用时变势场统一自动驾驶车辆的决策与轨迹规划
Unifying Decision-Making and Trajectory-Planning in Unsignalized Intersections Using Time-Varying Potential Fields
- 基于有限时域最优控制，引入时变人工势场建模
- 通过短时预测和冲突区占用系数避免碰撞
- 适合复杂无信号交叉口的多车协同场景
本文提出一种新型框架，用于在无信号交叉口对自动驾驶车辆实现决策与轨迹规划的融合。该方法采用有限时域最优控制问题（FHOCP），结合时变人工势场（TV-APF）。通过短时域运动预测和专用的冲突区占用系数，框架在FHOCP中有效考虑潜在碰撞风险。所提方法成功实现了决策与轨迹规划的统一，确保生成可行且安全的参考轨迹。在多车交通场景下的仿真结果验证了该方法的有效性。
原文摘要 · Abstract (English)
This paper presents a novel framework for integrated Decision-Making (DM) and Trajectory Planning (TP) for automated vehicles at unsignalized intersections. The approach leverages a Finite Horizon Optimal Control Problem (FHOCP) that employs Time-Varying Artificial Potential Fields (TV-APF). By utilizing short-horizon motion prediction and a dedicated conflict-zone occupancy coefficient, the framework suitably accounts for potential collisions within the FHOCP. The proposed method effectively unifies DM and TP, ensuring the generation of a feasible and safe reference trajectory. Simulation results in multi-vehicle traffic scenarios demonstrate the effectiveness of the approach.
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