本发明公开了一种低渗透率轨迹数据下排队服务时间动态估计方法,获取研究区域内部的车辆轨迹数据,确定区域内每辆车辆的车辆编号、轨迹点时间、车辆位置和车辆速度,对研究区域内部的车辆轨迹数据进行分析处理,提取其中的每一车辆停车信息和车辆停止线驶离时间,建立车辆停车概率模型,对车辆排队时间进行动态估计,采用三种估计方法对交叉口情况进行定量化分析,实现交叉口车辆排队服务时间的动态估计,克服了对车辆到达模式的假设,结合大数据信息,对城市道路中重要节点进行协调管控、优化信号灯配时方案能够高效地提升道路交通资源的利用效率,提升交通通行能力。

    The invention discloses a method for dynamically estimating queuing service time under low-permeability trajectory data. According to the method, vehicle trajectory data in a research region is obtained, the vehicle number, trajectory point time, vehicle position and vehicle speed of each vehicle in the region are determined, the vehicle trajectory data in the research region are analyzed and processed, parking information of each vehicle and vehicle stop line leaving time is extracted, a vehicle parking probability model is established, vehicle queuing time is dynamically estimated, intersection conditions is quantitatively analyzed by adopting three estimation methods, dynamic estimation of intersection vehicle queuing service time is achieved, the assumption of a vehicle arrival mode is overcome, through combination of big data information, important nodes in urban roads are managed and controlled in a coordinated manner, and a signal lamp timing scheme is optimized, so that the utilization efficiency of road traffic resources can be efficiently improved, and the traffic capacity is improved.


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    Titel :

    一种低渗透率轨迹数据下排队服务时间动态估计方法


    Erscheinungsdatum :

    2023-11-10


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

    IPC:    G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS