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 Waterstaat (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.


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



“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.”


“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


Uit Citymobil2 project:

Tabel met pathway to urban public transport.

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



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


“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


“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


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
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