Modeling Older Adults’ Motorized Travel Mode Choice with Autonomous Vehicles: Random-Parameter Logit Approach

Abstract

This study examines older adults' motorized travel mode choices in the context of autonomous mobility, with particular attention to how technology acceptance and digital competencies shape preferences for private autonomous vehicles (PAVs) and shared autonomous vehicles (SAVs). A mixed-mode stated-preference survey was conducted in Wuhan, China, in May 2022. The final sample included 734 respondents aged 60 years and above, each completing three choice tasks, yielding 2,202 observations across four alternatives: PAV, SAV, metro, and bus. A random-parameter logit model was estimated to capture preference heterogeneity. The results show significant random taste heterogeneity in travel cost, in-vehicle time, and walking/waiting time, with part of this heterogeneity associated with socioeconomic characteristics such as age, income, car ownership, and driving license status. Among technology acceptance constructs, attitude was positively associated with both PAV and SAV choice, perceived usefulness was positively related to SAV choice, while perceived ease of use showed a negative association with autonomous vehicle alternatives. Digital competency indicators had differentiated effects, with social and financial internet use being particularly relevant to SAV choice. Elasticity analysis further indicates that time components, especially in-vehicle time, are key determinants of older adults' autonomous mode selection. These findings provide evidence for age-friendly autonomous mobility strategies emphasizing reliability, reduced travel-time burdens, and inclusive digital support.