Uncovering mode and parking preferences in the era of autonomous vehicles

This study proposes a joint model for transport mode choice and parking strategy in dense urban environments, incorporating emerging scenarios derived from the introduction of autonomous vehicles, both private and shared. Based on a stated preference survey and a hybrid approach with latent variables, the factors that influence user decisions are analysed, considering traditional observable attributes (cost, travel time, parking search time) and attitudinal constructs (technological acceptance, perceived sustainability). The results show that cost and time remain key determinants, but new relevant variables emerge, such as recovery time and preferences for unconventional parking strategies. In particular, the model reveals that users with greater acceptance of AVs are more likely to prefer strategies such as returning the vehicle to the home or dropping off without parking. These findings provide valuable evidence for urban mobility planning and policy design that promotes efficient use of space and the transition to more sustainable forms of transport. The model developed allows for the anticipation of technology adoption scenarios and the targeting of differentiated strategies according to user profiles • Joint hybrid model integrating mode and parking choices under AV scenarios. • Inclusion of recovery time as a behavioural component of the trip chain. • Latent variable captures predisposition toward autonomous driving technologies. • Findings reveal differentiated user responses based on attitudes and technology affinity. • Policy insights for efficient and sustainable urban parking management.