一体式车辆避撞轨迹规划与跟踪控制

为提升复杂交通环境中智能车辆的避撞能力，将路径规划、速度规划及跟踪控制整合为一个优化问题，提出一种基于模型预测控制(MPC)的一体式车辆避撞轨迹规划和跟踪控制方法。首先，分析实际交通环境中的避撞场景，将智能车辆的避撞控制问题转化为多约束优化问题；其次，搭建7DOF(七自由度)车辆动力学模型和复合滑移工况的UniTire轮胎模型设计MPC控制器；再次，针对变速控制问题中传统基于时域预测模型的MPC控制方法无法在预测时域中实现车辆空间和位姿约束的问题，设计了基于空间域预测模型的MPC控制器；最后，基于Matlab和CarSim联合仿真平台设计了不同避撞场景验证所提方法，并与现有基于恒速假设的一体式避撞控制方法进行对比。仿真结果表明：所提方法能够充分发挥车辆的机动性能，解决现有一体式控制方法在复杂环境中避撞失败的问题，并保证避撞过程稳定和轨迹平滑。

Integrated Control of Trajectory Planning and Tracking for Vehicle Collision Avoidance

To improve the collision avoidance ability of intelligent vehicles in complex traffic environments, the pathplanning, speed planning, and tracking control are integrated into one optimization problem, and an integrated controlmethod of trajectory planning and tracking for vehicle collision avoidance based on model predictive control (MPC) isproposed. Firstly, the collision avoidance scene in the real traffic environment is analyzed, and the collision avoidancecontrol problem of intelligent vehicles is transformed into a multi-constraint optimization problem. Secondly, a 7DOFvehicle dynamic model and a UniTire model with combined slip conditions are established for MPC controller design.Thirdly, to solve the problem that, in the variable speed control problem, the traditional MPC based on the time-domainprediction model cannot accurately express the spatial and posture constraints of the vehicle over the predictionhorizon, an MPC controller based on a spatial-domain prediction model is designed. Finally, based on the co-simulationplatform of Matlab and CarSim, different collision avoidance scenarios are designed to verify the proposed method,and the existing integrated collision avoidance control method based on constant speed assumption is compared withthe proposed method. The simulation results show that the proposed method can make full use of the vehiclemaneuverability, solve the problem of collision avoidance failure of existing integrated control methods in complexenvironments, and ensure the stability of the collision avoidance process and smoothness of trajectory.