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<p>Four-wheel independent steering (4WIS) vehicles possess remarkable flexibility due to their multiple motion modes. However, efficiently allocating these motion modes to reach the destination under various operating conditions poses a significant challenge in trajectory planning. To address this issue, this study proposes a 4WIS vehicle trajectory planning method incorporating multiple motion mode sequence decision-making. The proposed method aims to simultaneously achieve optimal motion mode sequence decision-making and trajectory planning in diverse environments. Firstly, a multi-mode collaborative planning algorithm based on graph search is developed. This algorithm generates reasonable global paths by employing strategies such as multi-mode node expansion, optimal node selection, and goal node connection. Subsequently, the global path is segmented, and then the each path segment is optimized using the quadratic programming (QP) method. Finally, the trapezoidal velocity planning method is applied to the optimized path to generate the final trajectory. Simulations demonstrate that the proposed algorithm automatically determines an optimal sequence of motion modes while generating safe and smooth trajectories. Notably, in complex environments, the proposed method significantly enhances the vehicle’s trafficability.</p>

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A 4WIS Vehicle Trajectory Planning Approach Incorporating Multiple Motion Mode Sequence Decision-Making

  • 期刊论文

  • 发表日期：

    2026年1月13日

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  • Zeyu Yang,
  • Yuan Chang,
  • Yingjie Jin,
  • Mingyang Chen,
  • Manjiang Hu,
  • Yougang Bian,
  • Xiaoyan Peng

摘要

Four-wheel independent steering (4WIS) vehicles possess remarkable flexibility due to their multiple motion modes. However, efficiently allocating these motion modes to reach the destination under various operating conditions poses a significant challenge in trajectory planning. To address this issue, this study proposes a 4WIS vehicle trajectory planning method incorporating multiple motion mode sequence decision-making. The proposed method aims to simultaneously achieve optimal motion mode sequence decision-making and trajectory planning in diverse environments. Firstly, a multi-mode collaborative planning algorithm based on graph search is developed. This algorithm generates reasonable global paths by employing strategies such as multi-mode node expansion, optimal node selection, and goal node connection. Subsequently, the global path is segmented, and then the each path segment is optimized using the quadratic programming (QP) method. Finally, the trapezoidal velocity planning method is applied to the optimized path to generate the final trajectory. Simulations demonstrate that the proposed algorithm automatically determines an optimal sequence of motion modes while generating safe and smooth trajectories. Notably, in complex environments, the proposed method significantly enhances the vehicle’s trafficability.