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基于改进动态窗口法的离轴式全拖挂车辆主动避障OA

Active obstacle avoidance based on an improved dynamic window approach for off-axis full trailer vehicles

中文摘要英文摘要

针对普通乘用车的局部规划算法无法充分考虑整个拖挂系统,从而导致全拖挂车辆存在高碰撞风险的问题,提出一种针对离轴式全拖挂系统的改进动态窗口法(DWA),以实现无人全拖挂系统在非结构化道路下的主动避障.对牵引车速度进行采样,构成速度矢量空间,并根据系统约束和采样值,借助系统运动学模型预测两车体的运动轨迹;引入与目标点位置相关的子评价函数,提出一种符合全拖挂系统的评价函数;根据评价函数选择最优速度,确保系统安全抵达目标点.实验表明:所提方法在避障任务中具有可靠的安全性,在实车实验中,牵引车到障碍物边界的最小距离为0.83 m,全拖挂车辆到障碍物边界的最小距离为0.89 m.

Full trailers are at a significant risk of collision since the local planning algorithm for regular passenger cars does not completely account for the entire trailer system.To address this issue,a refined dynamic window approach(DWA)is proposed specifically for off-axis full trailer systems to enable proactive obstacle avoidance for unmanned full trailer systems on unstructured roads.Initially,the sampling of the towing vehicle's speed constructs a velocity vector space.The motion paths of both vehicles are then forecasted using the kinematic model of the system and the data that were sampled.Subsequently,introducing sub-cost functions related to the target point's position,an evaluation function tailored to the trailer system is proposed.Finally,the optimal velocity is selected based on the evaluation function to ensure the system safely reaches the target point.Experimental results demonstrate the method's reliable safety in obstacle avoidance tasks,with a minimum distance of 0.83 meters between the towing vehicle and obstacle boundaries in real vehicle experiments,and 0.89 meters for the full trailer from obstacle boundaries.

胡丹丹;赵金聚;牛国臣

中国民航大学 机器人研究所,天津 300300中国民航大学 机器人研究所,天津 300300中国民航大学 机器人研究所,天津 300300||民航智慧机场理论与系统重点实验室,天津 300300

信息技术与安全科学

全拖挂车辆动态窗口法非结构化道路主动避障运动学模型

full trailer vehicledynamic window approachunstructured roadactive obstacle avoidancekinematic model

《北京航空航天大学学报》 2026 (2)

415-425,11

国家自然科学基金(U2333205)中央高校基本科研业务费专项资金(3122023PY04) National Natural Science Foundation of China(U2333205)The Fundamental Research Funds for the Central Universities(3122023PY04)

10.13700/j.bh.1001-5965.2024.0404

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