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当前城市主干道过饱和交通流交通状况恶劣,交通拥堵时常发生,由于受信号灯的周期性阻滞作用,交叉口上游车辆淤积现象严重,传统的连续交通流模型无法用于估算城市主干道旅行时间。有鉴于此,提出了一种适用于中断交通流的基于车辆队列的旅行时间估算方法。基于道路上已有的存在型检测器,运用检测器采集的高精度实时数据,研究了车队识别和匹配方法,通过匹配车队信息,对通过饱和状态下城市主干道的车辆进行了实时旅行时间估算。在此基础上,利用Q-Paramics软件进行了实例模型仿真验证。通过对比算法估算值和仿真模型观测值,验证了算法的合理性和有效性,为评估饱和状态下的城市主干道交通状态奠定了基础。
Due to the poor traffic condition of the over-saturated traffic flow in the main urban roads and frequent traffic jams, the traffic congestion at the upstream of the intersections is serious due to the cyclical blockage of the traffic lights. The traditional continuous traffic flow model can not be used to estimate the travel time of urban main roads . In view of this, a vehicle queue-based travel time estimation method suitable for interrupting traffic flow is proposed. Based on existing presence detectors on the road, the real-time travel time of vehicles passing through the main roads in the saturated state was estimated by matching the fleet information with the high-precision real-time data collected by the detectors. . On this basis, using Q-Paramics software for instance simulation. By comparing the estimated value of the algorithm with the observed value of the simulation model, the rationality and validity of the algorithm are verified, which lays a good foundation for evaluating the traffic condition of the main arterial road in the saturated state.