一种面向时空同步约束的车机协同配送方法、系统及介质
By constructing a vehicle-machine collaborative topology network and a drone power consumption model, and combining an adaptive large neighborhood search algorithm and heuristic dynamic scheduling, the spatiotemporal synchronization problem of the vehicle-machine collaborative delivery system in a dynamic environment is solved, thereby improving the robustness and execution success rate of the system.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHANDONG UNIV OF SCI & TECH
- Filing Date
- 2026-05-19
- Publication Date
- 2026-07-17
AI Technical Summary
Traditional vehicle-machine collaborative delivery systems face challenges in spatiotemporal synchronization under dynamic environments, resulting in poor robustness and difficulty in achieving global search accuracy under complex constraints. Furthermore, insufficient prediction of drone power consumption leads to risks of idling and range mismatch.
A vehicle-machine collaborative topology network is constructed. Combined with the power consumption model of the UAV, an adaptive large neighborhood search algorithm is used for global path search. A heuristic dynamic scheduling engine is used to verify physical constraints and correct spatiotemporal decoupling, and generate vehicle-machine collaborative target scheduling instructions.
It significantly improves the robustness and success rate of the vehicle-machine collaborative delivery system in dynamic environments, ensures the economy and physical feasibility of route planning, and avoids the risks of idling and range mismatch.
Smart Images
Figure CN122222513B_ABST