Forecasting approach for Blind Spot Collision Alert

Bektache Djamel, Mohamed Amine Yakoubi, Ghoualmi Nacera Zine
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Abstract

Every year many accidents involving all categories of road users. However, some accidents are related to the blind spot, due to the deficiency of visibility in this zone, also lack of information or negligence. In this work, we focused on the road safety applications. The main of our researches is to alert the risk of blind spot collision. For this we designed a new approach, namely FBSCA, Forecasting Blind Spot Collision Alert, the driver alerts his neighbors for a possible accident related to the blind spot. The most interesting scenario testing includes the case where the vehicles need to exchange information in real-time in order to avoid traffic collisions when their visibility is hindered by road obstacles. For the implementation and testing of our approach we used popular network simulation tools such MOVE, SUMO and Ns2, we provided an assessment of proposed solution in order to alert the blind spot collisions for all neighboring vehicles.
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盲点碰撞预警的预测方法
每年都有许多事故涉及各类道路使用者。然而,一些事故与盲区有关,由于该区域的能见度不足,也缺乏信息或疏忽。在这项工作中,我们重点关注道路安全应用。我们的研究主要是对盲区碰撞风险进行预警。为此,我们设计了一种新的方法,即FBSCA (Forecasting Blind Spot Collision Alert,预测盲点碰撞警报),驾驶员提醒他的邻居与盲点有关的可能发生的事故。最有趣的场景测试包括车辆需要实时交换信息,以避免在能见度受到道路障碍物阻碍时发生交通碰撞的情况。为了实现和测试我们的方法,我们使用了流行的网络仿真工具,如MOVE、SUMO和Ns2,我们对提出的解决方案进行了评估,以便为所有相邻车辆发出盲点碰撞警报。
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