How do familiarity and fatal accidents affect acceptance of self-driving vehicles?

Expected benefits of disruptive technologies such as self-driving vehicles may only materialize if they are publicly accepted. Acceptance increases when implementation is experienced as initial concerns become unfounded and individuals become familiar with the new technology. Fatal accidents, however, negatively affect acceptance. This paper examines citizens' acceptance of self-driving vehicles by contrasting pre- and post-implementation of a self-driving shuttle in Switzerland and before and after the first fatal accident involving a self-driving vehicle in Arizona (USA) in 2018 gaining high media attention. To gauge acceptance, a panel survey using a random sample of 1408 Swiss residents was used. The results indicate that news about the fatal accident abroad exerts a stronger effect on acceptance than experiencing a self-driving bus trial. Latent scepticism causes acceptance to decrease in the event of an accident but only lasts short term. However, acceptance levels are stable and at high levels, which also explains the comparably low familiarity effects. As public acceptance is necessary for technology transitions, this article provides policymakers practical insights on how citizens form preferences towards traffic automation and related policy regulations. More specifically, results show how attitudes change over time while residents experience a trial and the first fatal accident with the technology at hand.     

Driving without the brain? Effects of value predispositions,media attention,and science knowledge on public willingness to use driverless cars in Singapore

This study employs the cognitive miser model and science literacy model as theoretical frameworks to investigate motivations behind public willingness to use driverless cars in Singapore. Findings from a large-scale survey of 1,006 adult Singaporeans indicate that public willingness to use driverless cars was strongly related to value predispositions, especially affect. Aside from having a direct relationship with willingness to use driverless cars, this study found that affect also had an indirect relationship with willingness to use driverless cars via benefit perceptions. Meanwhile, findings failed to reveal significant relationships between two types of science knowledge and willingness to use driverless cars. The findings shed light on the current public opinion on driverless cars in Singapore and lend support to the cognitive miser model over the scientific literacy model. Theoretical and practical implications are discussed.     

Safety of autonomous vehicles: what are the insights from experienced industry professionals?

Many drivers support the push towards the automation of transportation. Technology and automotive companies, the general public, and governments are all seen as the main groups pushing the automation revolution forward. The key to this revolution's success will rest with the perception of the professionals in the field as their perception will affect the way that Autonomous Vehicles (AVs) are adopted. This study surveyed 185 experienced industry professionals to gather their comments and opinions on AVs' purported safety benefits and drawbacks. The results in this paper illustrate that the ‘incorrect understanding of the surrounding objects by AVs’ could be the most significant technical concern and may lead to accidents. Some professionals had concerns about trusting the AVs’ safe operation without steering wheels, while some others believed that there is a chance that having steering wheels may increase safety concerns. The findings also suggest that while AVs might reduce the number of accidents, this may not necessarily be the case for the severity of any accidents. The severity may remain unchanged or even increase as a result of the adoption of AVs. This paper's results show that the majority of the professionals consulted agreed that AVs have the potential to increase road safety significantly. However, the consensus was that more research and testing is needed in this field.     

Use of local public transport among people with cognitive impairments – A literature review

Being able to move around in the community including using different modes of transport is a prerequisite for being able to participate in activities outside home. This can be particular challenging for people with cognitive impairments. Still, research regarding public transport for people with cognitive impairments is scarce. In this narrative review scientific literature focusing on people with cognitive impairments and their needs in public transport, was identified and summarised. All aspects in the travel chain perspective were of interest. Literature search engines Scirus, Elin and Cinahl were used during the search.Thirty-four articles were included and analysed according to which part of the travel chain they covered in the used model. The results showed that the articles were unevenly allocated to the different parts of the model. Future studies based on real-world experiences are essential, and more user-centred approaches should be adopted. Moreover, there is a need for the development and evaluation of evidence-based rehabilitation. Finally, more research is needed to foster societal awareness of the problems and needs in the public transport of people with cognitive impairments taking the whole travel chain into consideration.     

How,and for whom,will activity patterns be modified by self-driving cars? Expectations from the state of Georgia

Many studies have explored travelers’ perceptions of self-driving cars (or autonomous vehicles, AVs) and their potential impacts. However, medium-term modifications in activity patterns (such as increasing trip frequencies and changing destinations) have been less explored. Using 2017–2018 survey data collected in the US state of Georgia, this paper (1) measures (at a general level) how people expect their activity patterns to change in a hypothetical all-AV era; (2) identifies population segments having similar profiles of expected changes; and (3) further profiles each segment on the basis of attitudinal, sociodemographic, and geographic characteristics. In the survey, respondents were asked to express their expectations regarding 16 potential activity modifications induced by AVs. We first conducted an exploratory factor analysis (EFA) to reduce the dimensionality of the activity-change vector characterizing each individual, and estimated non-mean-centered (NMC) factor scores (which have been rarely used in applied psychology). The EFA solution identified four dimensions of activity change: distance, time flexibility, frequency, and long distance/leisure. Next, we clustered Georgians with respect to these four-dimensional expectation vectors. The cluster solution uncovered six segments: no change, change unlikely, more leisure/long distance, longer trips, more travel, and time flexibility & more leisure/long distance. Using NMC factor scores identified considerably more inertia with respect to expectations for change than would have been apparent from the usual mean-centered scores. Finally, the various segments exhibit distinctive demographics and general attitudes. For example, those in the more leisure/long distance cluster tend to be higher income and are more likely to be Atlanta-region residents compared to other clusters, while those in the no change and change unlikely clusters tend to be older and are more likely to be rural residents.