Bus-Drone Collaborative Transportation in An Integrated Passenger-Cargo-Postal System

In response to the national passenger-freight-postal integration strategy and address “last mile delivery” challenges in rural logistics, this paper proposes a demand-responsive bus and drone collaborative transportation scheduling problem for rural passenger-cargo-postal integration. In the context of coexisting multi-origin to multi-destination passenger transportation demands and single-origin to multi-destination freight delivery demands, a mixed-integer linear programming model is built to minimize the total transportation cost including fixed vehicle costs, variable operating costs, and passenger in-vehicle travel time costs. The model considers constraints such as passenger boarding time windows, freight delivery time deadlines, bus capacity limits, and bus-drone coordination. It is designed to make scheduling decisions for the integrated passenger-cargo-postal transportation bus and its onboard drones. Furthermore, Based on an analysis of the problem’s characteristics, a more compact mathematical optimization model is constructed using a more streamlined variable definition approach. Finally, a numerical analysis is conducted using Bandong Town, Minqing County, Fujian Province, as a case study. Results show that the compact model outperforms the original in both solution speed and quality. Furthermore, impact analyses examine the impacts of of passenger-freight integration, drone coordination, and passenger mid-route boarding and alighting, along with a sensitivity analysis of passenger in-vehicle time coefficients, reveal that the proposed demand-responsive integrated passenger-cargo-postal bus-drone collaborative transportation can complete freight delivery tasks while ensuring passenger ride satisfaction. It also improves transportation efficiency and reduces transportation costs, representing a promising integrated passenger-freight transportation mode.