The vehicle particle model was built to compare and analyze the effectiveness of three different collision avoidance methods. The results show that during vehicle high-speed emergency collision avoidance, lane change collision avoidance requires a smaller longitudinal distance than braking collision avoidance and is closer to that with a combination of lane change and braking collision avoidance. Based on the above, a double-layer control strategy is proposed to avoid collision when vehicles change lanes at high speed. The quintic polynomial is chosen as the reference path after comparing and analyzing three polynomial reference trajectories. The multiobjective optimized model predictive control is used to track the lateral displacement, and the optimization objective is to minimize the lateral position deviation, yaw rate tracking deviation, and control increment. The lower longitudinal speed tracking control strategy is to control the vehicle drive system and brake system to track the expected speed. Finally, the lane changing conditions and other speed conditions of the vehicle at 120 km/h are verified. The results show that the control strategy can track the longitudinal and lateral trajectories well and achieve effective lane change and collision avoidance.

To improve the roll stability of semi-trailers, a robust model predictive controller (RMPC) is designed. To analysis the vehicle dynamic behaviour, a nonlinear seven-degree of freedom (7-DOF) vehicle model is defined. Based on the robust invariant set theory, and taking the uncertainty of the driver's driving behaviour into account, the maximal robust control invariant (RCI) set is calculated and its robustness is analysed. The N-step controllable sets of the vehicle are also solved. An anti-roll controller considering multiple constraints is designed based on the robust model predictive control theory. Simulation results show that the controller can keep the lateral load transfer rate within 0.7 and make the state variables converge. In addition, the controller can reduce the lateral acceleration by 50% in the step steering input test.

Autonomous driving technology in urban environments is a very important avenue of research. Notably, the question of how to plan safe lane-changing trajectories is a challenge in multi-vehicle traffic environments. In our research, three kinds of polynomial lane changing mathematical models were analyzed and compared. It was found that the fifth polynomial is the most suitable for lane changing trajectories; it is defined as a generalized lane-changing trajectory cluster, whereby the minimum lane change time is determined by the vehicle lateral stability threshold. Here, a collision avoidance algorithm is proposed to eliminate unsafe trajectories. Finally, the TOPSIS algorithm is used to solve the multi-objective optimization problem, and the optimal lane-changing expected trajectory is obtained from the safe trajectory cluster. The simulation results showed improvements in lane-changing efficiency of 6.67% and no collisions in the overtaking condition. In general, the proposed method of identifying the optimal lane changing trajectory can achieve safe, efficient and stable lane changing.

针对汽车弯道紧急制动避撞问题,提出了一种双层控制方法.上层控制器设计了弯道紧急制动策略,基于两车实际相对距离计算出增强型剩余碰撞时间模型,利用该模型确定制动阈值以及制动减速度;下层控制器为车辆逆动力学模型和车辆验证模型,通过PID控制器调节来提高验证模型的准确性,并基于模糊控制理论设计了横向稳定控制器;最后参照中国新车评价协会测试办法进行仿真验证,研究表明:自车在55 km/h时,制动结束后两车相对距离在1.5 m左右,带有稳定性控制车辆的质心侧偏角始终处于安全范围内,该策略能够实现弯道下车辆紧急制动.