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Different Control Algorithms for a Platoon of Autonomous Vehicles

机译:无人驾驶小车的不同控制算法

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This paper presents a concept of platoon movement of autonomous vehicles (smart cars). These vehicles have Adaptive or Advanced cruise control (ACC) system also called Intelligent cruise control (ICC) or Adaptive Intelligent cruise control (AICC) system. The vehicles are suitable to follow other vehicles on desired distance and to be organized in platoons. To perform a research on the control and stability of an AGV (Automated Guided Vehicles) string, we have developed a car-following model. To do this, first a single vehicle is modeled and since all cars in the platoon have the same dynamics, the single vehicle model is copied ten times to form model of platoon (string) with ten vehicles. To control this string, we have applied equal PID controllers to all vehicles, except the leading vehicle. These controllers try to keep the headway distance as constant as possible and the velocity error between subsequent vehicles - small. For control of vehicle with nonlinear dynamics combi-nation of feedforward control and feedback control approach is used. Feedforward control is based on the inverse model of nominal dynamics of the vehicle, and feedback PID control is designed based on the linearized model of the vehicle. For simulation and analysis of vehicle and platoon of vehicles – we have developed Matlab/Simulink models. Simulation results, discussions and conclusions are given at the end of the paper.
机译:本文提出了自动驾驶汽车(智能汽车)的排排运动概念。这些车辆具有自适应或高级巡航控制(ACC)系统,也称为智能巡航控制(ICC)或自适应智能巡航控制(AICC)系统。这些车辆适合跟随其他车辆行驶所需距离,并排成一排。为了对AGV(自动导引车)弦的控制和稳定性进行研究,我们开发了一个跟车模型。为此,首先要对单个车辆进行建模,并且由于排中的所有车辆都具有相同的动力学特性,因此将单个车辆模型复制十次以形成具有十个车辆的排(弦)模型。为了控制该字符串,我们对所有车辆(领先车辆除外)应用了相等的PID控制器。这些控制器试图使行进距离尽可能保持恒定,并保持后续车辆之间的速度误差很小。对于具有非线性动力学的车辆控制,使用前馈控制和反馈控制方法的组合。前馈控制基于车辆标称动力的逆模型,而反馈PID控制则基于车辆的线性化模型进行设计。为了对车辆和车辆排进行仿真和分析,我们开发了Matlab / Simulink模型。最后,给出了仿真结果,讨论和结论。

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