冰雪天气下基于GIS的车辆防碰撞预警模型

GIS-based vehicle collision avoidance warning model in ice and snow weather

车辆防碰撞预警是智能交通系统中的关键技术,为了提升车辆防碰撞预警结果的准确性,提出一种冰雪天气下基于GIS的车辆防碰撞预警模型。采用雨雪检测模型对冰雪进行检测,通过亮度平均法去除雨雪,提升图像检测质量;同时通过自适应阴影检测方法统计车流量。根据对车辆制动过程以及跟车过程的动力分析,计算车辆之间的安全距离,提取标志物特征点,构建基于GIS的车辆防碰撞预警模型,通过模型实现车辆防碰撞预警。仿真实验结果表明,所提模型不仅可以有效预警车辆防止碰撞,同时还能够减少时间开销,可为未来完善车辆防碰撞预警系统提供理论基础。

Vehicle anti-collision warning is a key technology in the intelligent transportation system.In order to improve the accuracy of vehicle anti-collision warning results,a GIS-based vehicle anti-collision warning model in ice and snow weather is proposed.The rain and snow detection model is used to detect snow and ice,and the brightness average method is used to remove the rain and snow to improve the image detection quality;at the same time,the adaptive shadow detection method is used to count the traffic flow.According to the dynamic analysis of the vehicle braking process and the following process,the safe distance between vehicles is calculated,the landmark feature points are extracted,and a GIS-based vehicle anti-collision warning model is constructed,and the vehicle anti-collision warning is realized through the model.The simulation results show that the proposed model can not only effectively warn the vehicle to avoid collision,but also reduce the time overhead,which provides a theoretical basis for improving the vehicle anti-collision warning system in the future.