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车辆高速行驶自动变道避撞的纵向和横向控制策略。

Longitudinal and Lateral Control Strategies for Automatic Lane Change to Avoid Collision in Vehicle High-Speed Driving.

机构信息

Key Laboratory of Advanced Manufacturing Technology for Automobile Parts, Ministry of Education, Chongqing University of Technology, Chongqing 401320, China.

Chongqing Tsingshan Industrial, Chongqing 402760, China.

出版信息

Sensors (Basel). 2023 Jun 2;23(11):5301. doi: 10.3390/s23115301.

Abstract

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.

摘要

建立车辆粒子模型,对比分析三种不同避撞方法的有效性。结果表明,在车辆高速紧急避撞时,换道避撞比刹车避撞所需的纵向距离更小,更接近换道与刹车联合避撞的情况。基于此,提出一种双层控制策略,用于高速换道时避撞。比较分析三种多项式参考轨迹后,选择五次多项式作为参考路径。采用多目标优化模型预测控制跟踪横向位移,优化目标为最小化横向位置偏差、横摆率跟踪偏差和控制增量。较低的纵向速度跟踪控制策略是控制车辆的驱动系统和制动系统以跟踪预期速度。最后,验证了车辆在 120km/h 时的换道条件和其他速度条件。结果表明,控制策略可以很好地跟踪纵向和横向轨迹,实现有效的换道和避撞。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d612/10256023/9873cb41c111/sensors-23-05301-g001.jpg

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