Pioneering Cooperative Air-Ground Instant Delivery Using UAVs and Crowdsourced Couriers
Instant delivery, which has a strict time limit, has become a fundamental service in modern cities. Increasing demands and labor shortages make efficient instant delivery more challenging. Recently, the industry has recruited Unmanned Aerial Vehicles (UAVs) and part-time couriers to address this critical issue. However, the inherent delivery ability of crowdsourced couriers and the limited battery capacity of UAVs make them hard to solely meet the rapidly increasing instant delivery demands. Therefore, this paper proposes the first air-ground cooperative UAV and Courier Delivery paradigm, called UCD, to develop an optimal courier recruitment plan and assignment of instant delivery tasks for UAVs and couriers. In the UCD paradigm, courier and UAV delivery models are introduced, and a recruitment plan that considers both delivery demand and courier availability is designed. With this foundation, a data-driven algorithm is proposed to optimize delivery task assignments, maximizing the flexibility of UAVs and the capacity of couriers. Comprehensive evaluations are conducted on multiple long-term real-world datasets to demonstrate the superior performance of UCD.
Authors
- Jiashun Duan (ORCID: https://orcid.org/0009-0008-0151-8633)
- Yujiao Hu (ORCID: https://orcid.org/0000-0002-2271-1810)
- Yunji Liang (ORCID: https://orcid.org/0000-0002-8381-8187)
- Yan Pan (ORCID: https://orcid.org/0000-0001-8527-6134)
- Bin Guo (ORCID: https://orcid.org/0000-0001-6097-2467)
- Junhui Gao
- Juan Shi (ORCID: https://orcid.org/0000-0001-6410-398X)
Institutions
- National University of Defense Technology (CN)
- Northwestern Polytechnical University (CN)
- Air Force Engineering University (CN)
- Purple Mountain Laboratories (CN)
Publication Details
- Journal
- Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies
- Published
- 2024-11-21
- DOI
- https://doi.org/10.1145/3699722
- Citations
- 6
- Primary Topic
- UAV Applications and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 7.79