The invention discloses an urban traffic data-oriented real-time abnormal trajectory detection method, which comprises the steps of mapping GPS points in a traffic trajectory data set into an urban traffic road network through map matching, dividing the traffic trajectory data set into different training sets according to SD pairs, constructing a space-time model based on the SD pairs according to trajectories in the different training sets, and carrying out real-time abnormal trajectory detection on the basis of the space-time model. The method comprises the following steps: acquiring a test track, when the test track is a reached track, carrying out abnormity judgment on the reached track, when the reached track is normal, the test track is normal, otherwise, the test track is abnormal, when the test track comprises the reached track and a non-reached track, carrying out abnormity judgment on the reached track, and when the reached track is normal, carrying out abnormity judgment on the non-reached track. When the unreached track is an abnormal track, the test track is abnormal, when the unreached track is a normal track, the test track is normal, and when the reached track is abnormal, the test track is abnormal. The real-time abnormal track detection efficiency is improved, and the detection accuracy is improved.
本发明公开了一种面向城市交通数据的实时异常轨迹检测方法,包括将交通轨迹数据集中的GPS点经地图匹配映射到城市交通路网中,根据SD对将交通轨迹数据集划分为不同的训练集,根据不同训练集中的轨迹构建基于SD对的时空模型,获取测试轨迹,当测试轨迹为已达轨迹时,对已达轨迹进行异常判断,当已达轨迹为正常时,测试轨迹为正常,反之为异常,当测试轨迹包括已达轨迹和未达轨迹时,对已达轨迹进行异常判断,当已达轨迹为正常时,对未达轨迹进行异常判断,当未达轨迹为异常轨迹时,测试轨迹为异常,当未达轨迹为正常轨迹时,将测试轨迹为正常,当已达轨迹为异常时,测试轨迹为异常。提高了实时异常轨迹检测的效率并提高了检测的准确性。
Real-time abnormal trajectory detection method for urban traffic data
一种面向城市交通数据的实时异常轨迹检测方法
2023-08-15
Patent
Electronic Resource
Chinese
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