Glimpse of the Future: Simulating Life with Personally Owned Autonomous Vehicles and Their Implications on Travel Behaviors

Abstract

To explore potential travel behavior shifts induced by personally owned, fully autonomous vehicles (AVs), we ran an experiment that provided personal chauffeurs to 43 households in the Sacramento region to simulate life with an AV. Like an advanced AV, the chauffeurs took over driving duties. Households were recruited from the 2018 Sacramento household travel survey sample. Sampling was stratified by weekly vehicle miles traveled (VMT), and households were selected to be diverse by demographics, modal preferences, mobility barriers, and residential location. Thirty-four households received 60 h of chauffeur service for 1 week, and nine households received 60 h per week for 2 weeks. Smartphone-based travel diaries were recorded for the chauffeur week(s), 1 week before, and 1 week after. During the chauffeur week, the overall systemwide VMT (summing across all sampled households) increased by 60%, over half of which came from “zero-occupancy vehicle” (ZOV) trips (when the chauffeur was the only occupant). The number of trips made in the system increased by 25%, with ZOV trips accounting for 85% of these additional trips. There was a shift away from transit, ridehailing, biking, and walking trips, which dropped by 70%, 55%, 38%, and 10%, respectively. Households with mobility barriers and those with less auto dependency had the greatest percent increase in VMT, whereas higher VMT households and families with children had the lowest. The results highlight how AVs can enhance mobility, but also caution against the potential detrimental effects on the transportation system and the need to regulate AVs and ZOVs.

Using Online Videos to Improve Attitudes toward Shared Autonomous Vehicles: Age and Video Type Differences

“…To assess the effects of age and our videos on respondents' attitudes towards SAVs, we performed a 3 × 4 MANCOVA analysis on the SAVUPS dimension difference scores (intent to use SAVs, trust in SAVs, perceived usefulness of SAVs, perceived ease of use of SAVs, and perceived AV safety) using the independent variables age group (younger (18)(19)(20)(21)(22)(23)(24)(25), middle (30-64), and older (65+)) and video condition (ridesharing control video, educational video only, experiential video only, both educational and experiential videos). We included the covariates gender, ridesharing comfort (i.e., how comfortable the respondent was sharing a ridesharing vehicle with another passenger), past and present ridesharing experience, perceptions of technology, as well as the pre-video SAVUPS dimensions cost (i.e., how much cost influences their intent to use SAVs) and desire for control/driving-efficacy (i.e., their preference to drive themselves despite having automation available).…”

“…The most notable increase in vehicle miles traveled (VMT) came from an older woman who used the chauffeur service to more than triple the amount she drove in a week (117 miles vs. 516), citing the novelty and the ability to satisfy her latent demand for longer trips than she felt comfortable driving herself. Harb and colleagues' preliminary study results and the results that followed from the full experiment [18] strongly suggest that many of the potential safety, sustainability, and benefits related to congestion will not be realized by AVs if they are personally owned by individuals instead of shared.…”

Impacts of Connected and Automated Vehicles on Travel Demand and Emissions in California

“…Thus, we apply a 15% increase in demand for all travel modes (including auto modes, transit, rail, and air) to account for the induced demand. This can be considered as even a conservative estimate when compared with the findings from recent studies (52). Further, the availability of CAVs would also generate extra deadheading that is not captured in the original CSTDM framework.…”

Fear of AI: an inquiry into the adoption of autonomous cars in spite of fear, and a theoretical framework for the study of artificial intelligence technology acceptance

“…3, are sound and based on valid reasons that academia itself has found and discussed in recent studies. For example, several scholars argue that autonomous cars will generate individual benefits by eliminating the stress of driving (Arakawa et al 2019) and increasing one's productivity (Harb et al 2022;Malokin et al 2019). Similarly, in relation to urban benefits, there is a substantial body of academic literature positing that merging AI technologies and transport technologies together will reduce car accidents (Rezaei and Caulfield 2021) and traffic congestion (Lu et al 2020;Zhao et al 2021).…”