A real-time UAV delivery system considering dock selection and spatial conflict

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Hu, Ziyi, Cao, Yue, Li, Xinyu, Zhang, Xu, Zhang, Chuanke and Liu, Zhi (2025) A real-time UAV delivery system considering dock selection and spatial conflict. Expert Systems with Applications, 281. ISSN 0957-4174

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Abstract

The development of Unmanned Aerial Vehicle (UAV) has brought new vitality to logistics industry, especially for real-time delivery demand. Under real-time delivery model, the UAV transports parcel between docks (e.g., the designated location for UAV to drop off/pick up parcels), with vision that the fast response to demand is satisfied. Unlike traditional ground delivery services, the UAV model not only considers delivery cost, but also takes into account dock spatial conflicts during UAV takeoff and landing. Since the UAV delivery scheduling is an non-deterministic polynomial hard problem, the optimal solution is hard to obtain through off-the-shelf solvers within a limited response time under large-scale demand. Hence, we propose a real-time UAV delivery system, which provides the in-time UAV scheduling scheme under large-scale demand. In particular, the Ant Colony Algorithm and Q-value learning are utilized to select the optimal dock for UAV, so that the UAV flight time is reduced under spatial conflict avoidance. Besides, through solving the bi-level linear programming model, the optimal number of deployed docks and UAVs is determined, to reduce the delivery cost. Based on simulation experiments, our scheme outperforms other schemes on reducing UAV flight time and is robust to different geographical distribution of docks. The impact of spatial conflicts on UAV delivery is also reduced under our scheme.

Item Type: Article
Additional Information: Publisher Copyright: © 2025 Elsevier Ltd
Uncontrolled Keywords: delivery scheduling,real-time delivery,uav,engineering(all),computer science applications,artificial intelligence ,/dk/atira/pure/subjectarea/asjc/2200
Faculty \ School: Faculty of Science > School of Computing Sciences
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Depositing User: LivePure Connector
Date Deposited: 25 Jun 2025 15:30
Last Modified: 25 Jun 2025 15:30
URI: https://ueaeprints.uea.ac.uk/id/eprint/99721
DOI: 10.1016/j.eswa.2025.127498

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