基于计算机视觉的自动驾驶汽车转向角计算方法

R. Meganathan, Aarthi Alagammai Kasi, Sujatha Jagannath
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引用次数: 11

摘要

智能无人驾驶汽车发展的一个关键要求是有效导航的转向角计算。本文提出了一种计算成本相对较低的基于计算机视觉技术的无人驾驶车辆转向角计算新方法。拟议的制度包括三个主要阶段。第一阶段是利用高斯混合模型和期望最大化算法提取动态道路区域。第二阶段是基于提取的道路区域计算转向角度。此外,利用卡尔曼滤波技术消除了杂散的角度过渡噪声。在模拟器和实时图像上进行了测试,结果表明该算法能很好地估计出导航所需的实际转向角。此外,我们还观察到,这在不同的照明条件下以及结构化和非结构化道路场景下都有效。
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Computer Vision Based Novel Steering Angle Calculation for Autonomous Vehicles
A key requirement in the development of intelligent and driverless vehicles is steering angle computation for efficient navigation. This paper presents a novel method for computing steering angle for driverless vehicles using computer vision based techniques of relatively lower computing cost. The proposed system consists of three major stages. The first stage includes Dynamic Road region extraction using Gaussian Mixture Model and Expectation Maximization algorithm. The second stage is to compute the steering angle based on the extracted roadregion. In addition, Kalman filtering technique is used to cancel spurious angle transition noises. The proposed algorithm was tested both on a simulator and real-time images and was found to give a good estimation of actual steering angle required for navigation. Further, it was also observed that this works in different lighting conditions as well as for both structured and unstructured road scenarios.
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