Incorporating vehicle self-relocations and traveler activity chains in a bi-level model of optimal deployment of shared autonomous vehicles

The combination of autonomous vehicles (AVs) and free-floating car-sharing scheme is expected to deliver high potentials of both through effective AV self-relocations. Little research has been done on the deployment of shared AVs (SAVs) considering the interplays among SAV relocations, supply-demand dynamics, and travelers’ multi-modal multi-activity schedules. This study aims to propose a bi-level system optimal model inclusive of a new hub-based relocation strategy to moderate the supply and demand of SAVs. The lower-level captures travelers’ activity-travel scheduling behavior by an extended dynamic user equilibrium model and the upper-level determines the hub locations, fleet size, and initial distribution of SAVs. A heuristic algorithm based on Lagrangian relaxation is developed to solve the network design problem. Numerical examples demonstrate that SAV relocations can significantly influence travelers’ daily schedules and enhance mobility efficiency in the multi-modal transport system. We also find that the proposed hub-based relocation strategy outperforms two common SAV relocation strategies in the literature.