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Lateral and Longitudinal Control Algorithms for Visual Platooning of Autonomous Vehicles

机译:自动车辆视觉排横向和纵向控制算法

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This paper describes lateral and longitudinal control algorithms when vision-based autonomous vehicles form a platoon by detecting a preceding one with a machine vision system. The visual platooning in this paper is an extension of the longitudinal control in ACC, and is featured by both the lateral and longitudinal control of following vehicles. The lateral control algorithm for a following vehicle uses a target point positioned on a preceding vehicle and captured in the field of view. When the target point is appropriately positioned, a following vehicle is guided as if it chased the target. The lateral control consists of the steps of target point detection, path generation, and lateral control calculation. A coefficient of a cubic curve that is defined with a target point and the current position of the following vehicle provides the steering angle. The longitudinal control algorithm of a vehicle is determined with a distance between a preceding vehicle and a following one. The feasibility of the algorithms is shown by simulation studies and experiments with indoor mobile robots and automated passenger cars on a test track.
机译:本文通过用机器视觉系统检测前一体,介绍基于视觉的自治车辆时横向和纵向控制算法。本文的视觉排列是ACC中的纵向控制的延伸,并且由以下车辆的横向和纵向控制具有延伸。下面的车辆的横向控制算法使用定位在前面的车辆上的目标点并在视野中捕获。当目标点适当地定位时,引导以下车辆,就像它追逐目标一样。横向控制包括目标点检测,路径生成和横向控制计算的步骤。用目标点和以下车辆的当前位置限定的立方曲线的系数提供了转向角。用前面的车辆和下面的车辆之间的距离确定车辆的纵向控制算法。通过在测试轨道上的室内移动机器人和自动乘用车的模拟研究和实验显示了算法的可行性。

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