非结构化狭窄环境下4WIS车辆动态轨迹优化

doi:10.3901/JME.260287

摘要/Abstract

摘要： 四轮独立转向(Four-wheel independent steering，4WIS)车辆具备卓越的机动性，能够在复杂环境中实现更灵活的运动控制。然而，现有轨迹规划方法尚未充分挖掘4WIS车辆的运动特性，并普遍采用固定数量的圆盘近似车辆轮廓实现避障约束，难以兼顾避障精度与计算效率，且对动态环境的适应能力不足。针对上述问题，提出一种面向非结构化狭窄环境4WIS车辆动态轨迹优化方法。首先，改进混合A^*算法，考虑4WIS车辆多种模式运动特性改进算法的节点扩展和代价函数，并设计航向角动态调整策略，提出自适应多圆盘碰撞检测方法，自适应调整碰撞检测模型以适应复杂环境，并提高算法搜索效率。其次，构建4WIS车辆轨迹优化模型，提出基于自适应多圆盘避障约束，基于不同路径点对应的碰撞检测模型构建行车走廊以线性化避障约束，提高算法在复杂环境下的求解成功率和计算效率。然后，针对动态环境轨迹规划问题，提出基于模糊动态窗口法的局部轨迹重规划方法，实现对动态障碍物或新增静态障碍物的避让。仿真试验表明所提算法能生成平滑无碰撞的运动轨迹，在复杂环境下相比传统混合A^*算法，成功率提高了11.25%，计算时间减少了27.64 s，显著提高了4WIS车辆在复杂场景中轨迹规划效率与安全性。

关键词: 四轮转向车辆, 轨迹优化, 混合A^*, 自适应多圆盘, 轨迹重规划

Abstract: Four-wheel independent steering(4WIS) vehicles possess outstanding maneuverability, enabling more flexible motion control in complex environments. However, existing trajectory planning methods have yet to fully exploit the motion characteristics of 4WIS vehicles. Most approaches approximate the vehicle contour using a fixed number of discs to impose obstacle avoidance constraints, which limits the balance between avoidance accuracy and computational efficiency and reduces adaptability to dynamic environments. To address these issues, this paper proposes a dynamic trajectory optimization method for 4WIS vehicles operating in unstructured and narrow environments. First, the hybrid A^* algorithm is enhanced by incorporating the multi-modal motion characteristics of 4WIS vehicles to improve node expansion and cost evaluation. A dynamic heading adjustment strategy is introduced, along with an adaptive multi-disc collision detection method that adjusts the collision model according to environmental complexity, thereby improving search efficiency. Next, a trajectory optimization model for 4WIS vehicles is constructed. An adaptive multi-disc obstacle avoidance constraint is proposed, and driving corridors are generated based on the collision detection model corresponding to each path point, enabling linearization of obstacle avoidance constraints and improving the solution success rate and computational efficiency in complex environments. Furthermore, to address trajectory planning in dynamic environments, a local trajectory replanning method based on a fuzzy dynamic window approach is proposed, enabling effective avoidance of dynamic obstacles and newly introduced static obstacles. Simulation results demonstrate that the proposed method can generate smooth, collision-free trajectories. Compared with the conventional hybrid A^* algorithm, the proposed method increases the planning success rate by 11.25% and reduces computation time by 27.64 s, significantly enhancing the trajectory planning efficiency and safety of 4WIS vehicles in complex scenarios.

Key words: four-wheel independent steering, trajectory optimization, hybrid A^*, adaptive multi-disc, trajectory replanning

中图分类号:

U469

姜小龙, 李洋, 滕景佳, 黄文杰, 秦洪懋, 胡满江, 李国法, 边有钢. 非结构化狭窄环境下4WIS车辆动态轨迹优化[J]. 机械工程学报, 2026, 62(8): 410-431.

JIANG Xiaolong, LI Yang, TENG Jingjia, HUANG Wenjie, QIN Hongmao, HU Manjiang, LI Guofa, BIAN Yougang. Dynamic Trajectory Optimization for 4WIS Vehicles in Unstructured Narrow Environments[J]. Journal of Mechanical Engineering, 2026, 62(8): 410-431.

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链接本文: http://www.cjmenet.com.cn/CN/10.3901/JME.260287

http://www.cjmenet.com.cn/CN/Y2026/V62/I8/410

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