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为了及时发现和预警城市交通高峰时期的偶发事件，研究了态势监控的城市交通拥堵动态跟踪问题.对交通拥堵的相关属性、变化规律、空间分布以及判别方式等进行综合研究的基础上，分析了道路交通流的非线性动力学特征，建立了基于时空分布的路网交通拥堵态势监控的动态预警模型，提出了解决城市路网交通拥堵的方法，达到了充分利用交通资源、疏导交通、缓解交通拥堵的目的.该模型在对占有率、速度、流量三个基本交通流参数进行处理获得新的交通拥挤判别指标基础上，通过形态识别模型对拥堵状态进行判定.实例分析表明，该模型为缓解城市交通拥堵问题、提高城市交通管理水平、改善道路交通安全形势等具有重要的理论意义和应用价值.

Space-Time Distribution Model on State Monitoring of Urban Traffic Congestion

Based on characteristics parameters analysis, some indexes of the state monitoring on urban traffic congestions are defined. By establishing the urban traffic network model, this paper designs a quantitative analysis flow of space-time congestion monitoring of road network based on the multi-dimension theory. Then, it uses three space-time parameters to study the traffic jams monitoring model of road traffic network. Aimed at resolving the quick measurements and control of traffic congestions, a real-time decision support model which can timely reflect traffic congestion situations is developed. The results show that this real-time decision support model can take place of traffic engineers’ management works and raise the efficiency of congestion management. To quickly identify the non-recurrent incidents during peak period, an auto-identifying algorithm of urban traffic congestion is designed. An improved multi-dimension monitoring algorithm and interconnected model are proposed to identify the traffic congestion and its diffusion. The application results reveal the validity and maneuverability of the study, and a foundation for developing the decision support system is thus provided for urban traffic congestion management.