Impact of trust and travel experiences on the value of travel time savings for autonomous driving

Abstract

Autonomous driving is expected to strongly influence the value of travel time savings (VTTS) which is crucial for the assessment of the impact of automated vehicles (AVs). However, no consensus has been reached yet about the size and direction of the effect of AVs on VTTS. This high uncertainty around the VTTS is most likely due to high heterogeneity in preferences for travel time. Our hypothesis is that a key role in the heterogeneity of the VTTS for AVs is played by psychological factors. We focus in particular on Travel Experiences (besides individual preference for activities conducted during travelling) and Trust in travel time preferences for AVs. For this purpose, an online survey with a stated choice experiment and psychometric scales was conducted. Besides currently available transport modes, also a privately-owned AV (PAV) and a shared AV (SAV) were included in the choice sets. The data was analysed using a hybrid choice model. T-test and confidence intervals of the estimated VTTS are computed to assess if the VTTS are statistically significant and statistically different among user groups. Results confirm that both psychological factors have significant positive effect on VTTS for AVs. Gender, age, level of education and experience with similar systems were found to affect the VTTS directly and indirectly through their impact on the individual attitudes. Significant differences are found among some potential user groups, in particular in terms of trust to technology and anticipated travel experiences. For example, men are found to trust the technology more than women and also to have potentially higher technology affinity. However, our results show that they also perceive higher marginal disutility for travel time in both PAV and SAV. A comparison between a mixed logit model and the hybrid choice model reveals that capturing the indirect effect of the socio-economic characteristics of individuals through the effect of these factors on attitudes allows differentiating between the VTTS for different user groups. Lastly, implications for policy and technology deployment strategies are discussed based on the findings.