基于微分平坦与MPC的智能车换道控制算法

Intelligent Car Lane Change Control Algorithm Based on Differential Flatness and MPC

为了提高智能车换道的安全性,提出了一种基于微分平坦理论与模型预测控制(MPC)算法相结合的智能车换道轨迹规划与跟踪算法。该算法利用约束求解得到基于sigmoid函数的优化路径;将其与多项式参数化时间函数作为平坦输出,利用微分平坦理论构造一个非线性性能指标函数并对其进行优化求解完成车速规划;从而实现对智能车辆路径-速度分解式的轨迹规划。利用动力学模型预测控制算法线上控制的优点,对智能车的车轮转向进行实时控制,使得车辆按照规划好的轨迹行驶完成换道。通过CarSim与MATLAB/Simulink的联合仿真,将提出的轨迹规划算法应用于车辆系统仿真软件中进行验证,结果表明该算法能够实现对智能车进行轨迹规划和跟踪控制,使其安全高效地换至目标车道。

In order to improve the safety of intelligent car lane change,an intelligent vehicle lane change trajectory planning and tracking algorithm based on differential flat theory and model predictive control(MPC) algorithm is proposed. The optimal path based on sigmoid function is obtained by using constraint solution. Taking the parametric time function and polynomial as flat output,a nonlinear performance index function is constructed by using the differential flatness theory and optimized to complete the speed planning. Thus,the path planning of intelligent vehicle path-velocity decomposition is realized. Using the advantages of the dynamic model predictive control algorithm,the real-time control of the wheel steering of the intelligent vehicle enables the vehicle to complete lane change according to the planned track. Through the joint simulation of CarSim and MATLAB/Simulink,the proposed trajectory planning algorithm is applied to the vehicle system simulation software for verification. The results show that this algorithm can achieve the trajectory planning and tracking control of intelligent vehicles,so that it can safely and efficiently switch to the target lane.