The Potential Field (PF)-based path planning method is widely adopted for autonomous vehicles (AVs) due to its real-time efficiency and simplicity. PF often creates a rigid road boundary, and while this ensures that the ego vehicle consistently operates within the confines of the road, it also brings a lurking peril in emergency scenarios. If nearby vehicles suddenly switch lanes, the AV has to veer off and brake to evade a collision, leading to the "blind alley" effect. In such a situation, the vehicle can become trapped or confused by the conflicting forces from the obstacle vehicle PF and road boundary PF, often resulting in indecision or erratic behavior, even crashes. To address the above-mentioned challenges, this research introduces an Emergency-Stopping Path Planning (ESPP) that incorporates an adaptive PF (APF) and a clothoid curve for urgent evasion. First, we design an emergency triggering estimation to detect the "blind alley" problem by analyzing the PF distribution. Second, we regionalize the driving scene to search the optimal breach point on the road PF and the final stopping point for the vehicle by considering the possible motion range of the obstacle. Finally, we use the optimized clothoid curve to fit these calculated points under vehicle dynamics constraints to generate a smooth emergency avoidance path. The proposed ESPP-based APF method was evaluated by conducting the co-simulation between MATLAB/Simulink and CarSim Simulator in a freeway scene. The simulation results reveal that the proposed method shows increased performance in emergency collision avoidance and renders the vehicle safer, in which the duration of wheel slip is 61.9% shorter, and the maximum steering angle amplitude is 76.9% lower than other potential field-based methods.

翻译：摘要：基于势场的路径规划方法因其实时高效和简洁性而被广泛应用于自动驾驶车辆。势场常构建刚性道路边界，这虽能确保本车始终在道路范围内运行，但在紧急场景中暗藏隐患。当邻近车辆突然变道时，自动驾驶车辆必须偏转方向并制动以避免碰撞，这会导致"死胡同"效应。在此情况下，车辆因障碍物势场与道路边界势场的矛盾作用力而陷入困境或发生混乱，常引发决策犹豫或异常行为，甚至导致碰撞事故。针对上述挑战，本研究提出一种融合自适应势场与回旋曲线的应急停车路径规划（ESPP）方法。首先，通过分析势场分布设计紧急触发机制以检测"死胡同"问题；其次，对驾驶场景进行区域划分，综合考虑障碍物可能的运动范围，在道路势场中搜索最优突破点及车辆最终停车点；最后，利用优化回旋曲线在车辆动力学约束下拟合这些计算点，生成平滑的紧急避障路径。通过MATLAB/Simulink与CarSim模拟器在高速公路场景中的联合仿真，对所提出的基于ESPP的自适应势场方法进行评估。仿真结果表明，该方法在紧急避障安全性方面表现更优，与其他基于势场的方法相比，车轮滑移持续时间缩短61.9%，最大转向角幅度降低76.9%。