矿用卡车无人驾驶车载决策系统  

Onboard Decision-making System of Unmanned Mine Truck

作　　者：王佳 黄佳德 刘智聪 黄鹏 吕亮 WANG Jia;HUANG Jiade;LIU Zhicong;HUANG Peng;LYU Liang(Zhuzhou CRRC Times Electric Co.,Ltd.,Zhuzhou,Hunan 412001,China)

机构地区：[1]株洲中车时代电气股份有限公司,湖南株洲412001

出　　处：《控制与信息技术》2022年第5期9-16,共8页CONTROL AND INFORMATION TECHNOLOGY

基　　金：国家重点研发计划(2021YFB2501802)。

摘　　要：目前国内外针对矿山场景下无人驾驶车载决策系统的研究仍处于初级阶段,研究重心大多放在全局规划调度上,而忽视了全局规划调度基础上的单车自主决策方法的研究。为进一步提升系统的安全性与作业效率,文章重点研究了车载决策系统单车自主决策方法下的行为决策和运动规划两大核心功能。行为决策包含驾驶模式与任务模式决策、碰撞预警与防护决策、故障分级与安全导向决策,文中采用基于双层有限状态机方法实现单车自主决策的防护判断,以提高车辆在矿山的“装、运、卸”全流程场景运行的安全性。运动规划包含速度规划和路径规划,文中采用基于时间最短、能耗最优的二次规划算法来求解速度规划,并采用基于特殊场景下的混合A*与曲线拟合算法以求解局部路径规划,在装卸载、泊车场景可以提升10%~20%的运行效率。该系统在中国北方某矿区历经了半年实车生产运营,结果表明,该系统可有效提高车辆运行效率。At present, the research on unmanned mine truck system on-board decision system in mine scenarios at home and abroad is still in the initial stage, and its research focus is mainly on global planning and scheduling to improve overall safety and efficiency of the system, while ignoring the research on the mine truck independent decision method based on the global planning and scheduling. In order to further improve the safety and efficiency of the system, this paper focuses on the two core functions of behavior decision-making and motion planning under the mining truck independent decision-making method of the vehicle decision-making system. Behavior decision includes driving mode and task mode decision, collision warning and protection decision, fault classification and safety oriented decision, based on the double layer limited state machine method to realize mine truck autonomous decision protection judgment, to ensure that the vehicle in the "loading, transportation, unloading" whole process scenario of mine to improve the safety of vehicle operation. Motion planning includes speed planning and path planning. This paper adopts the quadratic programming algorithm based on the shortest time and the optimal energy consumption to solve the speed planning, and adopts the hybrid A-star and curve fitting algorithm based on special scenarios to solve the local path planning, so that the operation efficiency can be improved by 10%~20% in the loading and unloading parking scenario. The system has been production and operation in a mining area in northern China for half a year. The real vehicle production and operation results show that the system can effectively improve the vehicle operation efficiency and safety ability to avoid obstacles.

关 键 词：决策系统 无人驾驶 行为决策 运动规划 单车决策 矿用卡车 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置] U471.1[自动化与计算机技术—控制科学与工程]