Benodigde kennis

De benodigde kennis wordt in samenwerking bepaald tijdens werkbijeenkomsten en Ronde Tafels. Dit leidt tot kennisvragen die worden beheerd door het Ministerie van Infrastructuur en Milieu (DGB).

De onderstaande vragen zijn al deels beantwoord. De antwoorden staan in de documenten uit de collectie en zijn hier verzameld. (stand per maart 2017) Voor meer vragen en antwoorden: zie het Kennisjaarverslag.

DEPLOYMENT-Business models

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

 

Paper (no. 106, Heinrichs) states the following scenarios (business models) (see document and table 11.1)

Gevonden in (p. 220):

https://www.dropbox.com/s/iv8pe2nuz1wyggs/Heinrichs%2C%20D.%20%282016%29%20Autonomous%20Driving%20and%20Urban%20Land%20Use.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


Hieronder een lijst met een aantal documenten die enkel betrekking hebben op het subdomein. Er zijn nog meer documenten gerelateerd aan dit subdomein maar deze zijn ook gelinkt aan andere subdomeinen. De volledige collectie beschikbare documenten in onze online bibliotheek (catalogus en dropbox) 

Titel/Title Auteur(s)/Author(s) Product van/Produced by Opdrachtgever product/Product Requested by Publicatiedatum/ Publication date
Diffusion of Automated Vehicles J.A.H (Jurgen) Nieuwenhuijsen Technisch Universiteit Delft IenM-projectgroep zelfrijdende voertuigen 9-8-2015
Op advies van de auto J. Timmer (Rathenau Instituut)
J. Smids (TU Eindhoven)
L. Kool (Rathenau Instituut)
A. Spahn (TU Eindhoven)
R. van Est (Rathenau Instituut)
Rathenau Instituut Opdrachtgever Rathenau Instituut 1-1-2013
Het vervoer van morgen begint vandaag Marie-Pauline van Voorst tot Voorst, Rene Hoogerwerf STT, Den Haag STT, Den Haag 1-7-2013
Towards Safe and Efficient Driving through Vehicle Automation:The Dutch Automated Vehicle Initiative (DAVI) Raymond Hoogendoorn, Bart van Arem, Riender Happee, Manuel Mazo Espinoza and Dimitrios Kotiadis TU-Delft, Connekt TU-Delft, Connekt 30/11/2013
KPMG’s Global Automotive Executive Survey 2015 Dieter Becker KPMG International KPMG International 1-1-2015
Motoring of the future . The Transport Committee is appointed by the House of Commons to examine the expenditure, administration, and policy of the Department for Transport and its Associate Public Bodies. Ordered by the House of Commons 3-6-2015
Verkenning technologische innovaties in de leefomgeving Mr. H.M. (Henry) Meijdam, voorzitter Raad voor de leefomgeving en infrastructuur Nederlandse regering en parlement 31/1/2015
Automated Vehicles: Strategic Overview Bishop Bishop Consulting Rijkswaterstaat 18/12/2014
FEHRL Scanning Tour Automated Roads Tom Alkim Rijkswaterstaat FEHRL 14/12/2014
Recent International Activity in Cooperative Vehicle–Highway Automation Systems S.E. Shladover Federal Highway Administration’s (FHWA’s) Exploratory Advanced Research Program the FHWA Turner– Fairbank Highway Research Program’s Office of Operations Research and Development 15/12/2012
Grootschalig testen van zelfrijdende auto’s mw. drs. M.H. Schultz van Haegen Ministerie IenM de Tweede Kamer der Staten-Generaal 16/6/2014
De auto wordt automobiel Anouk Vrouwe TNO TNO 11-11-2013
Driverless Cars Are Further Away Than You Think Will Knight BMW BMW 22/10/2013
Preparing a Nation for Autonomous Vehicles Kara M. Kockelman, Ph.D., Daniel Fagnant The University of Texas, Department of Civil, Architectural and Environmental Engineering. The Eno Center for Transportation is a neutral, non-partisan think-tank that promotes policy innovation and leads professional development in the transportation industry. 15/10/2013
Kennisagenda Automatisch Rijden Tom Alkim, Joop Veenis VPS- Connekt Rijkswaterstaat 14/4/2015
INTELLIGENT VEHICLES + INFRASTRUCTURE TO ADDRESS TRANSPORTATION PROBLEMS – A STRATEGIC APPROACH John Maddox,  Dr. Peter Sweatman, Dr. Jim Sayer University of Michigan Mobility Transformation Center Ann Arbor, Michigan
United States
University of Michigan Mobility Transformation Center Ann Arbor, Michigan
United States
6-10-2015
Autonomous Fahren, technische, rechtliche und gesellschaftliche aspecten Markus Maurer, j. Christian Gerdes, Barbara Lenz, Herman Winner TU Braunschweig, Institut für Regelungstechnik, Deutschland, Stanford University, Stanford, USA Daimer Benz Stiftung 21/7/2015
Future of automated Vehicles Build Environment Workshop Steven E. Underwood, Ph.D. Graham Institute, TRB, AUVSI, and SAE Survey Results Graham Institute for Sustainability University of Michigan 29/07/2015
Truck-Platooning-Driving-the-future-of-Transportation Robbert Janssen, Han Zwijnenberg, Iris Blankers, Janiek de Kruijff TNO TNO 2-1-2015
AUVSI-TRB-Symposium2015-Presentaties-Deployment diverse Joop Veenis IenM-Rijkswaterstaat 31/07/2015
Urban Mobility Upgrade  Led by the ITF, work is carried
out in a collaborative fashion in working groups consisting of CPB
member companies, external experts and ITF researchers
International Transport Forum (ITF) International Transport Forum’s Corporate Partnership Board (CPB) 31/7/2015
Mini-Symposium-Steven-Shladover-Delft Steven Shladover California PATH Program Manager IenM-projectgroep zelfrijdende voertuigen 11//11/2015
European Truck Platooning Challenge 2016 People involved with the EC Truck Platooning Challenge where interviewed for this storybook The EU Truck Platooning Challenge 2016 is an initiative of the Dutch Ministry of Infrastructure and the Environment, managed by Rijkswaterstaat – in the framework of the EU Presidency 2016. Melanie Schultz van Haegen, Ministry of Infrastructure and the Environment 5-9-2016
Overview of pilots worldwide-2016 Compilation overview by Tom Alkim IenM-projectgroep zelfrijdende voertuigen IenM-projectgroep zelfrijdende voertuigen 08-03-2017
Overview of Roadmaps for Automated Vehicles worldwide Compilation overview by Tom Alkim IenM-projectgroep zelfrijdende voertuigen IenM-projectgroep zelfrijdende voertuigen 08-03-2017
Tem de robotauto – De zelfsturende auto voor publieke doelen Jelte Timmer, Linda Kool Rathenau Instituut Rathenau Instituut 02-10-2014
European Roadmap Smart Systems for Automated Driving Dr. Jadranka Dokic, Dr. Beate Müller, Dr. Gereon Meyer VDI-IT European Technology Platform on Smart Systems Integration 01-04-2015
Self-Driving Cars, The Next Revolution Gary Silburg, Richard Wallace KPMG LLP and the Center for Automotive Research (CAR) KPMG LLP and the Center for Automotive Research (CAR) ??/??/2012
Connected and Autonomous Vehicles – The UK Economic Opportunity John Leech, Mike Hawes KPMG LLP KPMG LLP ??/03/2015
Autonomous Cars – Self-Driving the New Auto Industry Paradigm Ravi Shanker, Adam Jonas, Scott Devitt, Katy Huberty, Simon Flannery, William Greene et al. Morgan Stanley LLC Morgan Stanley LLC 06-11-2013
Vision for the Dutch automotive sector PPS Automotive Federatie Holland Automotive PPS Automotive ??/05/2006
Roadmap between automotive industry and infrastructure organisations on initial deployment of Cooperative ITS Amsterdam Group Amsterdam Group C2C-CC, ASECAP, CEDR, POLIS 07-06-2013
On the road toward the autonomous truck: Opportunities for OEMs and suppliers Sebastian Gundermann, Norbert Dressler, Marc Winterhoff, Wilfried Aulbur, Wolfgang Bernhart Roland Berger Strategy Consultants Roland Berger Strategy Consultants ??/01/2015
Autonomous Driving—Political, Legal, Social, and Sustainability Dimensions Miranda A. Schreurs and Sibyl D. Steuwer Environmental Policy Research Centre (FFU), Freie Universität Berlin Springer Berlin Heidelberg 22/05/2016
New Mobility Concepts and Autonomous Driving: The Potential for Change Barbara Lenz , Eva Fraedrich German Aerospace Center (DLR), Institute of Transport Research Springer Berlin Heidelberg 22/05/2016
Deployment Scenarios for Vehicles with Higher-Order Automation Sven Beiker Stanford University Springer Berlin Heidelberg 22/05/2016
Autonomous Driving and Urban Land Use Dirk Heinrichs German Aerospace Centre (DLR), Institute of Transport Research Springer Berlin Heidelberg 22/05/2016
Implementation of an Automated Mobility-on-Demand System Sven Beiker Stanford University Springer Berlin Heidelberg 22/05/2016
Autonomous Vehicles and Autonomous Driving in Freight Transport Heike Flämig Technische Universität Hamburg-Harburg TUHH, Institute for Transport
Planning and Logistics
Springer Berlin Heidelberg 22/05/2016
Autonomous Mobility-on-Demand Systems for Future Urban Mobility Marco Pavone Department of Aeronautics and Astronautics, Stanford University Springer Berlin Heidelberg 22/05/2016
Automated and Autonomous Driving: Regulation under uncertainty Dr Bryant Walker Smith, Joakim Svensson International Transport Forum at OECD International Transport Forum’s Corporate Partnership Board (CPB) 05-07-2015
The Release of Autonomous Vehicles Walther Wachenfeld, Hermann Winner Institute of Automotive Engineering, Technische Universität Darmstadt Springer Berlin Heidelberg 22/05/2016
Preparing a Nation for Autonomous Vehicles: Opportunities, Barriers and Policy Recommendations Daniel J. Fagnant, Kara Kockelman Eno Center for Transportation Eno Center for Transportation ??/10/2013
Impact of Autonomous Vehicles on Urban Mobility Mohammed Azmat WU Vienna University of Economics and Business WU Vienna University of Economics and Business 29/07/2015
Self-Driving Cars: Disruptive or Incremental? Tao Jiang, Srdjan Petrovic, Uma Ayyer, Anand Tolani, Sajid Husain Sutardja Center for Entrepreneurship & Technology University of California, Berkeley Technology University of California 01-06-2015
The Road Ahead: The Emerging Policy Debates for IT in Vehicles Daniel Castro Information Technology & Innovation Foundation Information Technology & Innovation Foundation ??/04/2013
Truck Platooning – Enablers, Barriers, Potential and Impact B.A. (Bon) Bakermans Delft University of Technology TU Delft 29/08/2016
Climbing Mount Next: The Effects of Autonomous Vehicles on Society David Levinson Transportation, Department of Civil, Environmental, and Geo-Engineering, University of Minnesota Minnesota Journal of Law Science and Technology ??/??/2015
Ready or Waiting Todd Litman Traffic Technology International Traffic Technology International ??/01/2014
Managing Autonomous Transportation Demand Bryant Walker Smith CIS, the center for Internet and Society University of South Carolina 14/11/2012
How Governments Can Promote Automated Driving Bryant Walker Smith CIS, the center for Internet and Society University of South Carolina 17/3/2016
Societal Risk Constellations for Autonomous Driving. Analysis, Historical Context and Assessment Armin Grunwald Institute for Technology Assessment and Systems Analysis (ITAS), Karlsruhe Institute of Technology Springer Berlin Heidelberg 22/05/2016
Consumer Perceptions of Automated Driving Technologies: An Examination of Use Cases and Branding Strategies David M. Woisetschläger Institute of Automotive Management and Industrial Production, Technische Universität Braunschweig Springer Berlin Heidelberg 22/05/2016