst:

Hier wordt het niet waarschijnlijk verklaard:

“Less likely, even if repeatedly cited by the scientific community, is the conversion of the entire vehicle fleet into vehicles that are on the road on a sharing basis or operated by public transport providers. There are currently no indications that private cars are losing any of their attraction.”

Maar hier wordt een scenario geschetst waarin PT geïndividualiseerd wordt:

One possible first step in individualizing public transport could be company buses, such as the so-called Google Bus, equipped with WiFi access and operating in and around San Francisco, which brings the company’s employees to work. In this case, a specific community gets together in a communal shuttle. Comparable concepts, albeit in manifold varieties, are conceivable and appear particularly attractive when based on autonomously driven vehicles. “

Gevonden in (p. 180 & 186):

https://www.dropbox.com/s/i3wankjtjm4y1xc/Lenz%2C%20B.%20%26%20Fraedrich%2C%20E.%20%282016%29%20New%20Mobility%20Concepts%20and%20Autonomous%20Driving%20-%20The%20Potential%20for%20Change.pdf?dl=0

 

Another deployment scenario for automated driving involves implementing transportation paradigms that provide slow-moving passenger vehicles, for example in urban areas. Consumers could summon such vehicles using a smartphone app and ride them over relatively short distances (see the use case “vehicle on demand”).

In particular, companies from unrelated sectors can use image processing, object recognition, and route planning systems—which are already in widespread modular use—to implement transportation models with higher-order automation within a limited geographical range. The arrangements often proposed for market introduction are slow-moving and limited-area vehicles intended to serve what is known as the “first or last mile,” complementary to private automobiles or public transportation. To name one concrete example, these types of solutions could be used to reach bus and urban rail networks in areas where a regular schedule is not feasible due to inadequate infrastructure or financial limitations.

Due to the generally rather favorable conditions, it is anticipated that various individual city governments and operators of amusement parks, shopping malls, and other large-scale facilities will introduce automated transportation systems in the short term.”

Gevonden in (p.199-200): https://www.dropbox.com/s/91n2z7i19wfgzu6/Beiker%2C%20S.%20%282016%29%20Deployment%20Scenarios%20for%20Vehicles%20with%20Higher-Order%20Automation.pdf?dl=0

“The Autonomous Valet Parking use case starts from the assumption that the vehicle will be able to independently move from parking space to user and vice versa, even on public roads. The use of Autonomous Valet Parking in carsharing would initially mean that the effort required for the user to procure the vehicle and park it after use would fall considerably. Instead, from the user’s point of view, there would be a door-to-door service—comparable to taking a taxi, although one in which the user takes over the driving task for the actual journey. The overall travelling time would in any case be reduced with the shortened time and distance for accessing and egressing the vehicle. “

Gevonden in (p.181): https://www.dropbox.com/s/i3wankjtjm4y1xc/Lenz%2C%20B.%20%26%20Fraedrich%2C%20E.%20%282016%29%20New%20Mobility%20Concepts%20and%20Autonomous%20Driving%20-%20The%20Potential%20for%20Change.pdf?dl=0

Afhankelijk per scenario:

Key players:

 

  • Evolutionary: auto industry (OEMs)
  • Revolutionary: non-automotive technology companies (google, apple, etc)
  • Transformative: high-tech start-ups

 

Zie tabel 10.3, Gevonden in (p. 206):

https://www.dropbox.com/s/91n2z7i19wfgzu6/Beiker%2C%20S.%20%282016%29%20Deployment%20Scenarios%20for%20Vehicles%20with%20Higher-Order%20Automation.pdf?dl=0

“Little or no research about the influence of truck platooning on drivers is conducted. However, it can be assumed that for higher levels of automation (e.g. SAE automation level 3 and 4), driver tasks may become less and their time in the truck may be made more productive. Therefore a situation can be sketched in which a platoon can travel longer distances in which resting time are postponed. Driving time regulations are denoted in the AETR treaty which is part of European legislation (European Union, 2006). The legislation prescribes a maximum driving time of 9 hours per day and an obligatory break of 45 minutes after 4.5 hours of driving. Theoretically, this means that a truck with a single driver can cover 720 kilometer when driving with a constant speed of 80 km/h. The implementation of truck platooning may result in longer driving distances as the productivity of the drivers in the following trucks increases. The time in the following truck or trucks may evolve slower and by overtaking at the right moment a platoon can cover longer distances.”

Gevonden in (p. 35): https://www.dropbox.com/s/wnl33x2zqwwe5jy/MScThesisBakermans2016.pdf?dl=0

 

“To work well, connected vehicle technology requires a large network of vehicles equipped with similar, or at least interoperable, communication systems. With high degrees of vehicle autonomy comes the need for higher degrees of cooperation and, hence, higher levels of adoption density to deliver the technology’s full value and potential. Density is critical for V2V safety applications and for automated driving. Some “monitored automation” applications have “cooperative” features, which require minimal levels of adoption density to deliver on their value proposition.

Convergence-based applications could also be implemented and adopted within densely populated urban areas. This approach might obviate the need for broader infrastructure investment and create inducements for other cities and individual consumers to adopt the technology. This

is especially feasible in high-density areas such as the borough of Manhattan, where drivers could reap the benefits of V2I communication without the need to retrofit all of NewYork City.”

 

Gevonden in (p. 20): https://www.dropbox.com/s/fwrk6zjze93x7ri/KPMG%2C%20Self-Driving%20Cars%20Next%20Revolution.pdf?dl=0

(same answer as previous question)

“Steeds meer informatie over de volledige rijomgeving van de auto wordt beschikbaar door de communicatie van de auto met de infrastructuur en met andere voertuigen op de weg (zogenaamde Vehicle to Vehicle- systemen (V2V) en Vehicle to Infrastructure-systemen (V2I)). Denk aan zaken zoals gladheid van het wegdek, drukte op de weg, rembewegingen en baanwisselingen van voorgangers. De auto wordt onderdeel van een netwerk van sensoren, en functioneert zelf ook als sensor in het netwerk die informatie verspreidt naar andere weggebruikers.”

Gevonden in (p.23): https://www.dropbox.com/s/2z11fhsx1wqe8fc/Op_advies_van_de_auto_2013.pdf?dl=0

 

“Steeds meer informatie over de volledige rijomgeving van de auto wordt beschikbaar door de communicatie van de auto met de infrastructuur en met andere voertuigen op de weg (zogenaamde Vehicle to Vehicle- systemen (V2V) en Vehicle to Infrastructure-systemen (V2I)). Denk aan zaken zoals gladheid van het wegdek, drukte op de weg, rembewegingen en baanwisselingen van voorgangers. De auto wordt onderdeel van een netwerk van sensoren, en functioneert zelf ook als sensor in het netwerk die informatie verspreidt naar andere weggebruikers.”

 

Gevonden in (p.23): https://www.dropbox.com/s/2z11fhsx1wqe8fc/Op_advies_van_de_auto_2013.pdf?dl=0

 

Voor MaaS systemen:

“Another deployment scenario for automated driving involves implementing transportation paradigms that provide slow-moving passenger vehicles, for example in urban areas. Consumers could summon such vehicles using a smartphone app and ride them over relatively short distances (see the use case “vehicle on demand”). Key drivers behind these types of schemes tend to be high-tech start-ups but may also include transportation service providers, municipalities and operators of facilities such as amusement parks. Their goal is to combine the advantages of personal mobility (independence and flexibility) with those of public transportation (efficient use of energy and space) in order to achieve the mission described at the beginning with a priority on reducing urban traffic congestion .”

Gevonden in (no. 105, p. 199):

https://www.dropbox.com/s/91n2z7i19wfgzu6/Beiker%2C%20S.%20%282016%29%20Deployment%20Scenarios%20for%20Vehicles%20with%20Higher-Order%20Automation.pdf?dl=0

 

 

  • Taxing fuel at a level that reflects these impacts could make fuel- efficient vehicles more economically attractively to buyers. Automated driving could conceivably increase fuel efficiency by reducing crashes, smoothing speeds and flows, and enabling drag-reducing platoons.
  • Reducing parking subsidies is the second way that governments— particularly local governments—can better align the individual and social costs of motor vehicle travel. More precisely, many cities subsidize private vehicle ownership by providing free on-street parking (especially in residential areas) and by requiring new buildings to include more parking spots than the market demands.148 Cheap and plentiful parking encourages both vehicle ownership and vehicle usage.149 Conversely, making parking more expensive and less convenient could encourage the use of driverless systems that forgo parking altogether or, perhaps, advanced driver assistance systems that automate the driving task in part (such as park assist) or in whole (such as automated valet).
  • raising insurance minimums may help to translate safety gains from automated driving into financial terms that are obvious to vehicle owners and drivers.

 

 

Gevonden in (p.35): https://www.dropbox.com/s/4xefqqbpiaid71t/Smith%2C%20B.W.%20%282016%29%20How%20Governments%20Can%20Promote%20Automated%20Driving.pdf?dl=0

 

Zie eerdere opmerking over het Fieldlab en Researchlab in de Metropoolregio Rotterdam Den Haag (website MRDH)

Another deployment scenario for automated driving involves implementing transportation paradigms that provide slow-moving passenger vehicles, for example in urban areas. Consumers could summon such vehicles using a smartphone app and ride them over relatively short distances (see the use case “vehicle on demand”).

In particular, companies from unrelated sectors can use image processing, object recognition, and route planning systems—which are already in widespread modular use—to implement transportation models with higher-order automation within a limited geographical range. The arrangements often proposed for market introduction are slow-moving and limited-area vehicles intended to serve what is known as the “first or last mile,” complementary to private automobiles or public transportation. To name one concrete example, these types of solutions could be used to reach bus and urban rail networks in areas where a regular schedule is not feasible due to inadequate infrastructure or financial limitations.

Due to the generally rather favorable conditions, it is anticipated that various individual city governments and operators of amusement parks, shopping malls, and other large-scale facilities will introduce automated transportation systems in the short term.”

Gevonden in (p.199-200): https://www.dropbox.com/s/91n2z7i19wfgzu6/Beiker%2C%20S.%20%282016%29%20Deployment%20Scenarios%20for%20Vehicles%20with%20Higher-Order%20Automation.pdf?dl=0

 

 

  • Use of existing and public infrastructure:
  • The concept of truck platooning combines automation with the usage of existing public infrastructure. This increases the compatibility of the concept. New infrastructure is often expensive and it may not be clear who is responsible for the infrastructure.
  • Realization of fuel savings:
  • Truck platooning has the potential to significantly save fuel. This also results in less emissions. Though, the order of fuel savings in practice is still uncertain. It was found that truck platooning is probably not feasible when only fuel savings are taken into account.
  • Larger truck driver productivity:
  • Drivers in following trucks may be in a standby mode at highways or even disappear for high levels of automation. It can be concluded that coordinated platoon formation is needed to benefit from larger trip distances that may be possible due to platooning. Labor cost savings may largely contribute to the adoption of platooning as many flows become feasible for platooning when labor costs drop.

 

 

Gevonden in (p. 49): https://www.dropbox.com/s/wnl33x2zqwwe5jy/MScThesisBakermans2016.pdf?dl=0

 

(voorsorteren letterlijk)

“Through lane specific control using automated vehicles an optimal distribution of the lanes can be attained.  “

Gevonden in (p. 5): https://www.dropbox.com/s/9y15clx7oav7gpa/White%20paper%20DAVI.pdf?dl=0

(voorsorteren meer figuurlijk)

De Metropoolregio Rotterdam-Den Haag (MRDH) is hiertoe gestart met een aantal Fieldlabs (Lastmile) en een researchlab ism TU Delft. Meer info zie MRDH website.

“We estimate that autonomous vehicles can save the US economy $1.3 trillion per year. We believe the large potential savings can help accelerate the adoption of autonomous vehicles.

We see five drivers of the cost savings: Fuel cost savings ($158 bn), accident costs ($488 bn), productivity gain ($507 bn), fuel loss from congestion ($11 bn), productivity savings from congestion ($138 bn).

This is our base case estimate. Our bull case estimate of savings is $2.2 tn/year and a bear case is $0.7 tn/year

This is a rough estimate. It does not account for the cost of implementing autonomous vehicles (one-time), offsetting losses, and investment implications. It also assumes 100% penetration of autonomous vehicles to achieve the full run-rate of potential savings.”

Gevonden in (p. 48): https://www.dropbox.com/s/mhckyj2bha4id0u/Morgan%20Stanley%20%282013%29%20AUTONOMOUS-CARS:-SELF-DRIVING-THE-NEW-AUTO-INDUSTRY-PARADIGM.pdf?dl=0

DEPLOYMENT-Samenwerking

Voor AMOD (automated on demand):nn“Despite the largely independent operating characteristics of an AMOD system, there are several special conditions that warrant consideration. Firstly, operating personnel are required to safeguard operation. While it is not necessary for staff to oversee every individual steering, braking or drive command, but they must ensure safety of general operation within the established operating area (with its geographical limits) and specified parameters (e.g. speed or position). To achieve this, operation centers are established similar to those used for driverless trains or for logistics systems. Those centers are staffed with comparatively small numbers of personnel who monitor a large number of vehicles. The operating center is connected via radio to the individual vehicles and is capable of monitoring vehicle operating data, halting the vehicle in an emergency and communicating with passengers.” nn nnGevonden in (p.281):nnhttps://www.dropbox.com/s/3cr7xmonxcp6np2/Beiker%2C%20S.%20%282016%29%20Implementation%20of%20an%20Automated%20Mobility-on-Demand%20System.pdf?dl=0

Key players:nn n

    n

  • Evolutionary: auto industry (OEMs)
  • n

n

    n

  • Revolutionary: non-automotive technology companies (google, apple, etc)
  • n

n

    n

  • Transformative: high-tech start-ups
  • n

n nnGevonden in (p. 206): nnhttps://www.dropbox.com/s/91n2z7i19wfgzu6/Beiker%2C%20S.%20%282016%29%20Deployment%20Scenarios%20for%20Vehicles%20with%20Higher-Order%20Automation.pdf?dl=0nNote Joop: In het onderzoek van Surf STAD is voor Nederland door Bart Stoffels een mooi overzicht van stakeholders opgenomen.nnhttps://www.dropbox.com/s/vvb3xj5m1d4ntkp/zelfrijdende%20stad_20%20maart_BS.pptx?dl=0

Innovatie bevorderende wetgeving ontwikkelenn

    n

  • Om (testen met) zelfrijdende auto’s op de openbare weg juridisch mogelijk te maken, wordt de bestaande AMvB (Besluit ontheffing verlening exceptionele transporten) voor ontheffingverlening door de RDW aangepast. Ik verwacht dit voorstel begin 2015 aan uw Kamer te sturen. Tot die tijd is testen op kleinschalig niveau mogelijk. De RDW verleent dan ontheffing en beoordeelt samen met de wegbeheerders de veiligheid. Hierbij kijken we uiteraard naar wat er in de rest van de wereld gebeurt op dit terrein, bijvoorbeeld naar de regelgeving die in Californië is ontwikkeld.
  • n

n

    n

  • Ik streef daarnaast naar (inter)nationale regelgeving die marktintroductie van zelfrijdende voertuigtechnologie mogelijk maakt. Daarvoor nemen we het initiatief in internationale overleggen (EU en VN) en steunen we relevante voorstellen. Ter voorbereiding op het EU-voorzitterschap van Nederland inventariseer ik welke regelgeving/kaders ten behoeve van zelfrijdende auto’s op Europees niveau zouden moeten worden aangepast of waar een gezamenlijk kader wenselijk is. Uiteraard werk ik hierbij samen met andere landen.
  • n

n

    n

  • Grootschalige testen in de praktijk faciliteren en kennisontwikkeling:
  • n

n

    n

  • Ik geef na de zomer uitsluitsel over de voorwaarden en de locatie waaronder eerder genoemde testaanvraag kan worden uitgevoerd. Hierbij betrek ik eventuele andere aanvragen.
  • n

n

    n

  • Deze test gebruiken we om in de praktijk een basisprocedure en voorwaardenset voor het structureel testen van automatische voertuigtechnologie te ontwikkelen. Doel is veilig testen en de kennis structureel borgen voor volgende initiatieven en projecten. Hierbij werk ik samen met kennisinstellingen, bedrijfsleven, de RDW en wegbeheerders
  • n

  • We gaan actief deelnemen aan internationale initiatieven. Zo nemen we deel aan het World Economic Forum waarbij met de auto-industrie en andere relevante partijen barrières en mogelijke oplossingsrichtingen voor de zelfrijdende auto in kaart worden gebracht. Te denken valt aan vraagstukken rondom data (eigendom, beheer, uitwisseling en beveiliging) en aansprakelijkheid. Op nationaal niveau zal ik ook onderzoeken laten uitvoeren naar deze onderwerpen, daarbij neem ik ook privacy en rijvaardigheidseisen mee.
  • n

nGevonden in: https://www.dropbox.com/s/ze5qzm20upsqlye/grootschalige-testen-van-zelfrijdende-auto-s-4.pdf?dl=0nn 

Vehicle-to-X connectivity (V2X): Connectivity is an important element of the automated vehicles especially secure V2X communication requiring low latency. V2X technologies encompass the use of wireless technologies to achieve real-time two-way communication among vehicles (V2V) and between vehicles and infrastructure (V2I). The convergence of sensor-based solutions (current advanced driver assistance – ADAS) and V2X connectivity will promote automated driving. “nn nn“Digital infrastructure: Digital infrastructure (for road automation) includes static and dynamic digital representations of the physical world with which the automated vehicle will interact to operate. Issues to address include: sourcing, processing, quality control and information transmission. “nnGevonden in: https://www.dropbox.com/s/4hor6dyblxeeinb/15CPB_AutonomousDriving.pdf?dl=0

Machtspositie (70%):nn“Rental, taxi and ride sharing businesses will converge with the robo-taxi model. The market size will grow substantially as more people move from car-owners to ride-sharers. The younger generation and older adults will be early adopters of the new model. “nnGevonden in: https://www.dropbox.com/s/wozuc6h3xnh5fi1/Jiang%2C%20T.%2C%20et%20al.%20%282015%29%20Self-Driving%20Cars%20-%20Disruptive%20or%20Incremental.pdf?dl=0nn 

Voor trucks (80%):nn“This research showed that many different stakeholders are involved in the implementation of platooning. Moreover, it can be concluded that coop- eration between different competing industries and companies is impor- tant. Cooperation should lead to multibrand platooning and the possibility to platoon cross-border. “nnGevonden in: https://www.dropbox.com/s/wnl33x2zqwwe5jy/MScThesisBakermans2016.pdf?dl=0 nnVoor auto’s (80%): nn“The trends in the automotive industry point towards an increased demand for strategic cooperation between partners as wellnnas technologies, as cooperation leads to an innovative combination of competencies and technologies, and can lead to the development of entirely new concepts developed in international strategic partnerships. Those companies which move on this now will gain important competitive advantage over their competitors”n

n

n

n

n

n

n

Vision for the Dutch automotive sector

Voor AMOD (automated on demand):

“Despite the largely independent operating characteristics of an AMOD system, there are several special conditions that warrant consideration. Firstly, operating personnel are required to safeguard operation. While it is not necessary for staff to oversee every individual steering, braking or drive command, but they must ensure safety of general operation within the established operating area (with its geographical limits) and specified parameters (e.g. speed or position). To achieve this, operation centers are established similar to those used for driverless trains or for logistics systems. Those centers are staffed with comparatively small numbers of personnel who monitor a large number of vehicles. The operating center is connected via radio to the individual vehicles and is capable of monitoring vehicle operating data, halting the vehicle in an emergency and communicating with passengers.”

 

Gevonden in (p.281):

https://www.dropbox.com/s/3cr7xmonxcp6np2/Beiker%2C%20S.%20%282016%29%20Implementation%20of%20an%20Automated%20Mobility-on-Demand%20System.pdf?dl=0

Key players:

 

  • Evolutionary: auto industry (OEMs)
  • Revolutionary: non-automotive technology companies (google, apple, etc)
  • Transformative: high-tech start-ups

 

Gevonden in (p. 206):

https://www.dropbox.com/s/91n2z7i19wfgzu6/Beiker%2C%20S.%20%282016%29%20Deployment%20Scenarios%20for%20Vehicles%20with%20Higher-Order%20Automation.pdf?dl=0
Note Joop: In het onderzoek van Surf STAD is voor Nederland door Bart Stoffels een mooi overzicht van stakeholders opgenomen.

https://www.dropbox.com/s/vvb3xj5m1d4ntkp/zelfrijdende%20stad_20%20maart_BS.pptx?dl=0

Innovatie bevorderende wetgeving ontwikkelen

  • Om (testen met) zelfrijdende auto’s op de openbare weg juridisch mogelijk te maken, wordt de bestaande AMvB (Besluit ontheffing verlening exceptionele transporten) voor ontheffingverlening door de RDW aangepast. Ik verwacht dit voorstel begin 2015 aan uw Kamer te sturen. Tot die tijd is testen op kleinschalig niveau mogelijk. De RDW verleent dan ontheffing en beoordeelt samen met de wegbeheerders de veiligheid. Hierbij kijken we uiteraard naar wat er in de rest van de wereld gebeurt op dit terrein, bijvoorbeeld naar de regelgeving die in Californië is ontwikkeld.
  • Ik streef daarnaast naar (inter)nationale regelgeving die marktintroductie van zelfrijdende voertuigtechnologie mogelijk maakt. Daarvoor nemen we het initiatief in internationale overleggen (EU en VN) en steunen we relevante voorstellen. Ter voorbereiding op het EU-voorzitterschap van Nederland inventariseer ik welke regelgeving/kaders ten behoeve van zelfrijdende auto’s op Europees niveau zouden moeten worden aangepast of waar een gezamenlijk kader wenselijk is. Uiteraard werk ik hierbij samen met andere landen.
  • Grootschalige testen in de praktijk faciliteren en kennisontwikkeling:
  • Ik geef na de zomer uitsluitsel over de voorwaarden en de locatie waaronder eerder genoemde testaanvraag kan worden uitgevoerd. Hierbij betrek ik eventuele andere aanvragen.
  • Deze test gebruiken we om in de praktijk een basisprocedure en voorwaardenset voor het structureel testen van automatische voertuigtechnologie te ontwikkelen. Doel is veilig testen en de kennis structureel borgen voor volgende initiatieven en projecten. Hierbij werk ik samen met kennisinstellingen, bedrijfsleven, de RDW en wegbeheerders
  • We gaan actief deelnemen aan internationale initiatieven. Zo nemen we deel aan het World Economic Forum waarbij met de auto-industrie en andere relevante partijen barrières en mogelijke oplossingsrichtingen voor de zelfrijdende auto in kaart worden gebracht. Te denken valt aan vraagstukken rondom data (eigendom, beheer, uitwisseling en beveiliging) en aansprakelijkheid. Op nationaal niveau zal ik ook onderzoeken laten uitvoeren naar deze onderwerpen, daarbij neem ik ook privacy en rijvaardigheidseisen mee.

Gevonden in: https://www.dropbox.com/s/ze5qzm20upsqlye/grootschalige-testen-van-zelfrijdende-auto-s-4.pdf?dl=0

 

Vehicle-to-X connectivity (V2X): Connectivity is an important element of the automated vehicles especially secure V2X communication requiring low latency. V2X technologies encompass the use of wireless technologies to achieve real-time two-way communication among vehicles (V2V) and between vehicles and infrastructure (V2I). The convergence of sensor-based solutions (current advanced driver assistance – ADAS) and V2X connectivity will promote automated driving. “

 

“Digital infrastructure: Digital infrastructure (for road automation) includes static and dynamic digital representations of the physical world with which the automated vehicle will interact to operate. Issues to address include: sourcing, processing, quality control and information transmission. “

Gevonden in: https://www.dropbox.com/s/4hor6dyblxeeinb/15CPB_AutonomousDriving.pdf?dl=0

Machtspositie (70%):

“Rental, taxi and ride sharing businesses will converge with the robo-taxi model. The market size will grow substantially as more people move from car-owners to ride-sharers. The younger generation and older adults will be early adopters of the new model. “

Gevonden in: https://www.dropbox.com/s/wozuc6h3xnh5fi1/Jiang%2C%20T.%2C%20et%20al.%20%282015%29%20Self-Driving%20Cars%20-%20Disruptive%20or%20Incremental.pdf?dl=0

 

Voor trucks (80%):

“This research showed that many different stakeholders are involved in the implementation of platooning. Moreover, it can be concluded that coop- eration between different competing industries and companies is impor- tant. Cooperation should lead to multibrand platooning and the possibility to platoon cross-border. “

Gevonden in: https://www.dropbox.com/s/wnl33x2zqwwe5jy/MScThesisBakermans2016.pdf?dl=0

Voor auto’s (80%):

“The trends in the automotive industry point towards an increased demand for strategic cooperation between partners as well

as technologies, as cooperation leads to an innovative combination of competencies and technologies, and can lead to the development of entirely new concepts developed in international strategic partnerships. Those companies which move on this now will gain important competitive advantage over their competitors”

Vision for the Dutch automotive sector

DEPLOYMENT-Toekomstverkenningen-en-Transitiepaden

80% Driverless future A policy roadmap for city leaders Page 3 report Prioritize and modernize public transit. The role of transit will evolve as AVs and shared mobility become widespread. Transit agencies should focus on high-frequency, high-capacity services in dense urban corridors (such as rail, bus rapid transit), provide first and last-mile connections through driverless shuttles, and expand kiss-and-rides/mobility hubs.

80% Driverless future A policy roadmap for city leaders Page 12 report AVs will reduce demand for parking, gas stations, and other auto-related land uses. Some uses, particularly those in highly desirable areas, may be reused and repurposed over time. AVs are highly likely to reduce parking demand by taking personally owned automobiles off the street. Past studies estimate that, depending on the success of merging AV into city infrastructure, parking demand may be reduced by up to 90%. Parking, roads and other auto-related uses occupy a significant amount of land. The U.S. contains as many as two billion parking spaces, occupying up to 16,000 square miles of land (the equivalent of Connecticut and Vermont combined). The quantity of parking spaces in the country amounts to as many as eight parking spaces for every car. Parking consumes a significant amount of land, especially in suburban areas where auto use is highest and surface lots are more common than multi-story garages. At a typical suburban mall, parking or driveways make up 80% of the land, while only 20% is used for the mall. Even in denser, more urban areas, parking requires significant land area. For example, streets and parking take up 45% of land in downtown Washington, D.C. and up to 65% in downtown Houston.

“Automated driving, with its minimal space requirements and rather equal speed levels, could at least double the existing average road infrastructure capacity. “

Gevonden in (p.380): Autonomous Vehicles and Autonomous Driving in Freight Transport

 

“It has been shown in the model that the diffusion of vehicle automation can be speeded up through a high economic growth, a supportive policy towards vehicle automation and a high technological development. In this so-called ‘AV in bloom’ scenario highly and fully automated vehicles (level 4 and level 5) will start being available on the market for early adopters around 2030. Until that time there will be mainly partially and conditionally automated vehicles on the market. Level 2 and 3 will have about 60% market penetration. The market penetration of highly and fully automated vehicles is around 12% in this time period. In 2045 – 2050 this has been changed however and fully automated vehicles dominate the market. Partially and conditionally automated vehicles will have a 20% market penetration together. Level 4 and 5 will have around 75% market penetration. “

 

Gevonden in (p.117): Diffusion of Automated Vehicles

 

Incremental:

“The automaker will incrementally add autonomous features in existing cars, which allows them to monetize these features and as well as test them in real conditions. The following features are considered as incre- mental changes that may lead us to the development of self-driving cars.”

Disruptive:

“Google is building prototypes of fully autonomous vehicles that reject carmakers’ plans to gradually enhance existing cars with self-driving features. The Google self-driving car does not even have a steering wheel. Google will ramp up the production version of their car by 202011. The long-term vision of the self-driving car involves moving from an ownership model to a service model, in which large numbers of people simply call cars whenever they want them. The new business model from Google favors the Robo-Taxi model, where car rides will be provided on demand. Google also wants to dominate the market for providing maps and software for the self-driving car. “

Gevonden in (p.4-5): Self-Driving Cars: Disruptive or Incremental?

 

“No legislature, agency, or developer will be able to anticipate every legal complication that might arise in the case of particular automated driving technologies or applications. For this reason, governments should consider how best to provide interpretations and clarifications of existing law and, as necessary, to grant appropriate exceptions to and exemptions from that law.

Governments should consider whether and how they might use a variety of legal mechanisms, including legislative acts, administrative regulations, executive orders, legal interpretations, and policy statements, to address any obstacles or uncertainties suggested by existing law. In some instances, formally amending a statute may be the only way to clearly and correctly accommodate a particular automated driving application. In other instances, however, less formal means may be as appropriate. For example, depending on the state, the legislature, the department of motor vehicles, the highway patrol, or the attorney general may all play a role in defining the “driver” of an automated vehicle for the purpose of a particular legal regime.

The enforcement discretion already employed by government agencies and agents is an informal means of providing flexibility—as well as a potential source of significant uncertainty. For example, two state vehicle inspectors may disagree on whether a particular vehicle is “safe” for the purposes of vehicle registration, and two local police chiefs may disagree whether a motorist should be stopped or cited under any of the traffic code provisions with potentially unclear application to automated driving.176 Governments can manage this discretion by clarifying enforcement priorities, practices, and parameters. Especially when linked with the public network of support described below,177 this policy guidance can highlight jurisdictions that are especially receptive in practical terms to automated driving.

Recognizing and even formalizing a robust statutory or regulatory exemption authority may also provide developers with prospective certainty without reducing the flexibility available to them. This could be particularly important for limited deployments of truly driverless vehicles in particular communities. These deployments may reveal unanticipated legal hurdles that could be addressed at least temporarily through waivers rather than wholescale reform.178 In turn, the legal and practical lessons from these deployments can inform whatever broader reforms eventually do occur.

Some federal agencies already have explicit if limited authority to create exceptions to generally applicable law. The U.S. Department of Transportation, for example, “may exempt, on a temporary basis, motor vehicles from a motor vehicle safety standard . . . on terms the Secretary considers appropriate.”179 Indeed, the Department’s January 2016 announcement on automated and connected vehicle technologies specifically “encouraged manufacturers to submit requests for use of the agency’s exemption authority.”180 European governments have also relied heavily on exemptions to facilitate the research-and-development testing of automated driving.181 Expanding this explicit authority can provide more flexibility.

This authority can also be implicit. “Unless a statute or regulation employs ‘extraordinarily rigid’ language, courts recognize an administrative law principle that allows agencies to create unwritten exceptions to a statute or rule for ‘de minimis’ matters.”182 Significant statutory deviations for substantial undertakings, however, may fall outside this principle. “The ability to create a de minimis exemption ‘is not an ability to depart from the statute, but rather a tool to be used in implementing the legislative design.’”183

Finally, public safety cases might be part of a more formal process for granting significant exceptions to statutory or regulatory regimes.184 In short, a government might require a developer seeking a specific legal exemption to “publicly make and defend arguments about how well its system should perform and how well its system actually performs.”185 Such a process could encourage the sharing of information, the informal development of fluid best practices, and the technical education of regulators as well as the broader public.”

Gevonden in (p.38-41): How Governments Can Promote Automated Driving

Note Joop Veenis: In Nederland hanteren we het beleid van IenM: “Learning by doing” in een samenwerking tussen overheden, bedrijfsleven en kennisinstellingen.

The automotive industry is a global industry in which value is generated predominantly by suppliers to automakers. The Dutch automotive industry is no exception to this rule. Within specific areas in the automotive industry, the Netherlands even plays a significant role with leading innovative companies that are involved in automotive activities worldwide. In these areas, the Dutch automotive sector is highly innovative and possesses a considerable knowledge base. To further strengthen its role, the Dutch automotive sector has developed a vision supported by a strong ambition of the Dutch automotive industry to increase its annual revenues from Eur 12 bn to Eur 20 bn.

The Dutch automotive sector has two responses to the opportunities and challenges of today’s automotive industry: innovation and cooperation. Innovation is vital in the continuous struggle for cost reductions alongside increasing levels of quality, individuality, and personalisation, and legal requirements (e.g., noise, safety and emission). Effective cooperation is becoming more and more crucial as competitive advantage will gravitate towards those that discern their strengths and move quickly to build or join appropriate new collaborative networks.”

 

Gevonden in (p.7): Vision for the Dutch automotive sector

“According to (Anderson, et al. 2014) Self-propelled vehicles could considerably upsurge access and movement across a variety of populations presently incapable or not permitted to use conventional automobile. These include the incapacitated, older people, and children of age 16 or less. The most promising advantages would be personal independence, increased sociability, and access to vital services. Level 4 automation is expected to provide mobility and access at reduced cost when compared to the current system which provides mobility services for disabled for 14 to 18 percent of their budgets in the U.S. “

Gevonden in (p.42): Impact of Autonomous Vehicles on Urban Mobility

“This type of combined and improved transport systems come with many advantages like they would reduce the necessity for roads and parking; lessen congestion, air pollution and greenhouse gas emissions; would support the optimization of capitals used for transportation; and upsurge the living standards in the region. “

Gevonden in (p.39): Impact of Autonomous Vehicles on Urban Mobility

“Considering that off-street parking represents 50 000 spots in the baseline case and that the most parking- intensive scenario (car sharing without public transport) would require 25 621 spots, on-street parking spots could be totally removed from the streets, whatever the scenario considered. This would allow the reallocation of 1 530 000 m2 to other public uses2, equivalent to almost 20% of the kerb-to-kerb street area in Lisbon or 210 football fields. This freed-up space could be dedicated to non-motorised transport modes, delivery bays, parklets or other recreational and commercial uses. “

Gevonden in (p.26): Urban Mobility Upgrade

“Autonomous driving could have a dramatic, albeit gradual, effect on each of the traffic concepts discussed in the previous section. Absent other phenomena, the total cost of motor vehicle travel is likely to decrease, and demand for that travel is likely to increase faster than corresponding capacity.”

Gevonden in (p.1409): Managing Autonomous Transportation Demand

 

There are multiple models/players:

The Branded Integrated Life-Style Model

It’s a sleekly designed experience, riding in this self-driving car. As elegantly designed as the sleekest smart phone.You use an app on your phone to summon your car when you need it or to program a daily pick-up. It’s as simple as setting the alarm on your phone.Your windshield doubles as a screen, synching seamlessly with your other connected devices. As you ride along, you swipe through applications and web sites, checking your progress and the local weather on a digital dashboard, uploading photos to your favorite web site or watching a video. When you arrive at your destination, the screens you’ve opened are synched and waiting for you on whatever device you pick up next.

In this model, perhaps a company with no traditional presence in the auto industry that is already an integral part of the consumer’s life outside the vehicle could become a key participant in the ecosystem. Since self-driving vehicles will no longer need the same level of rigorous testing and validation, and manufacturing could potentially be outsourced, their emphasis would be on consumer research, product development, and sale of integrated lifestyle experiences.

The Branded Lifestyle Value Proposition: Design, Technology, Software, Consumer experience

The Open System Model

It’s all about the data and how to use these data to customize the consumer value proposition.The market for big data

is growing exponentially. Market intelligence provider IDC predicts that by 2015 the “Big Data” market will be $16.9 billion, up from $3.2 billion in 2010.35 A major player in the data market might not want to manufacture vehicles, but could

well design a vehicle operating system. With more than a billion cars serving up trillions of data points about consumer behavior, traffic patterns, and topography, an operating system (OS) developer could afford to give away the OS but accrue significant value from the data they could aggregate. Who would manufacture the vehicle? The OS provider could partner with any of the world’s vehicle manufacturers—and not just the traditional automotive manufacturers. Partnerships could be established with one or more new players who might compete in the branded technology arena.

The Open System Value Proposition: Utility, Technology, Customization

Mobility On Demand Model

Zipcar was the pioneer in the shared-vehicle field, but other players are breaking into the market. Whereas current mobility on demand providers must make vehicles easily accessible for customers in urban areas, their vehicle maintenance and parking fees are high. With self-driving vehicles, proximity to end-users would no longer be necessary. Vehicles could be dispatched by taxi and car service companies.

Giant retailers with a core competence in managing complex distribution channels or fleet providers with the capability

to manage the complexity of renting and allocation of fleets could enter the fray and accrue significant value in the new ecosystem. New entrants in the market might compete at either end of the spectrum—with generic, low-cost utilitarian transportation on demand at one end (the low-cost airline model) and super-luxury mobile executive suites and sleeping pods at the other (the first class or private jet experience). Success will be determined by efficiency, reliability, flexibility, vehicle maintenance, customer service, ease of human-vehicle interface, and integration with existing consumer devices—and all the other psychographic factors that determine consumer behaviors and brand preferences.

The Mobility on Demand Value Proposition: Flexibility, Reliability, Convenience, Cost

The OEM Model

Traditional automotive manufacturers have decades of experience in designing and manufacturing vehicles, and shaping an emotional connection with consumers. But will they move fast enough to maintain their brand dominance? Smart automotive manufacturers should be planning now, thinking about how to restructure their organizations and what potential strategic investments they should be making. History has not been kind to those who get stuck protecting the status quo in the face of disruptive change. In fact, collaboration is already taking place across the ecosystem as companies strive to stay relevant.The joint project between Intel and DENSO36 to develop in-vehicle communication and information systems exemplifies the new cross-industry synergistic relationships.

Vertical integration is an option for companies looking to bring a critical skill or technology in house. Some vehicle manufacturers have established venture capital subsidiaries to invest in promising new technologies as a means of bridging any skill or technology gaps. Doing so may provide a competitive advantage in this rapidly evolving ecosystem.

The OEM Value Proposition: Design, Technology, HMI, Supply Chain Management “

Gevonden in (p.32-33): Self-Driving Cars, The Next Revolution

Logistiek (trucks):

During the European truck platooning conference in April 2016 a vision for the implementation of truck platooning was presented (Eckhardt, 2016). This vision shows a potential development path of truck platooning. The vision shows similarities with the expectations of the deployment path of ERTRAC (2015). It also displays a development of both automation and cooperation in time. “

Zie tabel 2.2. met meer informatie. Gevonden in (p.8): Truck Platooning – Enablers, Barriers, Potential and Impact

OV:

Uit Citymobil2 project:

Tabel met pathway to urban public transport.

Gevonden in (p.21):Automated and Autonomous Driving: Regulation under uncertainty

 

Technologieontwikkeling:

Efforts toward full automation tend to follow one of two incremental paths. The first involves gradually improving the automated driving systems available in conventional vehicles so that human drivers can shift more of the dynamic driving task to these systems. The second involves deploying vehicles without a human driver and gradually expanding this operation to more contexts. These two approaches can be simplistically described as “something everywhere” and “everything somewhere.”

Gevonden in (p. 13): Automated and Autonomous Driving: Regulation under uncertainty

“De private partijen die verantwoordelijk zijn voor de ontwikkeling van zelfstandige robotvoertuigen in de Verenigde Staten, zien coöperatieve systemen als technologie die later toegevoegd kan worden. Maar zowel in Amerika als in Europa leeft het besef dat de coöperatieve en zelfstandige systemen elkaar zullen moeten aanvullen om tot een levensvatbare zelfsturende auto te komen. Vanuit beide ontwikkelingsrichtingen erkennen experts het belang van het samenbrengen van de twee benaderingen om voordelen te kunnen behalen. Deze convergentie is noodzakelijk om de auto’s voldoende betrouwbaar en kostenefficiënt zelfrijdend te maken4 (zie figuur 6). In de Verenigde Staten heeft de federale overheid daarom nu regelgeving voor voertuigcommunicatie op de agenda gezet. De onderste rode pijl in figuur 6 illustreert het Amerikaanse pad, dat sterk op de ontwikkeling van zelfstandige robotauto’s is gericht. De bovenste rode pijl geeft het Europese pad aan, dat via coöperatieve systemen een solide basis wil leggen voor de ontwikkeling van volledig zelfrijdende auto’s.”

Gevonden (p.22-23): Tem de robotauto – De zelfsturende auto voor publieke doelen

Testen:

“Autonomous driving is distinguished in particular by the omission of the human super- visor of assisted or partially-automated systems, and the supervisor’s ability to correct these systems. The metric consisting of real driving and driver’s license test that enables a conclusion about the safety of automation levels currently present in series production, is no longer valid for autonomous driving. The resulting loss of the reduction in the test cases means that current test concepts are not suitable for economically assessing the safety of a new system such as autonomous driving. Adhering to current test concepts would involve an economically unjustifiable overhead, and would result in an “approval-trap” for autonomous driving. However, the authors see three approaches for avoiding this “approval-trap”.

Firstly, the evolutionary approach, or alternatively the transformation (see Chap. 10), seems necessary, as only the step-by-step introduction along the different dimensions of speed, scenery and degree of automation enables existing components to be taken over and reduces the range of tasks for the following releases. Secondly, the necessary test cases must be reduced based on field experience and statistical procedures. The challenge here is the metric that allows a conclusion to be drawn about the safety of the system based on the completed test cases. Thirdly, alternative testing tools must be used alongside real driving. Here it is not expected to be able to do without real driving completely, because a verification of validity is required to move test cases to ViL, SiL and procedures that formally prove safety.

Finally, it must be stated that the challenges presented should not only be solved internally by the automobile industry. Even if test concepts are optimized for autonomous driving, there will not be 100 % safety. “

Gevonden in (p.446-447):The Release of Autonomous Vehicles

That depends:

While carsharing attracts particular attention, especially in its new flexible variant, and also in connection with vehicle automation, it is often overlooked that new options for (further) diversification in current public transport provision could also result, with further new forms of mobility concepts emerging. It also is vital here to take the relevant local conditions into account.

The basic options to be discussed in connection with public transport involve:

  • –  redesigning intermodality and transition to a more flexible form of public transportation
  • –  individualizing public transportation
  • –  expanding public transportation service options
  • The particular benefit that would arise from the use of autonomous vehicles here especially concern demand-driven services: Fixed route plans could be supplemented by flexible services. The additional routes could be optimized according to customer requirements. Fixed timetables would be replaced by temporally optimized routings corresponding to customer demands.
  • This individualization of public transport will, then, amount to “hybridization” at the latest when, beyond the flexibilization of times and routes, options regarding the vehicles available are also on offer. In essence, the idea of diversifying public transport via vehicle-specific provision is not new. Until now, however, it has only been possible to introduce this in very limited, mostly tourist-centered niches, due to the costs of manning the various fleets with the required staff (e.g. Cable Car in San Francisco, the Glacier Express in Switzerland, or the Blue Train in South Africa). “

Gevonden in (p. 185): New Mobility Concepts and Autonomous Driving: The Potential for Change

Bereikbaarheid:

“According to (Anderson, et al. 2014) Self-propelled vehicles could considerably upsurge access and movement across a variety of populations presently incapable or not permitted to use conventional automobile. These include the incapacitated, older people, and children of age 16 or less. The most promising advantages would be personal independence, increased sociability, and access to vital services. Level 4 automation is expected to provide mobility and access at reduced cost when compared to the current system which provides mobility services for disabled for 14 to 18 percent of their budgets in the U.S. “

Gevonden in (p.42): Impact of Autonomous Vehicles on Urban Mobility

Stress, productivity, road capacity, energy, emissions:

“Potentially, autonomous vehicles could significantly reduce stress levels and offer us the capability to rest – or work – while traveling. Driverless cars could also provide independent mobility for non-drivers, increase road capacity and reduce traffic congestion. They could additionally reduce parking costs, accidents, offer energy conservation, emissions reductions as well as more scope for vehicle sharing. “

Gevonden in (p.037): Ready or Waiting

Het Kennisinstituut Mobiliteit heeft recent een tweede studie hiernaar afgerond. Zie bibliotheek.

“Governments can anticipate—and possibly even accelerate—this watershed by taking some or all of the actions described in this Article. These strategies, which were identified through extensive discussions with developers and regulators of automated driving systems as well as other emerging technologies, are roughly organized into three overlapping categories:

  • Administrative strategies include preparing government agencies, preparing public infrastructure, leveraging procurement, and advocating for safety mandates.
  • Legal strategies entail carefully analyzing and, as necessary, clarifying existing law as it applies to automated driving; many of these strategies would also internalize more of the costs of conventional driving in a way that could properly incentivize automated driving.
  • Community strategies involve identifying specific local needs, opportunities, and resources that may be relevant to automated driving; communities can already start developing proposals in anticipation of public and private grants that may soon be announced. “

Gevonden in (p.3):How Governments Can Promote Automated Driving

 

“Auto’s voor dagelijks woon-werkverkeer kunnen een stuk kleiner zijn, omdat 80% van de autoritten slechts één passagier bevat. Rijbanen die gereserveerd zijn voor zelfrijdende voertuigen kunnen dynamisch wisselen van rijrichting om op verschillende tijden ruimte te geven aan de drukste rijrichting. “

Gevonden in (p.54): Verkenning technologische innovaties in de leefomgeving

 

“To ensure acceptable quality of service, one needs to increase the fleet size. To characterize such increase, we use the same techniques outlined in Sect. 19.3.1, which rely on the lumped approach. Vehicle availability is analyzed in two representative cases. The first is chosen as the 2–3 pm bin, since it is the one that is the closest to the “average” traffic condition. The second case considers the 7–8 am rush-hour peak. Results are summarized in Fig. 19.5 (left). With about 200,000 vehicles availability is about 90 % on average, but drops to about 50 % at peak times. With 300,000 vehicles in the fleet, availability is about 95 % on average and about 72 % at peak times. As in Sect. 19.3.1, waiting times are characterized through simulation. For 250,000 vehicles, the maximum wait times during peak hours is around 30 min, which is comparable with typical congestion delays during rush hour. With 300,000 vehicles, peak wait times are reduced to less than 15 min, see Fig. 19.5 (right). “

Gevonden in (p. 397): Autonomous Mobility-on-Demand Systems for Future Urban Mobility

 

Integratie met OV:

While carsharing attracts particular attention, especially in its new flexible variant, and also in connection with vehicle automation, it is often overlooked that new options for (further) diversification in current public transport provision could also result, with further new forms of mobility concepts emerging. It also is vital here to take the relevant local conditions into account. The basic options to be discussed in connection with public transport involve:

  • –  redesigning intermodality and transition to a more flexible form of public transportation
  • –  individualizing public transportation
  • –  expanding public transportation service options “

 

Gevonden in (p.185): New Mobility Concepts and Autonomous Driving: The Potential for Change

Automatisering OV:

A second development, far more prominently discussed in the scenarios in question, is the emergence of a new model of urban mobility, in the form of autonomous taxi fleets. This touches on aspects of the “Vehicle on Demand” use case as described in Chap. 2. In such a system, low-cost autonomous taxis do not operate on fixed routes following rigid timetables, but rather in a demand-oriented and flexible way. They are in permanent operation and run in a city-wide, dense network of stations. This mode of operation is similar to hailed shared taxis. The city is divided into cells. A “central transit point,” or a series of them, for pick up and drop off belongs to each of these cells. It should be possible to integrate and combine taxis with rail-bound public transport. The taxis will take over feeder and dispersion functions to and from rail-based public transport stations and pick up passengers there, while the more efficient and potentially faster public transport takes over for longer route sections. The use of an automated taxi network has already been described and modeled as a concept [32–34]. It could lead to a fundamental transformation of public transportation and solve the problem that high-speed rail has covering the last mile [23]. It involves abolishing standard bus and tram stops. It is important that the system is an integrated one. It is an open question whether taxis will be operated by the public or private sector. “

Gevonden in (p. 224-225): Autonomous Driving and Urban Land Use

 

IMPACT-Digitale Infrastructuur

50%

ROAD SAFETY WITH SELF-DRIVING VEHICLES: GENERAL LIMITATIONS AND ROAD SHARING WITH CONVENTIONAL VEHICLES

Chapter 3.2.1

Gomes(2014) argued that, “all 4 million miles of U.S. public roads will need to be mapped, plus driveways, off-road trails, and everywhere else you’d ever want to take the car” and this information would need to include “locations of street lights, stop signs, crosswalks, lane markings, and every other crucial aspect of a roadway.”

50% 

Zoeken naar strepen op het asfalt

Page 4 of document : Jene van der Heide, Senior adviseur Strategie en Beleid bij het Kadaster: ‘Voor kaartenmakers is het te duur om ook de afgelegen wegen in het buitengebied in kaart te brengen. En de overheid verzamelt uitsluitend informatie die nodig is voor het onderhoud van zulke wegen. Rijd je zo’n gebied binnen, dan vraagt een zelfrijdende auto waarschijnlijk aan zijn bestuurder om het even van hem over te nemen. Het kan zomaar 10 jaar duren voordat dit verschil tussen buitengebied en snelweg is weggewerkt.’

70%

Zoeken naar strepen op het asfalt

Page 5 report: Welke rol is weggelegd voor de overheid?

‘Past de definitie die de overheid hanteert voor een wegvak op de definitie die de automobielindustrie heeft van een wegvak? Dat loopt waarschijnlijk scheef. Want geautomatiseerde auto’s onderscheiden wegvakken in verband met verschillen in rijgedrag, en de overheid onderscheidt wegvakken in verband met de planning van beheer- en onderhoudswerkzaamheden.

Het Kadaster kan kaartenmakers helpen bij het opbouwen van een statisch wereldbeeld. Maar kaartenmakers hebben behoefte aan meer detail. Die extra nauwkeurigheid is niet alleen handig voor geautomatiseerd rijden, maar ook voor het beheer van de openbare ruimte. De afweging waar de overheid voor staat, is of ze zelf gaat investeren in de extra nauwkeurigheid, of dat ze het overlaat aan de markt.’ ‘Zeker als het gaat om statische informatie die ‘in advance’ beschikbaar is voor zelfrijdende auto’s, kan de overheid als leverancier een grote rol spelen. Andersom kan het voor wegbeheerders handig zijn om van autofabrikanten informatie af te nemen die met sensoren en camera’s ‘on the fly’ is verzameld, bijvoorbeeld over kuilen in de weg.

‘Ik zie een verschuiving in de rol van de overheid, van producent van kaartinformatie naar platform voor kaartdiensten, ook de betaalde diensten van kaartenmakers. De vraag is welke investeringen we moeten doen om die rol goed in te vullen? En we moeten nu alvast nadenken over de consequenties van de nieuwe verhoudingen. Gaat de overheid betalen voor de kaarten die ze voor haar eigen doelen nodig heeft?’ Stephen

T’Siobbel, Sr. Project Manager Advanced Driving bij TomTom Maps: ‘Ik denk niet dat TomTom ooit  kadasterkaarten gaat maken. Ik ga er van uit dat de overheid voldoende eigen use cases heeft om zelf topografische en kadastrale kaarten te beheren en te onderhouden. Net zomin als overheden kaarten zullen samenstellen die direct geschikt zijn voor private kaartenmakers, zullen kaartenmakers producten leverden die direct geschikt zijn voor overheden. Daarvoor zijn de verschillen te groot. Wel zullen onze kaarten voor Automated Driving over specifieke attributen beschikken die ook voor overheden relevant kunnen zijn, bijvoorbeeld informatie over het type van vangrails, of de exacte breedte van een rijstrook.’

70%

State of Art on Infrastructure for Automated Vehicles

Chapter 6

This  section  summarizes,  based  on  insights  from  the current scientific literature, projects, test sites, and  initiatives,  the  implications  of  vehicle  automation  on  the  infrastructure  for  each  SAE  level  of automation (in each case assuming 100% penetration level). According to Shladover (31) level 5 will not be here until 2075, while level 3 is problematic because of the difficulty to attain drivers’ attention after  being  out  of  the  loop  and  because  some  automakers  simply  will  not  attempt  level  3.  However, level 4 automation will probably be realized within the coming decade. In Table 6 a first attempt was made to summarize the requirements from the physical infrastructure to facilitate vehicle automation, followed by Table 7 which summarizes the requirements from the digital infrastructure. These results should  be  considered  with  caution,  as  many  of  the findings  from  the  scientific  literature  were  not explicitly based on empirical data and results, but on experts’ opinions.

 

IMPACT-Infrastructuur

80% Driverless future A policy roadmap for city leaders Page 3 report Prioritize and modernize public transit. The role of transit will evolve as AVs and shared mobility become widespread. Transit agencies should focus on high-frequency, high-capacity services in dense urban corridors (such as rail, bus rapid transit), provide first and last-mile connections through driverless shuttles, and expand kiss-and-rides/mobility hubs.

70% Driverless future A policy roadmap for city leaders Page 3 report Encourage adaptable parking.Fewer cars means fewer parking spaces, especially in city centers. Parking garages need to be built with housing or office conversion in mind and include level floors, higher ceiling heights and centralized ramps. These future-proof garages are already being contemplated in Boston and Nashville.

80% Driverless future A policy roadmap for city leaders Page 12 report AVs will reduce demand for parking, gas stations, and other auto-related land uses. Some uses, particularly those in highly desirable areas, may be reused and repurposed over time. AVs are highly likely to reduce parking demand by taking personally owned automobiles off the street. Past studies estimate that, depending on the success of merging AV into city infrastructure, parking demand may be reduced by up to 90%. Parking, roads and other auto-related uses occupy a significant amount of land. The U.S. contains as many as two billion parking spaces, occupying up to 16,000 square miles of land (the equivalent of Connecticut and Vermont combined). The quantity of parking spaces in the country amounts to as many as eight parking spaces for every car. Parking consumes a significant amount of land, especially in suburban areas where auto use is highest and surface lots are more common than multi-story garages. At a typical suburban mall, parking or driveways make up 80% of the land, while only 20% is used for the mall. Even in denser, more urban areas, parking requires significant land area. For example, streets and parking take up 45% of land in downtown Washington, D.C. and up to 65% in downtown Houston.

“Automated driving, with its minimal space requirements and rather equal speed levels, could at least double the existing average road infrastructure capacity. “

Gevonden in (p.380): Autonomous Vehicles and Autonomous Driving in Freight Transport

 

90%

Rapport Zelfrijdende auto’s, verkenning van implicaties op het ontwerp van wegen

Chapter 3.3
– Als  begrenzing  van  rijstroken  is fysieke  markering belangrijk, naast de eventueel al toe te passen   digitale  markering.   Dat   geldt  voor   alle   wegonderdelen.   De   markering  moet   goed waarneembaar  zijn,  door  in-car  sensoren  (camera’s)  en door  de  menselijke  bestuurder,  bij verschillende weers- en lichtcondities.

-Naarmate  de  automatiseringsgraad  toeneemt,  zijn  er steeds  meer  voertuigen  die  op smallere rijstroken kunnen rijden. Echter bestuurders van voertuigen die nog niet geautomatiseerd koers houden, zijn gebaat bij de huidige rijstrookbreedte (vrees marge en vetergang). Rijstroken kunnen dus   nog   niet   overal   smaller   gemaakt   worden.   Als   tussenoplossing   kunnen smallere doelgroepstroken voor de hogere SAE level voertuigen worden geïntroduceerd.

-Aanpassingen van het dwarsprofiel en de berminrichting (redresseerstrook, obstakelvrije zone, vluchtstroken) kunnen nog niet plaats vinden.

-Boogstralen kunnen ook nog niet aangepast worden. Wel zou overwogen kunnen worden om in bogen  met meer  stroken  de manueel  bestuurde voertuig en  alleen  in  de  buitenste  strook/stroken toe  te  staan  en  de  binnenste  strook/stroken  te  reserveren voor  automatische voertuigen  die  hun snelheid   kunnen   optimaliseren   op   de   infrastructuurkenmerken   en   de   voorkeuren   van   de inzittenden.  Een  risico  is  dat  manueel  bestuurde  voertuigen  het  gedrag  van  automatische voertuigen gaan imiteren, wat ertoe zou kunnen leiden dat ze met een te hoge snelheid de bocht in gaan. Ook de korte volgtijden van automatische voertuigen zouden overigens door menselijke bestuurders geïmiteerd kunnen worden. Dat geldt ook op andere wegonderdelen.

-Over  het  algemeen  geldt  dat  de  mix  van  verschillende voertuigtypen  een  aanvankelijk  wat onvoorspelbaar  verkeersbeeld  kan  geven.  Dat  heeft  met name invloed op de dimensionering van  uitwisselpunten. (in- en uitvoeger, weefvak, kruispunt, rotonde). De mix van voertuigen van verschillende  SAE  levels  kan  zorgen  voor  interactie  tussen  de  verschillende  voertuigtypen  die tegen  de  intuïtie  van  menselijke  bestuurders  ingaat. ZRA’s  gedragen  zich  anders  dan  de bestuurders van niet-ZRA’s, of bestuurders van voertuigen met een lager SAE level, op basis van hun intuïtie verwachten. De uitwisseling op sommige plaatsen is mogelijk te complex voor ZRA’s, die   nog   niet   met   elkaar   communiceren   en   meer   tijd   nodig   hebben,   door   de   grotere veiligheidsmarges  dan  die  die menselijke  bestuurders aanhouden  en vroegtijdig  remmen.  Dit  zal ertoe   kunnen  leiden   dat   uitwisselpunten   (in-   en   uitvoegstroken,   weefvakken)   eerst   ruimer gedimensioneerd  moeten  worden.  Dat  sluit  aan  bij  de praktijkobservatie  dat  ACC in  zijn huidige vorm leidt tot grotere volgafstanden.

-Voor onderliggende wegen geldt dat met name de interactie  met  langzaam  verkeer  (fietsers  en voetgangers) veel dilemma’s oplevert. Daardoor wordt de situatie veel complexer en daarvoor zijn op  dit  moment  nog  geen  (veilige)  oplossingen  beschikbaar.  Op  gebiedsontsluitingswegen  met gescheiden verkeersstromen gelden dit ook (op kruispunten en rotondes).

-Bij gemengd verkeer dient nog vastgehouden te worden aan het originele kruispuntontwerp en voorrangsregels.  De  ZRA  moet  zich  zoveel  aan  de  menselijke  bestuurders  aanpassen,  zodat verwarring voorkomen wordt bij bestuurders van niet-automatische voertuigen. Mogelijk heeft het automatische voertuig meer tijd  nodig  om  de  situatie op  een  kruispunt  in te  schatten,  als  er  niet met alle voertuigen in de buurt gecommuniceerd kan worden.

-Doorzicht op een rotonde is voor een ZRA, die communiceert met het overige verkeer, geen probleem, voor menselijke bestuurders wel.

– (truck) platooning brengt nog de nodige vragen met zich mee, als het streven is om vrijwel continu te  kunnen  platoonen  (dus  niet  moeten  opsplitsen  bij ieder  knooppunt)  om  de  voordelen  vanplatooning te kunnen behalen

Uit  het  bovenstaande  ontstaat  het  beeld  dat  de  mogelijke  consequenties  voor  het  wegontwerp  in  de situatie  met  gemengd  verkeer  waarschijnlijk  nogal  beperkt  zullen  zijn  (ofwel  dat  je  niet  veel  kunt veranderen  aan  het  wegontwerp  zolang  er  gemengd  verkeer  is).  Bij  gemengd  verkeer  kan  er  in  eerste instantie niets veranderd worden aan het ontwerp, dat gebaseerd is op wat menselijke bestuurders nodig hebben  om  veilig,  vlot  en  comfortabel  te  rijden.  Alleen  op  wegen  met  veel  capaciteit/rijstroken  kan overwogen  worden  een  deel  hiervan  voor  ZRA’s  te  reserveren en dit deel ook een nieuw wegontwerp te geven (scheiding in het dwarsprofiel van ZRA en niet-ZRA).

Smart Infra, Eerste schetsonderzoek naar level 4 snelwegen en kruispunten voor zelfrijdende auto’s

Chapter 5

Voor de transitiefase geldt dat zowel de zelfrijdende voertuigen als de conventionele voertuigen gebruik maken van dezelfde rijbaan. Zolang de conventionele voertuigen gebruik maken van de rijbaan zullen deze, ten behoeve van de verkeersveiligheid, maatgevend z

ijn voor de ontwerpcriteria aan de rijbaan. In de transitiefase is het daarom naar verwachting niet wenselijk versoberingen aan het ontwerp van autosnelwegen door te voeren.

Bij een gescheiden transitie zal er een doelgroepenstrook aan de linkerzijde van de rijbaan worden aangewezen voor de zelfrijdende voertuigen. In het geval dat de doelgroepenstrook als extra strook wordt toegepast, zullen de overige stroken versmald moeten worden en wellicht dat de vluchtstrook moet worden opgeofferd. Beide maatregelen leiden tot een

afwijking van de vigerende richtlijn (ROA 2014) en hebben mogelijk een negatief effect op de

verkeersveiligheid van met name de conventionele voertuigen. Met de extra strook wordt de totale capaciteit van de weg wel vergroot.

 

80%

Automated Vehicles. The Coming of the Next Disruptive Technology

Benefits page 17 report

With AVs, the demand for parking will decrease substantially because an AV can relocate itself to an area of free parking. Or, as an automated taxi, it can pick up its next ride. In some cases, a commuter can send the car home for his/her spouse to use.

 

Besides changes in parking spots Urban land use is expected to change as well with the implementation of AV’s. This Autonomous Driving and Urban Land Use report discusses the possible effects.

70% State of Art on Infrastructure for Automated Vehicles

 (See figure in Chapter 6))

This  section  summarizes,  based  on  insights  from  the current scientific literature, projects, test sites, and  initiatives,  the  implications  of  vehicle  automation  on  the  infrastructure  for  each  SAE  level  of automation (in each case assuming 100% penetration level). According to Shladover (31) level 5 will not be here until 2075, while level 3 is problematic because of the difficulty to attain drivers’ attention after  being  out  of  the  loop  and  because  some  automakers  simply  will  not  attempt  level  3.  However, level 4 automation will probably be realized within the coming decade. In Table 6 a first attempt was made to summarize the requirements from the physical infrastructure to facilitate vehicle automation, followed by Table 7 which summarizes the requirements from the digital infrastructure. These results should  be  considered  with  caution,  as  many  of  the  findings  from  the  scientific  literature  were  not explicitly based on empirical data and results, but on experts’ opinions.

IMPACT-Veiligheid

60%

ROAD SAFETY WITH SELF-DRIVING VEHICLES: GENERAL LIMITATIONS AND ROAD SHARING WITH CONVENTIONAL VEHICLES

Chapter 3/ Conclusion

Self-driving vehicles could compensate for some but not all crashes caused by other traffic participants (Pedestrian error could be compensated by AV). Lighting failures might turn out to be irrelevant to safety from the perspective of being able to control one’s vehicle at night, because self-driving vehicles might not rely on visual input. / (1) The expectation of zero fatalities with self-driving vehicles is not realistic. (2) It is not a foregone conclusion that a self-driving vehicle would ever perform more safely than an experienced, middle-aged driver. (3)During the transition period when conventional and self-driving vehicles would share the road, safety might actually worsen, at least for the conventional vehicles.

Safety Benefits of Automated Vehicles: Extended Findings from Accident Research for Development, Validation and Testing

17.4  Significance of Possible Predictions based on Accident Data

 

Automated Vehicles, Are we ready ?

Chapter 3.1

A common element in all levels of automation is safety-critical electronic control systems. There are voluntary industry standards, such as ISO 26262, which establish uniform practices for specific levels of safety integrity in complex embedded systems. In the United States, NHTSA has the regulatory responsibility for performance standards for vehicle systems or sub-systems that address a specific type of safety risk. For AVs, NHTSA is focusing on developing functional safety requirements as well as potential liability requirements in the areas of diagnostics, prognostics and failure response (fail safe) mechanisms (NHTSA, 2014).

 

70%

Safety Benefits of Automated Vehicles: Extended Findings from Accident Research for Development, Validation and Testing
17.1 introduction

→ report goes into more detail
For testing methods in order to develop and validate safe automated vehicles with reasonable expenditure, the author recommends combining area-wide traffic, accident, weather, and vehicle operation data as well as traffic simulations. Based on these findings, a realistic evaluation of internationally and statistically relevant real world traffic scenarios as well as error processes and stochastic models can be analyzed (in combination with virtual tests in laboratories and driving simulators)to control critical driving situations in the future.

Self-Driving Regulation, Pro-Market Policies Key to Automated Vehicle Innovation
50%
One important challenge, which is expected to be met by late 2014 or early 2015 , is providing sufficient evidence that road – tested autonomous vehicles are in fact safer than manually driven vehicles. As Bryant Walker Smith of Stanford Law School has noted, a high degree of statistical confidence must be reached in order for automakers and component developers to begin scaling up technology deployment beyond testing.

Google’s self- driving cars have logged over 500,000 miles on U.S. public roads to date. To demonstrate their safety over manually driven vehicles with 99 percent confidence, Google will need to log approximately an additional 200,000 miles of crash-free automated driving (see Table 2).

60% 

Zoeken naar strepen op het asfalt

Introduction page 4 of document

Van de 33.000 verkeersslachtoffers die de VS jaarlijks betreurt, zijn er volgens deskundigen 22.000 te voorkomen als we de mens achter het stuur vandaan halen.

Tomorrow’s Road Infrastructure for Automated Driving

Slide 11

Point made by an online respondent of a survey:

“I am extremely concerned that proponents have little regard to or understanding of the level of reliability required to class any of these systems as safe . For example in regard to Google cars : ‘Ultimately, Google aims to provide a solution for the millions of car accidents that occur worldwide – 93 percent due to human error .’Statement is misleading/ wrong . Human factors contribute to 93 percent of crashes but many other factors also contribute. And the most responsible drivers cause a crash where someone is injured around once in 2,000,000 Miles. And public would expect autonomous cars to have a much lower rate-say once in 20,000,000miles.That requires a system that will not fail/malfunction more than once in ~ 80 vehicle lives or once in 1250 years of average driving.”

The Release of Autonomous Vehicles

Chapter 21.1

60%

The Release of Autonomous Vehicles

21.3  Requirements for a Test Concept

In order to discuss in the following section why full automation poses a particular challenge for safety validation, we will first describe the requirements for test concepts to assess safety. These are divided into effectiveness and efficiency criteria.

21.5.1 Validity of the current test concept for autonomous driving

At present, real driving is the most important method for the approval; the reason for this, in particular, is the validity combined with the justifiable economic overhead. However, along with the economic overhead, autonomous driving also presents a systematic challenge for the known methods. At present, real driving stands for driving in public road traffic with test drivers. The task of the test driver is to drive or supervise the vehicle in every situation in accordance with the task of the vehicle user. Transferred to autonomous driving, the use of a test driver in the driver’s seat would be non-real behavior of a user, as the user does not have to supervise the vehicle and the environment anymore and intervene.

Motoring of the future

Point 64, page 27 in report

50%

Witnesses discussed the research evidence for the effectiveness of different systems. Professor Sampson said that it was very difficult to research which technologies were most effective in terms of reducing accidents, because of the difficulties in running controlled trials of different features, with sufficient numbers of vehicles. Professor Carsten explained that the key struggle was with the continual monitoring and evaluation of technology, and developing an understanding of how casualty rates were affected over time by different technologies.

He explained that while it was statistically possible to show the safety benefits arising from car impact regulations, it was “really hard” to do this in relation to other safety approaches.

70%

Automated Vehicles, Are we ready ?

Chapter 3.3

AVs are capable of providing large amounts of data that could assist investigation in case of a crash. By recording the actions and forces involved in the minutes before and after a crash, they may help determine the cause of the crash and assist in resolving any liability dispute.

Motoring of the future

Point 33, page 15 in report

Telematics also known as ‘black boxes’ monitor the location of a driver and driving performance.

Safety Benefits of Automated Vehicles: Extended Findings from Accident Research for Development, Validation and Testing

However, a safety prognosis of highly or fully automated vehicles depends on assumptions, as so far no series applications of such features exist. For testing methods in order to develop and validate safe automated vehicles with reasonable expenditure, the author recommends combining area-wide traffic, accident, weather, and vehicle operation data as well as traffic simulations.

Two questions discussed in paper:

–What significance do analyzes and findings from road-accident research hold for the introduction of automated vehicles?

–How can the potential safety benefits of automated vehicles be established?

The validity of accident data regarding potential safety benefits varies considerably depending on the collection method.

IMPACT-Verkeersafwikkeling

According to different studies, anywhere from 20 percent to 95 percent of miles traveled on U.S. roads could be in AVs by 2030. Fully automated taxi fleets could become a reality between 2023 and 2030, according to a report by Bloomberg. nnNevertheless, expert predictions on the timeline and rollout of AVs vary greatly. Some experts believe that technical challenges may be more difficult to solve than currently expected, and Level 4 or higher AVs may not become commercially available until the 2030s or 2040s (Litman, 2017). If AV implementation follows a similar uptake pattern of other vehicle technologies, like air bags or automatic transmissions, it could take one to three decades to dominate vehicle sales, plus one or two more decades to dominate vehicle travel,

80% Driverless future A policy roadmap for city leaders Page 3 report Prioritize and modernize public transit. The role of transit will evolve as AVs and shared mobility become widespread. Transit agencies should focus on high-frequency, high-capacity services in dense urban corridors (such as rail, bus rapid transit), provide first and last-mile connections through driverless shuttles, and expand kiss-and-rides/mobility hubs.

60% MOBILITY TRENDS: ELECTRIC, CONNECTED, SHARED Slide 6 and onwards Reducing car dependency in the city? Combined Mobility is the key! All services have their place in the urban mobility system but we need measures to optimise complementarity between the different modes and ensure every mode plays the right role. Without public transport, other sustainable & innovative mobility services cannot offer an affordable alternative to car ownership. In Paris, 65 % of Uber trips start or end within 200m of a metro station AV offer the potential to provide public transport ‘last mile’ services. To be efficient and reduce congestion, AV must be shared AV are already in operation in public transport networks. The challenge is to anticipate the future role and impact of this new transport mode in the wider urban mobility picture.

“Autonomous driving could have a dramatic, albeit gradual, effect on each of the traffic concepts discussed in the previous section. Absent other phenomena, the total cost of motor vehicle travel is likely to decrease, and demand for that travel is likely to increase faster than corresponding capacity.”

Gevonden in (p.1409): Managing Autonomous Transportation Demand

 

70%

Traffic Control and Traffic Management in a Transportation System with Autonomous Vehicles

Chapter 15.8 Conclusion

It was demonstrated in Sect.15.4, for example, that the capacity of a traffic signal can certainly be doubled. If the demand is low at the corresponding signal,this doubling is scarcely noticeable. But if the signal is working at the limits of its capacity, by contrast, even a minor increase in its capacity can lead to a dramatic

Improvement.

This can be observed quite clearly in the scenario in Sect.15.5: here the demand runs the values from very low to (temporary) over-saturation. Although the introduction of autonomous vehicles has little impact on green times and delays when demand is low, it yields major improvements when the system is operating beyond capacity. Nevertheless, the magnitude of these improvements does depend on the details of the scenario being examined. If the peak value for demand were just a bit lower, the benefit would also be significantly diminished. That notwithstanding, it may be asserted with confidence that at least in the urban context, the introduction of autonomous vehicles has the potential to generate substantial time gains at traffic signals which would then be available for other road users—if the introduction of these vehicles does not lead to an increase in demand for automotive transportation

50%

Methodische Verkenning Zelfrijdende Auto’s  en  Bereikbaarheid
Chapter 2.2.1 (Capacity with and without bottlenecks mixed AV non AV)

Arnaout en Bowling (2011) vonden voor een weg met 4 rijstroken in een scenario met en zonder oprit dat CACC een positief effect op de capaciteit heeft (tot +60% bij een penetratiegraad van 100%) als de penetratiegraad groter is dan 40% en de instroom hoog genoeg is. Bij lagere penetratiegraden was het positieve effect klein. Als de instroom laag is (vrije doorstroming), vonden ze geen effect op de capaciteit. Ze veronderstelden dat CACC voertuigen een volgtijd van 0,5 seconde aanhouden als ze achter een ander CACC-voertuig rijden en 0,8 tot 1,0 seconde (uniform verdeeld) als ze achter een ander voertuig rijden. Of men in praktijk deze korte volgtijden durft aan te houden is een grote uitdaging volgens hen (Shladover, Su, & Lu, 2012).

De CACC-voertuigen kunnen hun voorliggers volgen zonder dat de bestuurder gas hoeft te geven of hoeft te remmen; de bestuurder moet wel het voertuig in de strook houden. Er werd een overbelaste snelweg in gemodelleerd, met een lengte van 6,5 km en een snelheidslimiet van 105 km/uur zonder bottleneck . In de simulaties waren vier voertuigtypen aanwezig:

50%

Methodische Verkenning Zelfrijdende Auto’s en Bereikbaarheid

Hoofdstuk 2.6

ACC kan zowel een klein negatief als een klein positief effect hebben op de capaciteit (~ -5% -+10%). Voor CACC rapporteren de meeste studies een kwadratische toename van de capaciteit als penetratiegraad toeneemt met een maximale theoretische toename van 100% (verdubbeling). ACC en CACC hebben een positief effect op de stabiliteit. Bij hogere penetratiegraden ontstaan minder schokgolven en isde duur van de schokgolven aanmerkelijk korter.

 

The Effect of Autonomous Vehicles on Traffic

16.3 Gives theory for why capacity increases of purely AV traffic

 

Methodische Verkenning Zelfrijdende Auto’s en Bereikbaarheid

Chapter 2.2.4

70%

Naar verwachting neemt als gevolg van peloton vorming van vrachtverkeer de capaciteit uitgedrukt in voertuigen per uur naar verwachting toe mits de colonnes niet teveel het weven en in-en uitvoegen bemoeilijken. De verklaring hiervoor is dat vrachtwagens dichter achter elkaar kunnen rijden.(Minderhoud & Hansen, 2002)

 

Immers,als gevolg van de korte volgtijden neemt de pae-factor naar verwachting af. We hebben geen literatuur kunnen vinden die hier verder op ingaat. Wel zijn de onderstaande verwante studies uitgevoerd die inzicht kunnen bieden.
Vervolgens is een bottleneck geïntroduceerd om naar de capaciteitswaarden en pae-factoren te kijken bij een toenemende intensiteit en toenemend percentage vracht. Als de capaciteit bereikt is ligt de pae-waarde tussen de 1,9 en de 2,1 afhankelijk van het percentage vracht met een elasticiteit van 0,01 (als het percentage vracht met 1% toeneemt, neemt de pae-waarde met 0,01 toe). Dit is alleen getest voor vracht percentages tussen de 0%-20%. De capaciteit in pae blijft ongeveer constant.

70%

The Effect of Autonomous Vehicles on Traffic

Chapter 16.4.2

The models developed for traffic flow and capacity, assuming a given share of autonomous vehicles, show that capacity increases disproportionately highly as the share of autonomous vehicles increases. It should be noted that the shortening of the time gaps comes into effect as early as the first autonomous vehicle; the speed increase at high densities, however, will only be possible for purely autonomous traffic. The introduction of autonomous vehicles will succeed, in the opinion of the author, only in their ability to move safely in mixed traffic, as reserved transit areas would not be socially or economically acceptable, particularly with a low share of autonomous traffic. However, once a sufficient number of vehicles with autonomous capabilities are participating in traffic, it will be very beneficial to the transport efficiency to create reserved lanes for autonomous driving. The benefits of autonomous vehicles can be maximized by separation due to the nonlinear course of the capacity once non autonomous vehicles are added to autonomous traffic. In conjunction with specially dedicated lanes, the column speed could also be increased even when traffic demand is higher, which would lead to further significant capacity gains. This is not possible in mixed traffic, since even in trafficwith only a few human-driven vehicles, these would dictate the speed.
50%

Autonomous Driving: Disruptive innovation that promises to change the automotive industry as we know it

Page 7 report

Looking forward, we project “Level 3: limited self-driving automation” to be available by 2018-2020 with features such as highway chauffeur (automated driving on highways). Furthermore, we expect “Level 4: full self-driving automation” to be first offered for low speed situations by 2020-25 (e.g., in parking lots or low-speed areas) and eventually, including more complex operations to be offered by 2025-30 (e.g., city driving). Even with the introduction of new technologies, we do not expect global adoption of full self-driving automation with “door-to-door” capabilities across all vehicle segments before 2030-40.

 

LEGAL-Privacy

De concrete vraag die daarbij hoort is: kunnen de gegevens direct of indirect, bijvoorbeeld via hetncombineren van data, worden herleid tot een persoon?nBijvoorbeeld: voertuigidentificatiegegevens (Voertuig Id Nummer en kenteken) worden alsnpersoonsgegeven beschouwd, omdat zij via de registers in veel gevallen aan een natuurlijk persoonnkunnen worden gekoppeld. Als er geen sprake is van persoonsgegevens dan is de Wetnbescherming persoonsgegevens (Wbp) en vanaf 25 mei 2018 de AVG niet van toepassing.nIn de AVG, waarbij de Europese wetgeving rechtstreeks in de lidstaten van toepassing is, is hetnbegrip persoonsgegevens uitgebreid. Locatiegegevens worden expliciet als persoonsgegevensnaangemerkt. Bovendien is door de Europese Autoriteiten Persoonsgegevens een interpretatie vannhet begrip persoonsgegevens gekozen die ertoe leidt dat het niet meer van belang is of iemandnuiteindelijk geïdentificeerd zal kunnen worden. Ook als een anoniem persoon geïsoleerd (singlednout) kan worden uit een groep, bijvoorbeeld een willekeurige weggebruiker op een bepaaldenlocatie, dan is het feit dat deze weggebruiker individueel benaderbaar is voldoende om dengegevens als persoonsgegevens aan te merken. Het is immers mogelijk om bijvoorbeeld op dienbepaalde locatie een locatie gebonden reclameboodschap aan de weggebruiker te zenden.nIn feite komt het erop neer dat de verwerkte gegevens van een gepersonifieerde smart mobilitynapp in beginsel als persoonsgegevens zullen moeten worden aangemerkt, tenzij kan wordennaangetoond dat het isoleren van personen niet mogelijk is.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

• Aan de verwerking van persoonsgegevens worden verschillende eisen gesteld. Zo moet denverwerking rechtmatig zijn, behoorlijk en transparant. Het eerste betekent dat er eenngeldige rechtsgrond moet zijn. Het laatste betekent dat de verwerking navolgbaar moetnzijn en van behoorlijke kwaliteit.n• Ook moet het doel van de verwerking welbepaald zijn en uitdrukkelijk omschreven en voorneen gerechtvaardigd doel verwerkt.n• De persoonsgegevens moeten bovendien toereikend zijn, maar beperkt tot het voor hetndoel noodzakelijke.n• Ook moeten de gegevens zowel formeel als materieel juist zijn. Formeel in de zin dat eenngeregistreerd adres een bestaand adres is, materieel dat de betrokkene ook werkelijk opndat adres woont.n• De gegevens moeten ook zoveel mogelijk in een vorm worden bewaard die identificatienbuiten de doeleinden waarvoor ze werden verwerkt verhinderd.n• De gegevens worden beschermd door passende technische en organisatorischenmaatregelen.n• De verwerkingsverwerkingsverantwoordelijke is gehouden tot het naleving van denbeginselen en moet die naleving kunnen aantonen.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

De eerste stap is het beantwoorden van de vraag of de activiteit of dienst ook zonder denverwerking van persoonsgegevens kan worden uitgevoerd. Als dat het geval is, dan mogen geennpersoonsgegevens worden verwerkt.nAls de verwerking van de persoonsgegevens wel nodig is voor de activiteiten of dienstverlening dannis het zaak om het gerechtvaardigde doel zo helder en compleet mogelijk te formuleren ennduidelijk te communiceren naar de betrokkenen. Alle beoogde toepassingen moeten daarbij wordennvermeld, ook de toepassingen nadat de gegevens geanonimiseerd zijn. Overigens is anonimiserennmet de huidige technologie en de ruime interpretatie van het begrip persoonsgegevens zeernmoeilijk geworden.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

In eerste instantie beoordeelt de verwerkingsverantwoordelijke dat zelf, meestal degene die dendienst ontwerpt en in de markt zet. Deze geeft antwoord op de vraag of het mogelijk is de dienstnte leveren zonder gebruikmaking van persoonsgegevens.nAls de verwerking van persoonsgegevens gerechtvaardigd is, dan moet een rechtsgrondslagnworden bepaald op basis waarvan de persoonsgegevens kunnen worden verwerkt.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

Bij de meeste dienstverlening ligt het voor de hand om bij de bepaling van de rechtsgrond uit tengaan van toestemming van de betrokkene, die dan wel voordat hij/zij toestemming geeft goedngeïnformeerd moet zijn in heldere begrijpelijke taal.nOok andere rechtsgronden zijn denkbaar maar omdat zij geen expliciete toestemming van denbetrokkene omvatten zullen zij goed moeten worden onderbouwd om verrassingen achteraf tenvoorkomen. Voor dienstverlening valt te denken aan de verwerking in het kader van de uitvoeringnvan een overeenkomst met de betrokkene, of verwerking in het geval dit in het legitieme belang isnvan de verantwoordelijke. Voor deze laatste rechtsgrond is wel vereist dat een goede afwegingnwordt gemaakt tussen de belangen van de betrokkene en die van de verwerkingsverantwoordelijken(balancing test).nHet makkelijkste is natuurlijk om voor een wettelijke rechtsgrondslag te kiezen waarover weinignmisverstand kan ontstaan, zoals ‘informed consent’, of verwerking ter uitvoering van eennovereenkomst met de betrokkene. Als er discussie ontstaat over de toestemming dan kan denAutoriteit Persoonsgegevens beoordelen of de toestemming al of niet terecht is. Toestemming moetnvoldoende specifiek zijn (dus niet toegestaan zijn formuleringen als: ‘de gegevens zullen wordennverstrekt aan zorgvuldig door ons geselecteerde derden’) en in vrijheid gegeven. Inngezagsverhoudingen, zoals tussen werkgever en werknemer is van vrijheid doorgaans geen sprake,nmaar bij deelname aan een loterij in ruil voor afgifte van persoonsgegevens voornmarketingdoeleinden zal dit doorgaans wel het geval zijn.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

Bij de verwerking van persoonsgegevens geldt een aantal wettelijke voorwaarden waaraan moetnworden voldaan gedurende de verwerking van de persoonsgegevens:n• Omvang van de verwerking mag niet groter zijn dan voor het doel noodzakelijk isn• Duur van de verwerking mag niet langer zijn dan voor het doel noodzakelijk isn• Beveiliging van de gegevens moet plaatsvinden volgens ‘state of the art’ technischenstandaarden tegen redelijke kosten, proportioneel aan het belang van dengegevensverwerking. Regelmatige aanpassingen zijn dus vereist. (zie ook de stukken bijnde Smart Mobility community security;nhttp://smartmobilitycommunity.eu/bibliotheek?f%5B0%5D=og_group_ref%3A21nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

Om de persoonsgegevens te mogen verwerken moet de verwerkingsverantwoordelijke eennzogenoemde rechtsgrond hebben. De meest voor de hand liggende rechtsgrond voor SmartnMobility diensten is toestemming van de betrokkene. Om deze toestemming rechtsgeldig te kunnenngeven moet de betrokkene wel geïnformeerd zijn over wat de verwerking van de gegevens inhoud,nen of de gegevens bijvoorbeeld worden doorgeleverd aan derden. Ook kan een overeenkomst metnde dienstverlener leiden tot de verwerking van persoonsgegevens. Dit doet zich voor als dendienstverlener de overeengekomen dienst niet kan leveren zonder persoonsgegevens tenverwerken. Dit zal bij Smart Mobility diensten regelmatig het geval zijn.nOverige, minder vaak voorkomende rechtsgronden zijn de uitvoering van:n• een wettelijke verplichting van de verwerkingsverantwoordelijke,n• een vitaal belang van de betrokkene,n• het algemeen belang,n• een gerechtvaardigd belang van de verwerkingsverantwoordelijke.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

De betrokkene kan op elk moment zijn toestemming intrekken. Dit heeft alleen gevolgen vanaf hetnmoment van de intrekking. Verwerkingen die daarvoor hebben plaatsgehad blijven rechtsgeldig.nOok kan de overeenkomst die als rechtsgrondslag dient worden opgezegd. Dan zal de bevoegdheidntot het verwerken van de persoonsgegevens in de regel stoppen zodra de overeenkomst eindigt. Inngeval van andere rechtsgronden, die buiten de directe invloedsfeer van de betrokkene liggen is hetneenzijdig stoppen van de verwerking niet zonder meer mogelijk.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

In het geval de persoonsgegevens van de betrokkene met toestemming worden verwerkt moet denverwerkingsverantwoordelijke voorafgaand aan het verkrijgen van de toestemming de betrokkeneninformeren over welke gegevens om welke reden worden verwerkt, en hoe dat gebeurt. In hetngeval van een overeenkomst zou de verwerking uit de overeenkomst moeten zijn af te leiden. Innalle gevallen kan de betrokkene een informatieverzoek indienen bij denverwerkingsverantwoordelijke.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

Persoonsgegevens mogen aan derden worden doorgegeven mits dat gebeurt met toestemming vannde betrokkene voor gebruik door specifiek benoemde (categorieën van) derden en binnen dendoelstelling van de verwerking. Voor doorgifte buiten de EU gelden aparte regels.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

De volledige persoonsgegevens moeten direct nadat zij hun gebruiksdoel hebben gediend wordennsnel worden verwijderd of ten minste geanonimiseerd. Verder kunnen er voorschriften zijn die hetnbewaren van de gegevens gedurende een bepaalde periode mogelijk maken.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

De betrokkene kan te allen tijde aan de verantwoordelijk vragen om informatie over de vannhem/haar verwerkte persoonsgegevens. De verwerkingsverantwoordelijke moet een dergelijknverzoek inwilligen mits het niet tot buitensporige inspanningen leidt. In het geval dat het verzoeknongegrond of buitensporig is mag de verwerkingsverantwoordelijke de verstrekking van informatienaan de betrokkene weigeren of de kostprijs ervan doorberekenen.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

In dat geval kan de verwerkingsverantwoordelijke worden gevraagd deze gegevens te corrigerennof, indien gewenst door de betrokkene, laten verwijderen.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

Als uit het antwoord op het verzoek om informatie aan de verwerkingsverantwoordelijke blijkt datner meer gegevens worden verzameld dan voor het doel van de verwerking noodzakelijk is, dannmoeten deze onmiddellijk worden verwijderd.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

Ja, dat kan. De verwerkingsverantwoordelijke heeft de plicht om de gegevens in een machineleesbarenvorm aan de betrokkene ter beschikking te stellen, zodat deze ze mee kan nemen naarneen andere dienstverlener, de zogenoemde dataportabiliteit.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

Helemaal zeker is niet zo gemakkelijk, maar na de verwijdering, bijvoorbeeld na overstappen naarneen andere provider zou een verzoek kunnen worden gedaan aan de oorspronkelijke provider omninzage in de persoonsgegevens die deze nog onder zich heeft. Dan kan blijken of de gegevens al ofnniet zijn verwijderd.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

De betrokkene kan als hij/zij een klacht heeft over de verwerking deze indienen bij de AutoriteitnPersoonsgegevens (AP). Als de gegevensverstrekking voortvloeit uit een wettelijke of contractuelenverplichting, dan moet de verwerkingsverantwoordelijke de betrokkene wijzen op de mogelijkengevolgen als de gegevens niet worden verstrekt, bijvoorbeeld dat de dienst niet of slechts ten delenkan worden verleend.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

De verwerkingsverantwoordelijke is degene die doel en middelen van de verwerking bepaalt,nanders gezegd het hoe en waarom van de verwerking. Zonder de verwerkingsverantwoordelijkenzou er geen verwerking van de persoonsgegevens hebben plaatsgevonden.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

Om te beginnen kijken of de verwerking van data ook persoonsgegevens omvat. Als dat het gevalnis moet de omvang van de verantwoordelijkheid worden vastgesteld, zijn er bijvoorbeeld meernpartijen met een verantwoordelijkheid (gedeelde verwerkingsverantwoordelijkheid). Vervolgensnmoet ervoor worden gezorgd dat de verwerkingen waarvoor u verantwoordelijk bent innovereenstemming met de regels worden uitgevoerd en voldoende transparant en te verantwoordennzijn. Daarbij is het van belang de verwerking zo in te richten dat datalekken tijdig wordenngedetecteerd en gerapporteerd aan de Autoriteit Persoonsgegevens (AP).nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

De eerste voorwaarde is dat de verwerkingsverantwoordelijke moet kunnen aantonen dat erntoestemming conform de wettelijke definitie is verleend. Dat wil zeggen dat de toestemming eennvrije, specifieke, geïnformeerde en ondubbelzinnige wilsuiting van de betrokkene moet zijn. Hij/zijnmoet door middel van een verklaring of een ondubbelzinnige actieve handeling aangeven dat hij/zijnde verwerking van persoonsgegevens aanvaardt. Een ander voorwaarde is dat de betrokkene dentoestemming op ieder moment moet kunnen intrekken. Deze mogelijkheid moet voorafgaand aannde toestemming worden meegedeeld aan betrokkene. Ook moet de verwerkingsverantwoordelijkennagaan of de toestemming vrijelijk kan worden gegeven. Dit is bijvoorbeeld niet het geval bijntoestemming gegeven door werknemers in het kader van hun dienstverband.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

Bijzondere categorieën persoonsgegevens zijn persoonsgegevens waaruit bijvoorbeeld etnischenafkomst, politieke opvattingen, religieuze of levensbeschouwelijke overtuigingen, of hetnlidmaatschap van een vakbond blijken. Verwerking van deze gegevens is verboden tenzij aan eennvan de ontheffingsvoorwaarden wordt voldaan. De voor het Smart Mobility veld belangrijkste is denuitdrukkelijke toestemming van de betrokkene.nDe regeling geldt ook voor de verwerking van genetische gegevens, biometrische gegevens metnhet oog op de unieke identificatie van een persoon, of gegevens over gezondheid, of gegevens metnbetrekking tot iemands seksueel gedrag of seksuele gerichtheid. Gevoelige gegevens zijn gegevensndie potentieel kunnen leiden tot het blootleggen van bijzondere categorieën gegevens. In het kadernvan Smart Mobility gaat het dan bijvoorbeeld om locatiegegevens, waaruit in bepaalde gevallennkan worden afgeleid waar iemand heen gaat, bijv. kerk, ziekenhuis etc.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

Gelet op het risico dat uit de gevoelige gegevens persoonsgegevens van de bijzondere categorienkunnen worden afgeleid, zal vooral voorkomen moeten worden dat deze gegevens te lang wordennbewaard. Ingeval van verwerken van locatiegegevens zouden deze direct na de verwerking moetennworden geanonimiseerd of weggegooid.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

In de verordening zijn enkele criteria opgenomen waaraan de beveiliging moet voldoen. Dezencriteria moeten overigens per verwerking nader worden ingevuld. Het moet om te beginnen gaannom State of the Art beveiliging. Dat betekent dat de techniek regelmatig moet worden ge-update.nVerder moet de beveiliging proportioneel zijn. Dat betekent in verhouding tot het te beschermennbelang. Bij gevoelige gegevens dus bijvoorbeeld een hoger niveau dan bij gewonenpersoonsgegevens. Tenslotte moeten de kosten van de beveiliging ook proportioneel zijn, innovereenstemming met het te beschermen belang. Daarbij gaat het niet alleen om technische, maarnook om logische en organisatorische maatregelen. Al deze maatregelen samen bepalen hetnbeveiligingsniveau.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

Ten behoeve van controle door de AP moet een register van verwerkingen worden bijgehoudenndoor de verwerkingsverantwoordelijke, waarin de volgende informatie is opgenomen:n• naam en contactgegevens van de verwerkingsverantwoordelijke,n• de verwerkingsdoeleinden,n• een beschrijving van de categorieën persoonsgegevens,n• de categorieën van ontvangers,n• eventuele doorgiften buiten de EU,n• de termijnen waarbinnen de gegevens moeten worden gewist,n• een beschrijving van de beveiligingsmaatregelen,n• eventuele verwerkers die worden ingeschakeld.nHet register kan schriftelijk of elektronisch worden opgesteld.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

Dat hangt af van de omvang en de aard van de verwerking. Bijvoorbeeld of dengegevensverwerking regelmatige observatie vereist, of als er sprake is van bijzonderenpersoonsgegevens. In dat geval is een FG op grond van de AVG verplicht. Ook een vereniging ofnander orgaan dat categorieën verwerkingsverantwoordelijke vertegenwoordigd kan namens dezenbedrijven een FG in dienst nemen die vervolgens deze rol voor de desbetreffende bedrijven speelt.nDaarbij is van groot belang dat de FG onafhankelijk is van het management van de betrokkennbedrijven en van het bestuur van de vereniging.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

In geval van een datalek moet de verwerkingsverantwoordelijke dit zo spoedig mogelijk, maarnuiterlijk binnen 72 uur melden bij de AP, tenzij het niet waarschijnlijk is dat het lek de rechten ennvrijheden van de betrokkenen kan schaden. Tevens worden de betrokkenen zo snel mogelijkngeïnformeerd. Bij de melding aan de AP moeten de volgende meldingen worden gedaan:n• Aard en categorieën van persoonsgegevens,n• Naam en contactgegevens van de FG,n• Waarschijnlijke gevolgen van de inbreuk,n• Getroffen maatregelen.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

Dat mag aan een verwerker die voldoende garanties biedt ten aanzien van de bescherming van denrechten van de betrokkene. De voorwaarden waaronder de verwerker de persoonsgegevens magnbewerken moeten worden opgenomen in de verwerkingsovereenkomst.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

De verwerker wordt door de verwerkingsverantwoordelijke ingehuurd om in zijn/haar opdrachtnpersoonsgegevens te verwerken. Als er zo’n opdracht is dan bent u verwerker.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

U moet ervoor zorgen dat de verwerkingen die aan u zijn toevertrouwd in overeenstemming metnde regels worden uitgevoerd en voldoende transparant en te verantwoorden zijn. Daarbij mag unzonder voorafgaande schriftelijke toestemming van de verwerkingsverantwoordelijke geennonderaannemers inschakelen.nn Q&A Wouter van Haaften

Category: LEGAL-Privacy

LEGAL-Toelatingseisen

0%nnDit aspect is niet genoemd in de literatuur, en wellicht meer een vraag voor technical.nn 

75%nnUit: (The pathway to driverless cars, a code of practise for testing) “It is expected that automated driving systems will rely on the interaction and correct operation of several computers and electronic control modules. It will be important that:n

    n

  • Software levels and revisions running on each vehicle to be tested are clearly documented and recorded.
  • n

  • All software and revisions have been subjected to extensive and well documented testing. This should typically start with bench testing and simulation, before moving to testing on a closed test track or private road. Only then should tests be conducted on public roads or other public places.”
  • n

nUit: (Products Liability and Driverless Cars): ” Common sense would hold that, if an original manufacturer in no way participates in or promotes the post-sale installation of autonomous vehicle technology manufactured by a third party, the original manufacturer should not be liable for alleged defects in that technology. Unfortunately, some of the case law relating to liability for third-party conversions in other contexts doesn’t necessarily support this common sense conclusion.”

0%nnEr wordt niet gesproken over gedefinieerde prestatiemaatstaven. Dit kan erop duiden dat hier nog geen standaarden voor zijn ontwikkeld.

 nn25%nn(Report from the Commission to the European Parliament and the Council) Er is een richtlijn voor standaardisatie van ITS binnen de Europese Unie. De lidstaten moeten zelf wetgeving maken die daaraan voldoet.

0%nnEr wordt niet gesproken over gedefinieerde veiligheidsniveaus. Dit kan erop duiden dat hier nog geen standaarden voor zijn ontwikkeld.

100%nnUit (Societal Risk Constellations for Autonomous Driving. Analysis, Historical Context and Assessment): “Risk management must be adapted to the respective risk constellations and be conducted on the appropriate levels (public debates, legal regulations, politically legitimated regulation, business decisions, etc.). It is based on the description of the risk constellation, in-depth risk analyses in the respective fields and a societal risk assessment.”

TECHNICAL-(Cyber)Security

50% Adviesrapport Cybersecurity Autonoom rijdende voertuigen Fox IT (2014)nnDit rapport geeft inzicht in kwetsbaarheden van moderne voertuigen, risico’s bij introductie van autonoom rijdende voertuigen en mogelijke maatregelen om deze risico’s tegen te gaan.nOndanks de dreiging die klein is, is het toch ontzettend belangrijk om goede maatregelen te nemen.Voor de korte termijn is een zestal generieke maatregelen voorgesteld waarmee het op korte termijn mogelijk is een beeld te krijgen van de beveiliging van systemen voor autonoom rijdende auto’s, daarmee van de veiligheid van het rijden erin en de beveiliging te verbeteren. Deze 6 maatregelen richten zich op het onderzoeken van autonoom rijdende voertuigen op kwetsbaarheden, deze op te lossen en op het klaar zijn voor een aanvalnmiddels een gevonden kwetsbaarheid. Gezien de verwachting dat cybercrime voor autonoom rijdende voertuigen sterk zal groeien en dat niet alle problemen van tevoren te voorspellen zijn, wordt voor de lange termijn geadviseerd te streven naar een framework waarin maatregelen zich kunnen ontwikkelen.nn10% Whitepaper Cybersecurity and PrivacynnWhite-paper about the security and reliability of connected and cooperative mobility, the interoperability between road infrastructure managers, the different brands, suppliers and systems, and the protection of personal information which is collected and used.nThe seven subjects are:n- Connected and cooperative communicationn- Standardisationn- Security by designn- The need of system (component) certificationn- PKIn- Privacyn- Behaviournn10% ERTRAC Automated Driving RoadmapnnThe main objective of the ERTRAC Roadmap is to provide a joint stakeholders view o n the development of AUtomated Driving in Europe, The Roadmap starts from common definitions and a listing of available technologies, and then identifies the challenges for the implementation of higher levels of automated driving functions. Development paths are provided for the different categories of vehicles.nThe Key CHallenges identified should lead to efforts of Research and Development: ERTRAC calls for pre-competitive collaboration among European industry and research providers. The key role of public authorities is also highlighted: for policy and regulatory needs, with the objective of European harmonisation.

90% Adviesrapport Cybersecurity Autonoom rijdende voertuigen , Fox IT (2014)nnDit rapport geeft inzicht in kwetsbaarheden van moderne voertuigen, risico’s bij introductie van autonoom rijdende voertuigen en mogelijke maatregelen om deze risico’s tegen te gaan.nOndanks de dreiging die klein is, is het toch ontzettend belangrijk om goede maatregelen te nemen.Voor de korte termijn is een zestal generieke maatregelen voorgesteld waarmee het op korte termijn mogelijk is een beeld te krijgen van de beveiliging van systemen voor autonoom rijdende auto’s, daarmee van de veiligheid van het rijden erin en de beveiliging te verbeteren. Deze 6 maatregelen richten zich op het onderzoeken van autonoom rijdende voertuigen op kwetsbaarheden, deze op te lossen en op het klaar zijn voor een aanvalnmiddels een gevonden kwetsbaarheid. Gezien de verwachting dat cybercrime voor autonoom rijdende voertuigen sterk zal groeien en dat niet alle problemen van tevoren te voorspellen zijn, wordt voor de lange termijn geadviseerd te streven naar een framework waarin maatregelen zich kunnen ontwikkelen.nn60% Comprehensive Experimental Analyses of Automotive Attack SurfacesnnGeeft inzicht in manieren van digitale inbraak van autos.n‘’We discover that remote exploitation is feasible via a broad range of attack vectors (including mechanics tools, CD players, Bluetooth and cellular radio), and further, that wireless communications channels allow long distance vehicle control, location tracking, in-cabin audio exfiltration and theft.’’nn50% Security Challenges for Cooperative andInterconnected Mobility SystemsnnIdentificeert en kwantificeert risico’s van Interconnected Mobility Systems.nn‘’The biggest security risk factors foreseen are application data integrity validation, the usage of insecure position information and systems that are currently not secure by design. These risk factors will have to be addressed in the coming years, to pave the road for successful introduction of cooperative and interconnected mobility systems’’nn20% Roland Berger Global Automotive Supplier Study 2018nnReport for the automotive industry about disruptive technology and future prospects. What is the current situation, what can we expect in the the future and what challenges and consequences does that future bring. With the focus on security of connected vehicles the following threads and accompanying tips are found:n n- Internet based attacksn- Hardware attacksn- Sensor attacksn- Near-field wireless attacksn n- Threat vectors span all connected vehicle components and systemsn- Suppliers must design E/E architectures to prevent component-level attacks and understand the design implications for integration into vehicle sub-systems.n- Organization structures and design processes must adapt accordingly.n- Evolving legal and regulatory requirements for data security & protection and product safety must be addressed as well.nn20% Veiligheidsrisico’s van Automated/Connected MobilitynnIn this paper the innovation possibilities for the Dutch state on the field of cyber security of automated/connected mobility are mapped.

TECHNICAL-Architectuur

100% Ja dat kan; nnLearning to Drive: Perception for Autonomous Cars Chapter 3 smooth road detectionnn‘’Accurate perception is a principal challenge of autonomous off-road driving. Perceptive technologies generally focus on obstacle avoidance. However, at high speed, terrain roughness is also important to control shock the vehicle experiences. The accuracy required to detect rough terrain is significantly greater than that necessary for obstacle avoidance. self-supervised learning approach for estimating the roughness of outdoor terrain. Our main application is the detection of small discontinuities that are likely to create significant shock for a high-speed robotic vehicle. By slowing, the vehicle can reduce the shock it experiences. Estimating roughness demands the detection of very small surface discontinuities – often a few centimeters. Thus the problem is significantly more challenging than finding obstacles.’’ Experimental results from this paper show that speed control – reduction  used offers significant improvement in shock  detection.nn80% Self-supervised Road Detection in Desert TerrainnnThe paper presents a method for identifying drivable surfaces in difficult unpaved and offroad terrain conditions as encountered in the DARPA Grand Challenge robot race. Instead of relying on a static, pre-computed road appearance model, this method adjusts its model to changing environments. It achieves robustness by combining sensor information from a laser range finder, a pose estimation system and a color camera. Using the first two modalities, the  system first identifies a nearby patch of drivable surface. Computer Vision then takes this patch and uses it to construct appearance models to find drivable surface outward into the far range. This information is put into a drivability map for the vehicle path planner.

50% Do Autonomous Vehicles Learn?nnSelf learning capabilities of autonomous vehicles. The paper discusses discuss why, whether, and with which challenges and approaches machine learning is possible in its current form in autonomous driving. The paper portrays the view of vehicle technology in particular on this question, and is based on experience from the literature for the area of machine learning.

60%nnModel Based Vehicle Detection and Tracking for Autonomous Urban DrivingnnThis paper describes the moving vehicle detection and tracking module that we developed for our autonomous driving robot Junior. The module provides reliable detection and tracking of moving vehicles from a high-speed moving platform using laser range finders. The paper presents the notion of motion evidence, which allows us to overcome the low signal-to-noise ratio that arises during rapid detection of moving vehicles in noisy urban environments.nn20% Toyota and a Boy Wonder Team Up on Self-Driving CarsnnArticle describing the team up of Toyota and Luminar. Toyota is buying lidar systems from Luminar for their autonomous driving cars. The article says a few things about what lidar systems can see when used in autonoumous driving.nn20% Laser kijkt om de hoeknnArticle describing the tests researchers from Stanford University are doing with lasers. The tests focus on detecting objects behind obstacles, they use a laser to look around the corner. The setup works in real word test with traffic signs and other reflective objects, it isn’t so effective with object that don’t reflect a lot of light. They are improving the system to be able to handle these objects as well as sunny days when there is a lot of interference.

TECHNICAL-Data

30% Digital Infrastructure (for Road Transport Automation) (EU)nnPowerpoint presentation about VRA. Vehicle and Road Automation is a support action funded by the European Union to create a collaboration network of experts and stakeholders working on deployment of automated vehicles and its related infrastructure.nn 

Category: TECHNICAL-Data