Optimizing a modular autonomous vehicle hub-and-spoke public transportation system

Abstract

Modular autonomous vehicle (MAV), as a novel mode of public transportation, is anticipated to reshape the next generation of transportation systems, with the potential to adapt to diverse travel demand patterns in urban areas. In this study, we consider a MAV hub-and-spoke public transportation system (MAV-HSPTS). Each MAV can operate independently for first-mile/last-mile transport of passengers. Multiple MAVs can assemble into a modular bus, operating synchronously on mainline corridors with predetermined routes, stations, and timetables. We formulate a MAV routing, scheduling and repositioning model in a rolling horizon framework to capture the operation of the system. A heuristic algorithm that assigns passenger requests to MAVs is developed to reduce the computation time. The model and solution algorithm are evaluated on a bus transit corridor in Shanghai, China. Results demonstrate that the MAV service can reduce passenger travel time by over 20 % compared to conventional bus service, and over 90 % of the passengers could benefit from the convenience of in-bus transfers. MAV reposition proves to be an effective method to reduce the operational costs, especially in scenarios with imbalanced demand distribution.