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中文摘要：
为了解决拥堵状态下交通网络瓶颈识别问题，文章基于时空检测数据对道路节点和路段拥堵状态进行了分析，并以此为基础建立了城市交通网络瓶颈识别与分类模型。拥堵发生期间，以任意2辆浮动车连续通过拥堵路径各个交叉口时间间隔作为统计时间，以拥堵路径各个交叉口对应流向流出率作为统计对象，连续统计多辆浮动车通过时的交通量序列，建立了拥堵路径交叉口关联度模型并以此划分交通网络瓶颈。以划分的交通拥堵瓶颈区域作为密闭区域，通过分析拥堵路径平峰期间与拥堵期间的流人流出率，使用切比雪夫不等式在置信度95％范围内建立了拥堵瓶颈的3类模型：输入型瓶颈、输出型瓶颈和通过型瓶颈。以实际区域道路网络为研究对象，使用上述模型对拥堵区域进行了分析，结果表明该模型可有效识别并分类交通网络瓶颈。
英文摘要：
In order to solve the problem of bottleneck identification in congested traffic network, the road node and link were analyzed based on temporal and spatial detection data, and then the urban traffic network bottleneck identification and classification model was established. Taking the interval of any two floating cars continuously through each intersection of congestion path as statistical time and the rate of outflow corresponding to each intersection of congestion path as statistical object, the traffic sequence when many floating cars were passing through was continuously statisticalized. Then the intersection correlation model was established to divide the traffic network bottleneck. Taking the divided area of traffic bottleneck as a closed area, through analyzing the inflow and outflow rate during the period of congestion and flat peak, and using the Chebyshev＇s inequality under the condition of a 95% confidence level, three types of congestion bottleneck were established, namely imported bottle- neck, outputted bottleneck and passed bottleneck. Taking the actual regional road network as analysis object, the eongestion area was analyzed by using the above model. The results show that the model can effectively identify and classify the traffic network bottleneck.
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