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Path Tracking and Handling Stability Control Strategy With Collision Avoidance for the Autonomous Vehicle Under Extreme Conditions

机译:基于极端条件下自动车辆的碰撞避免碰撞的路径跟踪和处理稳定性控制策略

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摘要

A novel control strategy is proposed for the autonomous vehicle equipped with the front and rear independent steering systems to enhance the capability of collision avoidance and improve path tracking and handling stability under critical maneuvers. The novel control system includes a path replanning controller, a path tracking controller, and a stability controller. The path replanning controller is designed to generate a collision-free trajectory by optimizing a cost function. The cost function can be updated quickly and iteratively, according to the dynamic fitting matrix and measurement signals. The path tracking controller and the stability controller with considering multi-constraints are designed to generate the steering angle of the front wheel and the rear wheel, respectively, which improve the ability of path tracking and handling stability of the autonomous vehicle under extreme conditions. The real-time effectiveness of the proposed control strategy is verified and evaluated in Hardware-in-the-loop (HIL) simulation environment. The function of collision avoidance of the control algorithm is verified in the scenario of the preset obstacle artificially on the globally planned path. The proposed control strategy, presents superior performance against two other control strategies based on model predictive control algorithm, and also exhibits satisfactory performance in terms of path tracking as well as handling stability of the autonomous vehicle.
机译:提出了一种新颖的控制策略,为配备前后独立转向系统的自主车辆,提高临界行动下的碰撞避免和改善路径跟踪和处理稳定性的能力。新颖的控制系统包括路径复制控制器,路径跟踪控制器和稳定控制器。路径复制控制器旨在通过优化成本函数来生成无碰撞轨迹。根据动态拟合矩阵和测量信号,可以快速且迭代地更新成本函数。考虑多约束的路径跟踪控制器和稳定控制器分别设计成分别产生前轮和后轮的转向角,这提高了在极端条件下自主车辆的路径跟踪和处理稳定性的能力。验证了所提出的控制策略的实时效果,并在硬件循环(HIL)仿真环境中进行了验证和评估。在全局计划路径上人工的预设障碍物的场景中验证了控制算法的碰撞避免的函数。所提出的控制策略,对基于模型预测控制算法的另外两个控制策略具有卓越的性能,并且在路径跟踪方面也表现出令人满意的性能,以及自主车辆的稳定性。

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