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Safe Driving at Traffic Lights: An Image Recognition Based Approach

机译:交通信号灯的安全驾驶:一种基于图像识别的方法

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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.
机译:随着车辆数量的增加,交通事故的数量也增加,特别是在交通信号灯处。为了提高红绿灯的驾驶安全性,本文提出了一种智能安全驾驶助手,可以根据红绿灯的相位为驾驶员提供驾驶建议,而现有研究已忽略了这些信息。驾驶辅助系统由带有单个车载摄像头的图像识别系统组成,可以减轻观察交通灯相位的困难。识别系统使用卷积神经网络获取交通灯倒计时信息,并使用交通灯信息的结果估算倒计时时间。此外,我们开发了一个模型,可以通过使用摄像头和交通信号灯的信息来计算交通信号灯与车辆之间的距离。根据交通信号灯的相位和获得的距离,驾驶助手可以提供一种速度控制策略,以提高驾驶员的安全性。最后,进行了广泛的实验以验证所提出方法的有效性。

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