Dong Ding, Ye Hongtao, Luo Wenguang, Wen Jiayan, Huang Dan
School of Automation, Guangxi University of Science and Technology, Liuzhou 545036, China.
Guangxi Key Laboratory of Automobile Components and Vehicle Technology, Guangxi University of Science and Technology, Liuzhou 545036, China.
Sensors (Basel). 2024 Aug 12;24(16):5211. doi: 10.3390/s24165211.
In response to the fact that autonomous vehicles cannot avoid obstacles by emergency braking alone, this paper proposes an active collision avoidance method for autonomous vehicles based on model predictive control (MPC). The method includes trajectory tracking, adaptive cruise control (ACC), and active obstacle avoidance under high vehicle speed. Firstly, an MPC-based trajectory tracking controller is designed based on the vehicle dynamics model. Then, the MPC was combined with ACC to design the control strategies for vehicle braking to avoid collisions. Additionally, active steering for collision avoidance was developed based on the safety distance model. Finally, considering the distance between the vehicle and the obstacle and the relative speed, an obstacle avoidance function is constructed. A path planning controller based on nonlinear model predictive control (NMPC) is designed. In addition, the alternating direction multiplier method (ADMM) is used to accelerate the solution process and further ensure the safety of the obstacle avoidance process. The proposed algorithm is tested on the Simulink and CarSim co-simulation platform in both static and dynamic obstacle scenarios. Results show that the method effectively achieves collision avoidance through braking. It also demonstrates good stability and robustness in steering to avoid collisions at high speeds. The experiments confirm that the vehicle can return to the desired path after avoiding obstacles, verifying the effectiveness of the algorithm.
针对自动驾驶车辆无法仅通过紧急制动来避免障碍物这一情况，本文提出了一种基于模型预测控制（MPC）的自动驾驶车辆主动避撞方法。该方法包括轨迹跟踪、自适应巡航控制（ACC）以及高速行驶时的主动避障。首先，基于车辆动力学模型设计了一种基于MPC的轨迹跟踪控制器。然后，将MPC与ACC相结合来设计车辆制动以避免碰撞的控制策略。此外，基于安全距离模型开发了用于避撞的主动转向。最后，考虑车辆与障碍物之间的距离以及相对速度，构建了避障函数。设计了一种基于非线性模型预测控制（NMPC）的路径规划控制器。此外，采用交替方向乘子法（ADMM）来加速求解过程，并进一步确保避障过程的安全性。所提出的算法在Simulink和CarSim联合仿真平台上的静态和动态障碍物场景中进行了测试。结果表明，该方法通过制动有效地实现了避撞。在高速转向避撞时也表现出良好的稳定性和鲁棒性。实验证实车辆在避障后能够返回期望路径，验证了算法的有效性。
