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An Online Path Planning Algorithm for Automated Vehicles for Slow Speed Maneuvering

机译:慢速机动车辆在线路径规划算法

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Today the level of automation of road vehicles increases due to the new requirements of the society. In the last century the main motivation was to make driving easier or more comfortable, nowadays lower fuel consumption, higher traffic safety and reduced environmental impact are in the focus of the developments. The improvement of automation will result a safer and environmental friendlier road transport.In automated vehicles a software does the driving tasks. It is a complex, multiple level controlling task which has several steps. An important step is, when the vehicle plans its own trajectory. The trajectories can also be meant aspects: it can mean the exact path and speed profile of the vehicle or it can mean the nodes on a traffic network where the vehicle should go.This paper presents the development of path planning algorithms. Based on the earlier offline path planning research this paper will present a basic online path planning algorithm. To reach the aim a map will be given as a 2204 × 1294 size matrix where the roads, the obstacles and the parking areas will be defined by different numbers. The map presents a smaller area of the campus of the Budapest University of Technology and Economics. The development, the testing and validation will be done in Prescan simulation environment. The aim is to make an algorithm which can modify the pre-planned path of the vehicle to avoid the collision with the LIDAR-sensed obstacles. The vehicle speed will be assumed slow enough to ignore the dynamical properties of the vehicle.
机译:今天,由于社会的新要求,公路车辆的自动化水平不断提高。在上个世纪,主要动机是使驾驶变得更轻松或更舒适,如今,降低油耗,提高交通安全性和减少对环境的影响成为发展的重点。自动化的改进将带来更安全,更环保的道路运输。在自动驾驶汽车中,软件可以完成驾驶任务。这是一个复杂的,多级控制任务,它包含多个步骤。重要的一步是,当车辆计划自己的轨迹时。轨迹也可以表示方面:可以表示车辆的确切路径和速度曲线,也可以表示车辆应去往的交通网络中的节点。本文介绍了路径规划算法的发展。在较早的离线路径规划研究的基础上,本文将提出一种基本的在线路径规划算法。为了达到这个目的,将以2204×1294大小的矩阵形式给出地图,其中道路,障碍物和停车区域将由不同的数字定义。该地图显示了布达佩斯科技经济大学校园的一小部分区域。开发,测试和验证将在Prescan仿真环境中完成。目的是提出一种算法,该算法可以修改车辆的预定路径,从而避免与LIDAR感应的障碍物发生碰撞。假定车速足够慢而忽略了车辆的动力特性。

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