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Driving Assistance System at T-junctions in Mauritius

机译：在毛里求斯的T-Chonionction驾驶辅助系统

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Road accidents somehow have made it to the headlines in the news or have been the hot topics on social media in the past few years in Mauritius. This work focuses on finding a solution to aid car drivers at T-junctions which had the highest number of accidents amongst all the other junctions in Mauritius. The main objective of this work is to assist a driver at a T-junction in decision-taking whether to move out or wait and hence to decrease the number of accidents at T-junctions. An advanced driving assistance system has been developed using Raspberry pi and Neural Compute Stick to achieve better frames per second during the processing of the live video streaming. The system detects, tracks the oncoming car and calculates the speed of the vehicle approaching a T-junction. The detection, tracking and speed calculation of a car were tested and the results obtained were satisfactory. In the case where no vehicle was being detected, the system successfully displayed a message that the lane was clear and the driver could move out of the junction. Also, the latter was asked to wait when the lane was blocked and was alerted of a danger whenever the speed limit was exceeded by the vehicle on the adjacent road at the T- junction. The average speed accuracy obtained is 84.96 %.
机译：道路事故以某种方式向新闻中的头条新闻或过去几年来到了新闻中的热门话题在毛里求斯的几年内。这项工作侧重于寻找一个解决方案，以帮助汽车司机在毛里求斯的所有其他联盟中具有最多的事故。这项工作的主要目标是在决策中协助驾驶员在决策中进行T-Chonction，是是否搬出或等待，从而减少T-Chonctions的事故数量。通过覆盆子PI和神经计算棒开发了先进的驾驶辅助系统，以在实况视频流的处理期间实现每秒更好的帧。系统检测，跟踪迎面而来的汽车并计算接近T-Anction的车辆的速度。测试了汽车的检测，跟踪和速度计算，得到的结果令人满意。在没有检测到车辆的情况下，系统成功地显示了通道清晰的消息，并且驾驶员可以移出交界处。此外，当车辆在T界线上的相邻道路上超过速度限制时，后者被要求等待当车道被封锁并警告危险时。获得的平均速度精度为84.96％。

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