When will most cars be able to drive fully automatically? Projections of 18,970 survey respondents
Introduction
Fully automated driving is expected to improve road safety and traffic flow efficiency and may have a considerable influence on transportation businesses (e.g., car insurance) and the shape of road infrastructure (Fagnant & Kockelman, 2015). Parking spaces within cities may soon no longer be needed, and road networks will likely change. Before fully automated driving becomes ubiquitous, appropriate transport policies will need to be developed regarding, for example, research funding, certification, liability, security, data privacy, communication protocols, vehicle registration, driving laws, taxes, insurance minimums, public-private cooperation, roadway design, and land use (for reviews and discussions on policies regarding automated driving, see Anderson et al., 2016, Fagnant and Kockelman, 2015, Fraedrich et al., 2019, Milakis et al., 2017, Smith, 2017).
The direction of influence of transportation policies runs both ways. On the one hand, policies can affect the uptake of automated driving: progressive policies can accelerate uptake (Smith, 2017), whereas premature regulations “can run the risk of putting the brakes on the evolution toward increasingly better vehicle safety technologies” (NHTSA, 2013). In a scenario-construction study, 20 experts in the Netherlands predicted that between 7% and 61% of the vehicle fleet would be fully automated by 2050 (Milakis, Snelder, Van Arem, Van Wee, & Correia, 2017), depending on the restrictiveness versus progressiveness of the assumed transportation policies. On the other hand, transport policies are themselves influenced by technological developments and current levels of excitement about automated driving. Parkhurst and Lyons (2018) explained that policies for automated driving are constructed around a common understanding of an inherently uncertain future. These authors lamented the “enthusiasm shown by many policymakers” and that the economic promises regarding automated vehicles “have seduced some policymakers”. Thus, it can be argued that responsible policymaking requires predicting when automated cars will be commonplace and regular monitoring of whether these predictions should be adjusted.
Futurists have long been concerned with making predictions about the introduction of automated vehicles. As early as 1940, Geddes outlined a blueprint of automated highway systems to be deployed in the United States (Geddes, 1940). In the late 1980s, Kurzweil predicted that by the end of the 1990s/early 2000s “the cybernetic chauffeur, installed in one’s car, communicates with other cars and sensors on the roads. In this way it successfully drives and navigates from one point to another” (Kurzweil, 1990). In 2012, Kurzweil admitted that his prediction was wrong, yet noted that it was “not all wrong”, considering the achievements in the Google self-driving car project (Kurzweil, 2012).
Predictions of the advent of fully automated driving have evolved from futurism to mainstream science and actual automotive practice. Automotive manufacturers are already testing their automated vehicles on public roads (Department of Motor Vehicles, 2018), with Waymo having reached the milestone of 10 million self-driven miles across 25 American cities (Waymo, 2018). However, these vehicles are not commercially viable yet and do not formally fulfil the definition of fully automated driving, because the automation occasionally disengages and a human driver has to take over control (Dixit, Chand, & Nair, 2016).
In August 2013, Nissan revealed plans for fully automated vehicles in 2020 (NissanNews.com, 2013), an estimate that was revised to 2022 in November 2017 (Nissan Motor Corporation, 2017) and repeated in March 2018 (Nissan Motor Corporation, 2018). In July 2016, BMW predicted that their first fully automated cars would be in production by 2021 (BMW News, 2016). In September 2018, the company presented the iNext model to be put in production in 2021; this is not an autonomous car but a highly automated one with a steering wheel that “retracts slightly” when in automated mode (BMW Group, 2018). Similarly, in August 2016, Ford announced that they expect their first fully automated cars for commercial ride sharing in 2021, although the chief technical officer of the company argued that fully automated cars with no steering wheel or pedals are unlikely to be available to customers before 2025 (Sage & Lienert, 2016). The company’s website as of May 2019 still referred to 2021 as the year when “Ford will have a fully autonomous vehicle in operation by 2021 …. the vehicle will operate without a steering wheel, gas pedal or brake pedal within geo-fenced areas …. By doing this, the vehicle will be classified as a SAE Level 4 capable-vehicle” (Ford Motor Company, 2019). In June 2016, Continental stated that they would be ready for production of fully automated cars by 2025 (Continental AG, 2016), an estimate persisting in September 2018 (Continental AG, 2018a). On the one hand, automotive manufacturers are expected to make accurate predictions regarding the deployment of fully automated cars, because it is the car manufacturers that together with OEMs and ICT companies develop and will sell those vehicles. On the other hand, the predictions by automotive manufacturers presented in the media may not be the most reliable source of information, because of potential conflicts of interest in the market uptake.
Shladover, one of the pioneers of automated driving research in the United States, argued that it is unlikely for fully automated cars to arrive any time soon: “fully automated vehicles capable of driving in every situation will not be here until 2075. Could it happen sooner than that? Certainly. But not by much.” (Shladover, 2016). In a survey among 217 attendees of an automated vehicle conference (31% of whom were employed in academia, 24% in the automotive industry, and 9% in government positions), Underwood (2014) observed a median of 2030 regarding the estimate when fully automated driving will be introduced to the market in the United States. Based on a survey among 3500 transport professionals in London, Begg (2014) reported that 10% of the respondents estimated that Level 4 vehicles would be commonplace on UK roads by 2030, whereas 20% reported 2040, 19% reported 2050, and 30% predicted that such a milestone would never be reached.
Besides polling the vision of automotive manufacturers, scientists, and other professionals, it is important to poll what the public thinks regarding the deployment of fully automated cars. It is the public who should eventually buy and use such vehicles and who will ultimately determine their future success. There is much to say about the hypothesis that aggregate predictions of a large number of individuals can be more reliable and accurate than the predictions of single experts, a phenomenon also known as the ‘wisdom of crowds’ or vox populi (Galton, 1907, Surowiecki, 2004). However, it has been found that only little social influence is required to undermine the wisdom-of-crowds effect (Lorenz, Rauhut, Schweitzer, & Helbing, 2011). The concept of automated driving has been said to be under the influence of media bias (Anania et al., 2018) and in the midst of a hype (Bartl and Rosenzweig, 2015, Lyons and Davidson, 2016). Shladover (2016) noted: “My concern is that the public’s expectations have been raised to unreasonable levels because of the hype out there on the Internet”. Drawing a parallel with the dot-com bubble between 1995 and 2001 (Ofek & Richardson, 2003), there may be significant risks associated with overconfident expectations regarding automated driving. If a hype indeed exists, the post-hype “trough of disillusionment” (cf. Fenn, 2007) may be characterized by a significant number of deprecated investments, preventable bankruptcies, and job losses. Hence, it ought to be monitored whether the crowd has overoptimistic expectations regarding the deployment of automated driving and whether these expectations are changing over time.
Previous surveys indicate that people appreciate automated driving, with a reduction in traffic accidents, emissions, and energy consumption being reported as important benefits (Bansal et al., 2016, Piao et al., 2016, Schoettle and Sivak, 2014). Continental, 2013, Continental, 2018b polled the public’s opinion on whether cars that drive themselves “will be a part of daily life in 5 to 10 years”. Results showed optimistic responses, with between 37% and 75% of respondents in agreement with the statement, depending on the survey year, respondents’ country, and the precise formulation of the question. Other survey research has revealed concerns about the security, privacy, legal liability, and ethical decisions of automated vehicles (Bonnefon et al., 2016, Kyriakidis et al., 2015, Schoettle and Sivak, 2014).
From the above, it is apparent that there is a lack of knowledge regarding when the public expects autonomous driving to be ubiquitous. This study aims to poll the public’s expectation regarding the moment when fully automated cars will be widespread and whether this expectation has been adjusted over time. Accordingly, large numbers of respondents from more than 100 countries were polled over the last 4.5 years.
Section snippets
Surveys
Between June 2014 and January 2019, we performed 15 surveys via the crowdsourcing service CrowdFlower (nowadays called Figure-Eight), mostly to poll people’s opinion on various aspects of automated driving, such as user’s acceptance, worries, willingness to buy, and preferences for human-machine interfaces. In each survey, the following question was included: “In which year do you think that most cars will be able to drive fully automatically in your country of residence?” Here, we analyze the
Results at the individual level
Table 2 provides descriptive statistics of the respondents per study. There were 21,017 respondents from 130 countries, of whom 18,970 respondents in 128 countries provided a numeric response to the question of interest or answered ‘never’. These 18,970 responses exhibited a skewed distribution, with a clear zero end-digit preference (Fig. 1).
Table 3 shows that across the 15 surveys, 23–49% of the respondents reported a year between 2017 and 2029. The median predicted year across all surveys
Discussion
Over the course of 4.5 years, we conducted 15 online surveys in which we asked respondents when most cars will be able to drive fully automatically in their country of residence. The first survey in which we asked this question was June 2014 (De Winter, Kyriakidis, Dodou, & Happee, 2015) and the last survey ran until January 2019.
The median reported year across all 15 surveys was 2030, which is more optimistic than previously published expert estimates (Begg, 2014, Litman, 2018, Milakis et al.,
Acknowledgments
The research presented in this paper is being conducted in the project HFAuto – Human Factors of Automated Driving (PITN-GA-2013-605817).
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