Welcome to the Knowledge Agenda on Automatic Driving, an initiative of the Ministry of Infrastructure and Water Management, Department of Transport and the RDW-Vehicle-approval, to provide an online overview of available and required knowledge in the field of automatic driving.

The overview is divided into a number of knowledge domains to map the various facets. In the library you will find an extensive collection of reports, papers and presentations, including summaries and background information. The library is used worldwide. The last report on Ethics was requested 674 times in a short time! About 30 pieces are downloaded every day.

The collection of knowledge documents is managed in Dropbox. With Dropbox you can search directly in the folders with documents and full text. Contact joop@veenis.net to gain access to the Dropbox.

Since 2015 we keep a list of knowledge questions (the required knowledge). Our collection of documents provides an answer to these knowledge questions. New questions are coming up because we are getting further and further into the implementation of “Connected Automated Driving”. The set of knowledge questions includes the topics automated driving and Smart Mobility (ITS). Additional overviews with projects are available here on the ITS theme. Experts on themes also develop knowledge and standards in the Netherlands/EU; an overview can be found here.

The popular knowledge questions are:


There are multiple models/players:nnThe Branded Integrated Life-Style ModelnnIt’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.nnIn 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.nnThe Branded Lifestyle Value Proposition: Design, Technology, Software, Consumer experience nnThe Open System ModelnnIt’s all about the data and how to use these data to customize the consumer value proposition.The market for big datannis 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 couldnnwell 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.nnThe Open System Value Proposition: Utility, Technology, Customization nn Mobility On Demand ModelnnZipcar 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.nnGiant retailers with a core competence in managing complex distribution channels or fleet providers with the capabilitynnto 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.nnThe Mobility on Demand Value Proposition: Flexibility, Reliability, Convenience, Cost nnThe OEM ModelnnTraditional 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.nnVertical 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.nnThe OEM Value Proposition: Design, Technology, HMI, Supply Chain Management “nnFound on (p.32-33): Self-Driving Cars, The Next Revolution

Regarding making PT more flexible:nnSuch 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.”nnRegarding offering new service options for PT:nnConcerning 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.”nnFound on (p. 186 & 187): New Mobility Concepts and Autonomous Driving: The Potential for Change

“Transport data analysis revealed that most feasible platooning trips have their origin and destination relatively close to each other (less than 100km).  nWhen 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 Impactnn 

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. Found on (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=0nn Note Joop: In the Netherlands there are tests concerning a connection with the station Ede and the Campus of Wageningen (WEPODS). In 2018 there will be tests with the WEPOD to the airport Weeze in Germany. There are also some test in the region MRDH near Airport Rotterdam.

The opinions are divided, depending on different assumptions about the future: nnProbable nothing imported in explained in the following article. :nn“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.” nnScenario with individual Public TransportnnOne 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. “nnFound on (p. 180 & 186):nnhttps://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=0nn

Our annual knowledge report reports on this. It indicates to which knowledge questions answers and research have become available. In December, we will put the subjects and knowledge questions for research and trials into the coming year. Currently, the priorities in the list of knowledge questions (AR + C-ITS) are being worked on by, among others, IenW, RWS, Knowledge Institutions and Provinces, Cities, regions and pilot projects.

On this site you will also find an overview of relevant conferences and events and a collection of films and webinars via the menu. News and current developments are maintained by us through the library and twitter feed (#KARNL). Every week, a lot of knowledge and material is added to the collection, in all knowledge areas.