Both emergency braking and active steering are possible choices for collision avoidance manoeuvres, and any obstacle avoidance strategy aims to design a control algorithm preventing accidents. However, the real-time path needs to consider the motion state of surrounding participants on the road. This work presents a collision avoidance algorithm containing the path-planning and the tracking controller. Firstly, the lateral lane-changing spacing model and the longitudinal braking distance model are presented, describing the vehicle to reactively process dynamic scenarios in real environments. Then, we introduce the safety distance into the artificial potential field algorithm (APF), thereby generating a safe path in a simulated traffic scene. Redesigning the influence range of obstacles based on the collision areas and corresponding safety distance compared with the classic APF. Besides, based on the threat level, the repulsion is divided into the force of the position repulsion and the speed repulsion. The former is related to the relative position and prevents the vehicle from approaching the obstacle. The latter is opposite to the relative speed vector and decelerates the ego vehicle. Simultaneously, the attraction is improved to apply a dynamic environment. Finally, we design a model predictive control (MPC) to track the lateral motion through steering angle and a Fuzzy-PID control to track the longitudinal speed, turning the planned path into an actual trajectory with stable vehicle dynamics. To verify the performance of the proposed method, three cases are simulated to obtain the vehicle responding curves. The simulation results prove that the active collision avoidance algorithm can generate a safe path with comfort and stability.

紧急制动和主动转向都是避免碰撞行为的可能选择，并且任何避障策略都旨在设计一种预防事故的控制算法。但是，实时路径需要考虑周围参与者在路上的运动状态。这项工作提出了一种避免碰撞的算法，其中包含路径规划和跟踪控制器。首先，提出了横向变道间距模型和纵向制动距离模型，描述了车辆在实际环境中对动态场景进行反应性处理的过程。然后，我们将安全距离引入人工势场算法（APF）中，从而在模拟交通场景中生成安全路径。与传统的APF相比，根据碰撞区域和相应的安全距离重新设计障碍物的影响范围。此外，根据威胁程度，将排斥分为位置排斥力和速度排斥力。前者与相对位置有关，可防止车辆接近障碍物。后者与相对速度矢量相反并且使自我车辆减速。同时，吸引力被改善以应用动态环境。最后，我们设计了模型预测控制（MPC）以通过转向角跟踪横向运动，并设计了Fuzzy-PID控件以跟踪纵向速度，从而将计划路径转变为具有稳定车辆动力学的实际轨迹。为了验证所提出方法的性能，模拟了三种情况以获得车辆响应曲线。仿真结果表明，主动防撞算法能够产生舒适，稳定的安全路径。