Optimal Design of a Hub-and-Spoke Transit Network with Autonomous Buses Considering Platooning

The ability of a hub-and-spoke network to aggregate passenger flows at hub nodes has made it an emerging trend in bus transit network design. Autonomous bus platoons with larger vehicle capacities are well suited for serving dense passenger demand, thereby enhancing economies of scale. However, the design of hub-and-spoke transit networks with autonomous bus platoons have not been fully explored. This paper focuses on a two-stage hybrid hub-and-spoke bus transit network design problem with autonomous bus platoons, where only the lead vehicle requires a driver, while following vehicles operate autonomously. The proposed network integrates inter-hub routes and regular routes. The solution framework consists of two main steps. First, a customized K-medoids clustering algorithm is proposed to identify hub stations in the network. Second, a bi-level optimization model is formulated to design the hybrid hub-and-spoke transit network with autonomous bus platoons and determine the route set as well as service frequencies, aiming to minimize costs for both passengers and operators. To solve large-scale problems in the real world, an efficient genetic algorithm-based framework is proposed with a route generation algorithm to produce the initial route set. Experiments conducted on the Mandl benchmark demonstrate the effectiveness of the proposed method. A case study in Xiong’an, China shows that, compared with the existing network, the hybrid hub-and-spoke network with autonomous bus platoons achieves reductions in total cost and passenger travel time by 12.87% and 8.66%, respectively. Additionally, the contribution of autonomous bus platoons to enhancing economies of scale is observed especially under high-demand scenarios.