智能汽车路径跟踪混合控制策略研究

针对传统单一控制算法无法有效协调智能汽车不同转向工况下横向控制性能要求的问题,根据智能汽车在高速和低速转向工况下呈现出的系统特性差异,设计了一种基于PID控制和模型预测控制的智能汽车路径跟踪混合控制策略。该控制策略在低速模式下采用PID控制,在高速模式下则采用模型预测控制,通过车辆速度确定路径跟踪控制模式,进而设计带稳定监督的控制模式切换机制,实现了横向控制系统的平滑切换。基于Carsim和MATLAB/Simulink仿真平台对所设计的智能汽车路径跟踪混合控制策略进行了仿真验证,在此基础上,进一步完成了实车试验。仿真和实车试验结果表明,所设计的混合控制策略能够保证智能汽车不同速度下的路径跟踪性能,具有较好的跟踪精度、实时性和车辆行驶稳定性。

Research on Hybrid Control Strategy for Intelligent Vehicle Path Tracking

In order to solve the problems of traditional single control algorithm might not effectively coordinate the lateral control performance requirements of intelligent vehicles under different steering conditions, a hybrid control strategy of intelligent vehicle path tracking was designed based on PID control and model predictive control by combining with the different system characteristics of intelligent vehicles under high-speed and low-speed steering conditions. The control strategy selected PID control in low-speed mode and model predictive control in high-speed mode, The path following control mode was determined by vehicle speed, and then a switching mechanism of control mode with stable supervision was designed to realize smooth switching of lateral control system. Based on Carsim and MATLAB/Simulink simulation platform, the hybrid control strategy of intelligent vehicle path tracking was simulated and verified. Then, the real vehicle tests were further completed. Simulation and real vehicle test results show that the designed hybrid control strategy may ensure the performance of the intelligent vehicle path tracking at different speeds, and has good tracking accuracy, real-time performance and vehicle running stability.