Map matching method of large-scale floating cars based on road incremental updating under emergency accidents

Xiao-ming Sun, Zhaosheng Yang, Pengcheng Sun
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Abstract

Vehicle-grade traffic information selecting type based on floating cars plays a significant role when it was under the influence of emergency accidents, and map matching (MM) is the key technology of this type. In this paper, against the problems of current MM method, we proposed a novel MM method based on road incremental updating data. This method was carried out through network topology which updated according to roads' dynamic changes, and it could solve real-time MM process by an effective candidate links identification method, at the same time, the MM method put forward applied parallel roads reverse recognition method on the link matching. And on the junction, this method took delay matching method and optimal path selection method to overcome the MM complexity caused by intersections and main side roads in large-scale urban traffic network. Experiment results showed that the MM method proposed in this paper can perform high MM precision in large-scale and complicated road network under emergency accidents.
紧急事故下基于道路增量更新的大型浮动车地图匹配方法
基于浮车的车辆级交通信息选择类型在突发事故影响下发挥着重要作用,而地图匹配(MM)是该类的关键技术。针对当前MM方法存在的问题,提出了一种基于道路增量更新数据的MM方法。该方法通过根据道路动态变化而更新的网络拓扑来实现,通过一种有效的候选链路识别方法来解决实时MM过程,同时提出的MM方法将平行道路反向识别方法应用于链路匹配。在交叉口上,采用延迟匹配方法和最优路径选择方法,克服了大规模城市交通网络中交叉口和主干道造成的MM复杂性。实验结果表明,本文提出的分模方法在突发事故下的大规模复杂路网中具有较高的分模精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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