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Vision Based Intelligent Vehicle Steering Control Using Single Camera for Automated Highway System

机译:基于视觉的智能车辆转向控制自动化公路系统

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Generally, stereoscope vision is used for guiding autonomous intelligent road vehicles, as image depth can be calculated easily. However, when one of the camera fails, it will advantages to have suitable guidance algorithm that can detect the lane marking using single camera. The primary objective of this work is to develop and implement control algorithms for identifying and guiding the intelligent road vehicle in the assigned lane using image-processing techniques, using single camera. It deals with dividing the video being taken by the camera, into several number of frames. Then, the obtained frames are processed using Image acquisition techniques in Matlab. It detects the lane to be followed through image processing, calculates the angle of movement required for the robot to stay in the assigned path and commands the steering system with appropriate control algorithms. The identification of lane is done using color detection and boundary marking techniques. The image initially undergoes Inverse Perspective Mapping (IPM) for viewing the 3-D space in a 2-dimensional array. Once the IPM of the acquired image undergoes lane detection algorithm, the angle of any curve in the lane is detected using angle detection module. The robot is also made to move at the center of the path using Fuzzy Logic algorithms, where it takes distance from the left detected edge as the input and outputs the angle to be moved by the robot to stay in the center. The developed algorithm has been tested using P3-DX Pioneer mobile in laboratory condition. The experimental result obtained show that the algorithm used by the vehicle to follow the center of the lane, with any given angle or position of initiation, has worked all the times under given experimental conditions, with a maximum error of 2 cm.
机译:通常,立体镜视觉用于引导自动智能公路车辆,因为可以容易地计算图像深度。但是,当其中一个相机失败时,具有合适的引导算法,可以使用单个摄像机检测车道标记的合适引导算法。这项工作的主要目标是使用单个相机使用图像处理技术,开发和实施用于识别和引导所指定的车道中智能公路车辆的控制算法。它涉及将相机拍摄的视频分成几个帧。然后,使用MATLAB中的图像采集技术处理所获得的帧。它检测要遵循图像处理的通道,计算机器人保持在分配的路径中所需的移动角度,并用适当的控制算法命令转向系统。使用颜色检测和边界标记技术进行车道的识别。该图像最初经历反向透视映射(IPM),用于在二维阵列中查看三维空间。一旦获取的图像的IPM经历车道检测算法,使用角度检测模块检测车道中的任何曲线的角度。还使用模糊逻辑算法在路径的中心移动机器人,其中从左检测边缘距离左侧检测到的距离作为输入,并输出由机器人移动的角度以保持在中心。在实验室条件下使用P3-DX先驱移动测试了开发的算法。获得的实验结果表明,车辆使用的算法跟随车道的中心,任何给定角度或发起位置,在给定的实验条件下所有时间都在工作,最大误差为2cm。

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