Driverless cars and user acceptance (Fully) automated vehicles are becoming a reality. The technology is there. But are we ready? There is an important difference between the availability of a technology and its widespread adoption. In the case of automated mobility, the uncertainty concerning the timing towards the introduction of full automation for our personal use is huge, and subject to a lot of controversy. On the one hand, driverless vehicles inspire dreams of the future; on the other, user acceptance could be a major barrier in a move to full automation, and need to be included in assessments of future market uptake. – link to automation • Total autonomy is not necessarily an experience of freedom. Often people need some form of control over the vehicle they use to feel safe and independent. • Autonomous vehicles allow people to do multiple tasks at the same time. Their value of time will change as a result, and long travel times will become more acceptable. • Expectations at the consumer level need to be put in the perspective of the cost of automation. How much are people willing to pay for an automated car?• New forms of sharing of automated vehicles will grow compared to ownership, especially for the younger generations.• The introduction of AVs brings about some concerns with regard to ethics. A recent (May, 2016) survey in the US has found that, although only 17% of the respondents expressed concerns about the use of partially self-driving vehicles, “94.5% said they could not accept a vehicle that a human can’t control manually when needed.” In the UK, “65% of motorists believe that a human being should always be in control of the vehicle” . These results are a clear indication that user acceptance could be a major barrier in a move to full automation, and need to be included in assessments of future adoption. Today, automated vehicles (AVs) are a reality. According to the six levels of driving automation – from “no automation” to “full automation” – defined by SAE International’s new standard J3016, automated driving Level 0 and Level 1 are already fully deployed in the market. A recent study by the Society of Motor Manufacturers and Traders (SMMT) shows that, in the UK, “more than half of new cars registered in 2015 were fitted with safety-enhancing collision warning systems, with other technologies such as adaptive cruise control, autonomous emergency braking and blind spot monitoring also surging in popularity.” . Higher levels of automation are starting to be deployed in real life, albeit in dedicated environments. In addition, Volvo is about to launch an experiment in China, where drivers will use AVs in real-life conditions on public roads. In March 2016, Baidu together with BMW announced the intention to distribute AVs starting in 2018 . Plans are not limited to automated cars: for instance, Tesla has announced that they are working on an automated bus-like system that would be closer to micro-transit than to traditional bus services . Current levels of automation (or levels that will soon be operational) already go a long way towards what consumers expect from automated mobility. For instance, a recent survey found that “43.5% of survey respondents said the main reason they want driverless cars is so the car can find a parking spot and park itself”, although being able to multi-task came a close second with 39% . These relatively modest expectations at the consumer level need to be put in the perspective of the cost of further automation. Greenblatt and Shaheen (2015) reckon that the technology needed to enable automation (at Levels 3 and above) today costs around US$150,000, or approximately 133,000 EUR (market exchange rate of 15 April 2016). If we compare this to the total purchase price of a private automobile, this exceeds even the average purchase price of luxury brands, and is about five times larger than the average for all segments. In this respect, ride sharing turns out to be a crucial condition to better spread the high cost of automation among users. CROSS LINK WITH LAURENT’s AUTOMATION AND SHARING. There have been some questions regarding ethical considerations, particularly around how AVs should be programmed to react in complex crash situations where a choice has to be made on whose life to prioritise . While it is thought that the deployment of AVs will eventually lead to lower crash rates, it is possible that “improved safety for one group may come at the expense of another. If vehicle fatalities are reduced, but cyclist fatalities increase, even an overall safety improvement might be unacceptable to society” (IBID, p. 98). AVs create the so called ‘safety dilemma’: people want cars to minimize casualties, but everybody wants their own car to protect them at all costs. Another issue is related to security: automated vehicles could be used for terrorist attacks (such as car bombs) without any physical risk and with much lower risks of detection for the terrorist. Moreover, automated vehicles could be hacked for malicious purposes . Some argue that these security issues are not yet well understood (see Anderson et al. 2014). – link to safety and security The greater comfort provided by AVs, and the possibility for the traveller to engage in leisure or work activities instead of driving, may reduce the Value of Time spent in traffic. This will affect travel behaviour in several ways. People will tolerate longer travel times and longer commutes. This in itself could lead to longer distances travelled and, indirectly, to more urban sprawl. This sprawl could be the result of people and companies moving out of city centres. Secondly, people will become more tolerant of “wasting” time in periods of heavy traffic, and this may lead to even higher traffic during peak hours. It is thus really important to understand how the values of time will change as a result of automation (Wadud et al., 2016; Childress et al., 2015). All in all, the process towards full mobility automation will take decades and will be progressive, as more and more driving functions become automated. This progression will take into account user acceptance and preferences so that people will gradually become accustomed to automation. Anderson et al. (2014) Autonomous Vehicle Technology – A Guide for Policymakers, RAND publications, 2016 Childress et al. (2015) Using an activity-based model to explore possible impacts of automated vehicles, Submitted for presentation at the Transportation Research Board 2015 Greenblatt, J. B., S. Shaheen (2015) On-Demand Mobility, Autonomous Vehicles, and Environmental Impacts, Current Sustainable/Renewable Energy Reports, volume and issue forthcoming. DOI 10.1007/s40518-015-0038-5. Noah J. Goodall (2014) Machine Ethics and Automated Vehicles Author, Pre-print version. Published in G. Meyer and S. Beiker (eds.), Road Vehicle Automation, Springer, 2014, pp. 93-102 Wadud, Z., D. MacKenzie and P. Leiby (2016) Help or hindrance? The travel, energy and carbon impacts of highly automated vehicles, Transportation Research Part A: Policy and Practice, 86, 1–18.