Cooperative drone-based hitchhiking vehicle framework for last-mile logistics services: A case study for online food delivery scenarios

The rapid advancement of low-altitude technology has shown significant potential to revolutionize the traditional ground-based last-mile logistics services. However, technical and operational challenges (such as limitations on payload size and weight, as well as battery capacity restrictions) hinder the widespread adoption of drone-based logistics systems, which can be addressed by a cooperative vehicle-drone delivery approach. In view of this, we investigate the drone-vehicle cooperative delivery problem through a multi-layered architecture that formally synchronizes urban transit networks, drone distribution systems, and logistics operations. To be specific, we propose the drone hitchhiking last-mile delivery framework (DHLDF) to enhance urban last-mile logistics services. To facilitate the framework’s deployment, a decentralized agent-based heuristic is developed to operationalize the DHLDF through real-time spatio-temporal coordination. The proposed approach is validated through a high-fidelity simulation of Manhattan’s urban fabric, synthesizing real-world taxi trajectory datasets with commercial food-delivery demand. Experimental results demonstrate that DHLDF significantly enhances systemic throughput, achieving a 20.6% improvement in success rates and an 11.9% reduction in energy consumption compared to direct drone delivery by achieving higher drone turnover rates. Moreover, case studies conducted on real-world urban networks demonstrate the practical applicability of DHLDF in diverse last-mile delivery scenarios. These findings offer meaningful insights for policymakers and logistics managers regarding the operational efficiency, scalability, and adaptability of DHLDF to complex spatial-temporal demand patterns, highlighting its potential for real-world implementation.