Integrated Unmanned Aerial Vehicles and Public Buses for Parcel Delivery in Urban Area

Abstract

<p>Deploying Unmanned Aerial Vehicles (UAVs) for parcel delivery in urban areas offers faster, more flexible, and cost-effective services while reducing traffic congestion, environmental impact, and improving accessibility. However, UAV efficiency is constrained by limited flight range and battery life, posing challenges in covering large urban areas. Leveraging the dense urban bus networks and the substantial number of buses in operation presents a novel solution: integrating UAVs with public buses. In this approach, buses act as mobile charging stations, enabling en-route UAV recharging and facilitating ride share with buses to enhance delivery efficiency. To optimize UAV routing and recharging schedules, we propose a Mixed Integer Programming (MIP) model. Due to the model’s complexity, an Adaptive Large Neighborhood Search (ALNS) heuristic algorithm is employed for efficient problem-solving. Numerical experiments on varying scales show that for small instances, our ALNS heuristic matches Gurobi's optimal solutions in less time. For larger instances, where Gurobi provides only feasible lower bounds within limited time, our ALNS heuristic delivers superior solutions faster. Real-world experiments in Shenzhen’s Luohu district further validate the effectiveness of the bus-UAV integration. Compared to UAV-only delivery, our approach reduces average costs by up to 29.53%, and by 18.18% in average compared to charging station-based en-route recharging, demonstrating significant operational advantages.<br></p>