交通信号灯安全驾驶:一种基于图像识别的方法

Cuizhu Bao, Chen Chen, H. Kui, Xiaoyang Wang
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引用次数: 8

摘要

随着车辆数量的增加,交通事故的数量也在增加,尤其是在红绿灯处。为了提高交通信号灯下的驾驶安全性,本文提出了一种智能安全驾驶助手,根据交通信号灯的相位为驾驶员提供驾驶建议,这一信息在现有研究中被忽视。驾驶助手由一个带有单个车载摄像头的图像识别系统组成,可以改善观察交通灯相位的困难。该识别系统利用卷积神经网络获取红绿灯倒计时信息,并利用红绿灯倒计时信息的结果估计倒计时时间。此外,我们还开发了一个利用摄像头和红绿灯信息计算红绿灯与车辆距离的模型。驾驶辅助系统可以根据所获得的交通灯相位和距离提供速度控制策略,以提高驾驶员的安全性。最后,进行了大量的实验来验证所提出方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Safe Driving at Traffic Lights: An Image Recognition Based Approach
With the increasing number of vehicles, the number of traffic accidents also increases, especially at traffic lights. To enhance the driving safety at traffic lights, in this paper, we propose an intelligent safe driving assistant to provide drivers with driving advice based on traffic light phases, which information has been neglected by existing research. The driving assistant consists of an image recognition system with a single on-board camera, which can ameliorate the difficulties of observing traffic light phases. The recognition system obtains traffic light countdown information using a Convolutional Neural Network, and estimates the countdown time using the results of traffic light information. In addition, we develop a model to calculate the distance between the traffic light and vehicle by using the information of camera and traffic light. Based on the traffic light phase and the distance obtained, the driving assistant can provide a velocity control strategy to improve driver's safety. Finally, extensive experiments are conducted to verify the effectiveness of proposed methods.
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