Reshaping Urban Logistics: Route Planning Strategies for Collaborative Delivery Using Autonomous Vehicles and Passenger-Freight Combined Buses

In recent years, the rapid growth of e-commerce has led to a surge in demand for urban logistics. The traditional truck-based delivery model, characterized by high energy consumption and limited delivery efficiency, is increasingly inadequate for urban express delivery requirements. This study proposes a collaborative delivery route planning model that integrates autonomous vehicles with passenger-freight combined buses to optimize urban express delivery routes, enhance delivery efficiency, and reduce logistics costs. Additionally, a single-parent genetic algorithm was developed for path optimization within this model. This algorithm evaluates delivery route quality by comprehensively considering factors such as delivery time, operational costs, and energy consumption. Finally, a case study conducted in Hanzhong City demonstrates that the collaborative delivery model, compared to the traditional truck-based delivery model, reduces operational costs for courier companies by Ɏ624.75, decreases travel distance by 13.48 kilometers, and increases daily net revenue for bus companies by Ɏ347.2. This study validates the efficiency and economic viability of the collaborative delivery model in modern urban logistics, providing robust support for optimizing urban delivery systems.