Paving the way for autonomous Vehicles: Understanding autonomous vehicle adoption and vehicle fuel choice under user heterogeneity

Vehicle automation, along with vehicle electrification and shared mobility, may transform the existing transportation if they are handled properly. However, they may create unintended consequences if the current market dominance of fossil fuel and privately-owned vehicles persists, and travel patterns and transportation policies remain unchanged. The extent of these potential benefits and unintended consequences depends on the expected AV adoption process, people's preferred vehicle powertrain, and AV-related policy and infrastructural support. This paper seeks to understand the impacts of attitudinal factors and roadway designs on people's intention to use AVs and to purchase battery-electric AVs (EAVs) and gasoline-powered AVs (GAVs) under travel and user heterogeneity. Fourteen latent attitudinal factors related to the perceptions and attitudes towards AV and EV technologies, driving, the environment, and personal innovativeness were considered. An EAV-enabled urban design environments were created, featuring dedicated AV lanes, wireless charging for EAVs, and AV pick-up/drop-off zones. Using a stated preference survey data of over 1300 responses in the U.S., Multiple Indicators and Multiple Causes models are estimated to understand the relationship among various latent variables and capture heterogeneities within the population based on their sociodemographic and behavioral characteristics. The model estimation results show that the respondents’ perception of AVs and EAVs advantages, road safety improvement potential, compatibility with their lifestyles and travel needs, and their attitudes towards driving are key factors of their intention to use AVs and purchase EAVs. Furthermore, some segments of the population based on their sociodemographic and travel behavior characteristics are more likely to have a higher intention to use AVs and buy EAVs. The model estimation results and study insights can be used by policymakers to develop road network design guidelines and policies to nudge consumers towards more sustainable transportation options, minimize the unintended consequences of vehicle automation, and maximize its benefits.