Modeling travelers’ joint car ownership and car type choice behavior : the role of autonomous vehicle safety-security perceptions

Abstract

Car ownership and car type choice are critical components of transportation planning, yet the interplay between these decisions and the impact of emerging vehicle technologies, such as autonomous vehicles (AVs), remain underexplored. As AVs become more prevalent, travelers’ perceptions and behaviors regarding their safety and security may affect their adoption. This study investigates how travelers’ risk perceptions (safety, security, and range anxiety) shape their joint decisions to own a car and select a vehicle type within a multimodal transportation system. We propose a discrete choice modeling-based equilibrium analysis framework that integrates a dogit model to capture captivity effects in car ownership decisions and a nested logit model to account for similarities among car types. The framework is formulated as a mathematical programming problem, ensuring solution existence and uniqueness. Numerical experiments on a toy network and a real-world case study reveal that reductions in travelers’ risk perceptions toward AVs lead to significant increases in AV adoption, highlighting the critical role of public trust in transitioning to AV-dominated markets. By explicitly linking risk perceptions to long-term transportation planning, this model equips policymakers with a tool to design strategies that address behavioral barriers to AV adoption while balancing efficiency and safety objectives.