Last Mile Passenger and Freight Synergistic and Mobile Distribution via Modular Autonomous Vehicles

As community logistics services and personal delivery demands grow rapidly, improving logistics efficiency has become a vital research focus. Considering the need for multi-partition joint distribution, we propose a solution utilizing modular autonomous vehicles (MAVs) that offer diverse transportation functions. First, we design a Passenger and Freight Collaborative Transportation System based on Modular Public Transportation Services (PFCTS-MPTS) and define the operation as a Multi-partition Pickup and Delivery Problem (MPPDP), which is modeled as a multi-objective mixed-integer nonlinear programming problem aimed at optimizing system operating costs and service efficiency. We propose a tailored heuristic framework consisting of three sequential algorithms to solve MPPDP, which can effectively address the impact of temporary demands on operation strategy and efficiently repair and optimize feasible solutions. A numerical study conducted in the Chengdu Baifo community demonstrated that the heuristic framework outperforms ALNS algorithms in solving MPPDP. Furthermore, by comparing it with benchmark strategies, we verified the advantages of PFCTS-MPTS in reducing operating costs and enhancing passenger and freight satisfaction. We also provided suggestions for operators on MAV type selection and order rule design based on sensitivity analysis to reduce operating costs.