基于V2X的协同自适应巡航控制的设计与实现

Yangquan Sun, Ping Wang, Fuqiang Liu
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引用次数: 1

摘要

基于V2X通信的协同驾驶因其在提高道路交通系统安全性和效率方面的巨大潜力而受到广泛研究。在乘客舒适度约束下,采用协同自适应巡航控制(CACC)算法对车辆的安全性和限速进行优化。在一个排中,横向控制器和纵向控制器按照模型预测控制(MPC)框架进行设计和实现。控制算法以减小跟踪误差为目标,将系统的跟踪控制作为一个非线性问题,采用粒子群优化算法进行求解。本文对该算法在不同场景下进行了仿真,仿真结果表明,该控制器能有效提高CACC系统的可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design and Implementation of Cooperative Adaptive Cruise Control based on V2X
Cooperative driving based on V2X communication has been widely studied for its great potential in improving the safety and efficiency of road transportation systems. Under the constraints of passenger comfort, the safety and speed limit of the vehicles can be optimized by the cooperative adaptive cruise control (CACC) algorithm. Within a platoon, the lateral controller and the longitudinal controller are designed and implemented following the model predictive control (MPC) framework. The goal of the control algorithm is to reduce the tracking error, so we formulate the tracking control of the system as a nonlinear problem and solve it by the particle swarm optimization (PSO) algorithm. This paper simulates the proposed algorithm in different scenes, and the simulation results show that the controllers can improve the reliability of the CACC system effectively.
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