{\sf TriDeliver}: Cooperative Air-Ground Instant Delivery with UAVs, Couriers, and Crowdsourced Ground Vehicles
2026-04-10 • Robotics
RoboticsHuman-Computer Interaction
AI summaryⓘ
The authors present TriDeliver, a system that combines human couriers, drones (UAVs), and crowdsourced ground vehicles to make instant delivery faster and cheaper. They use a method called Transfer Learning to teach drones and ground vehicles based on how human couriers deliver parcels, improving scheduling and coordination. Tested on a real dataset, TriDeliver significantly cut delivery costs and time compared to previous methods that only used drones and couriers. It also reduced how much crowdsourced vehicles were disrupted in their normal tasks.
instant deliveryUnmanned Aerial Vehicles (UAVs)crowdsourced vehiclesTransfer Learninghierarchical cooperationparcel schedulingdelivery costdelivery timeneural networks
Authors
Junhui Gao, Yan Pan, Qianru Wang, Wenzhe Hou, Yiqin Deng, Liangliang Jiang, Yuguang Fang
Abstract
Instant delivery, shipping items before critical deadlines, is essential in daily life. While multiple delivery agents, such as couriers, Unmanned Aerial Vehicles (UAVs), and crowdsourced agents, have been widely employed, each of them faces inherent limitations (e.g., low efficiency/labor shortages, flight control, and dynamic capabilities, respectively), preventing them from meeting the surging demands alone. This paper proposes {\sf TriDeliver}, the first hierarchical cooperative framework, integrating human couriers, UAVs, and crowdsourced ground vehicles (GVs) for efficient instant delivery. To obtain the initial scheduling knowledge for GVs and UAVs as well as improve the cooperative delivery performance, we design a Transfer Learning (TL)-based algorithm to extract delivery knowledge from couriers' behavioral history and transfer their knowledge to UAVs and GVs with fine-tunings, which is then used to dispatch parcels for efficient delivery. Evaluated on one-month real-world trajectory and delivery datasets, it has been demonstrated that 1) by integrating couriers, UAVs, and crowdsourced GVs, {\sf TriDeliver} reduces the delivery cost by $65.8\%$ versus state-of-the-art cooperative delivery by UAVs and couriers; 2) {\sf TriDeliver} achieves further improvements in terms of delivery time ($-17.7\%$), delivery cost ($-9.8\%$), and impacts on original tasks of crowdsourced GVs ($-43.6\%$), even with the representation of the transferred knowledge by simple neural networks, respectively.