The invention discloses a vehicle abnormal behavior detection method and system based on trajectory data, analyzes the distribution characteristics of vehicle trajectory data under different spatial-temporal characteristics, and aims to avoid the defect that an abnormal behavior data screening method with a set threshold value neglects data internal information. The invention provides an abnormal behavior judging and screening method aiming at vehicle microscopic trajectory data by taking data which does not conform to most data feature expressions as abnormal behavior data, a supervised machine learning method is combined, and a data distribution module and a comprehensive processing module are introduced on the basis of a traditional support vector machine model, so that the abnormal behavior of the vehicle microscopic trajectory data is judged and screened. And proposing an abnormal behavior detection method aiming at the microscopic trajectory data. According to the method, vehicle abnormal behaviors are researched from the microscopic level to serve for macroscopic traffic flow operation state evaluation and traffic event early warning, the traffic state judgment efficiency is improved, traffic congestion nodes are rapidly dredged, and a theoretical basis is provided for highway management and decision making.
本发明公开了一种基于轨迹数据的车辆异常行为检测方法及系统,分析不同时空特征下车辆轨迹数据的分布特性,为了避免设置既定阈值的异常行为数据筛选方法会忽略数据内部信息的缺点,本发明将与大部分数据特征表现不相符的数据作为异常行为数据,提出一种针对车辆微观轨迹数据的异常行为判定与筛选方法,并结合有监督的机器学习方法,在传统支持向量机模型的基础上引入数据分流模块与综合处理模块,提出针对微观轨迹数据的异常行为检测方法。本发明从微观层面,研究车辆异常行为服务于宏观的交通流运行状态评估与交通事件预警,实现交通状态判断效率提升,交通拥堵节点快速疏导,为高速公路管理与决策提供理论依据。
Vehicle abnormal behavior detection method and system based on trajectory data
一种基于轨迹数据的车辆异常行为检测方法及系统
2024-02-09
Patent
Elektronische Ressource
Chinesisch
IPC: | G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS |
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