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Recognition of parking spaces on dry and wet road surfaces using received light intensity of laser for ultra small EVs

机译:使用超小型电动汽车的激光接收光强度识别干燥和潮湿路面上的停车位

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Research and development of automatic driving technology has been actively conducted in recent years. Under this background, it is considered that the car parking problem is expected to be developed for supporting drivers to complete automatic parking. Many parking lots in an urban area prepare parking spaces with asphalt road surface drawn by white paint. Research to recognize parking spaces using camera images has been conducted so far. However, camera images are known to be not robust to environmental conditions such as nighttime and a backlight. Therefore, a method of recognizing parking spaces is proposed so that it can be used even when the use time is day or night, irrespective of whether the road surface is dry or wet. In the proposed method, the road surface is classified using the statistical model of the received light intensity value of laser range scanner. Then, the target parking position is estimated by Hough transformation.
机译:近年来,已经积极进行自动驾驶技术的研究和开发。在这种背景下,认为将出现停车问题以支持驾驶员完成自动停车。市区中的许多停车场都准备有白色油漆绘制的沥青路面的停车位。迄今为止,已经进行了使用相机图像识别停车位的研究。然而,已知照相机图像对于诸如夜间和背光的环境条件不是鲁棒的。因此,提出了一种识别停车位的方法,以使得即使在白天或晚上使用时间时也可以使用该方法,而与路面是干还是湿无关。在所提出的方法中,使用激光测距仪的接收光强度值的统计模型对路面进行分类。然后,通过霍夫变换估计目标停车位置。

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