一种无人驾驶车队调度方法、装置及电子设备

By employing global path planning and local optimization methods, the problem of low efficiency of unmanned vehicle fleets in complex port environments has been solved, achieving safe and efficient fleet scheduling. This method is applicable to various scenarios without the need for additional hardware facilities.

CN117133143BActive Publication Date: 2026-07-17BEIJING SENIOR SMART DRIVING TECHNOLOGY CO LTD

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
BEIJING SENIOR SMART DRIVING TECHNOLOGY CO LTD
Filing Date
2023-07-21
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Existing unmanned vehicle fleet dispatching technologies suffer from low efficiency and insufficient safety in complex port environments, are unable to adapt to various scenarios, and require additional hardware support.

Method used

A method combining global path planning and local optimization is adopted. Taking into account real-time vehicle information and external factors, the local task path of the vehicle is planned, and the safety and efficiency of the path are improved through optimization algorithms, avoiding the installation of additional hardware facilities.

Benefits of technology

It improves the overall efficiency and scheduling accuracy of autonomous vehicle fleets, is applicable to a variety of complex scenarios, and does not require additional traffic lights or isolation equipment, thus enhancing the system's flexibility and applicability.

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Abstract

本说明书实施例提供一种无人驾驶车队调度方法、装置及电子设备,所述方法包括:对目标区域的无人驾驶车队进行全局路径规划,得到全局路径规划结果;基于任务车辆的行驶信息和全局任务路径对应的参考信息,确定任务车辆的局部任务路径;基于局部任务路径的属性信息,优化局部任务路径,得到优化后的局部任务路径信息。根据本说明书实施例所述的无人驾驶车队调度方法,既能够对无人驾驶车队进行统一的全局路径规划,还能够结合车辆的实时行驶信息,综合兼顾多种外部因素,规划车队车辆行驶过程中的局部任务路径,并进行反向局部优化,可以在保证安全的同时有效提升无人驾驶车队的整体效率和调度准确度,且能够推广并应用于多种复杂场景。
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