FCD-based Identification Method for Urban Recurrent Traffic Congestions
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摘要: 常发性拥堵严重影响了城市路网运行效率,准确识别常发性拥堵是交通部门解决交通拥堵问题的重要任务。研究选取浮动车数据作为基础,确定了数据分析的时间粒度,从常发性拥堵的时空特性角度出发,建立拥堵阈值、时段拥堵时长比和常发频度3级判别指标,并运用 GIS 技术,结合指标体系设计了常发性拥堵时空分布的筛选平台。以北京为例,针对早高峰常发性拥堵路段进行识别。通过对识别结果的分析和相关数据对比,成果可反映常发拥堵的特征,以及北京近年来的缓堵工作效果。Abstract: The recurrent traffic congestion has seriously affected the operating efficiency of urban road network .I-dentification of recurrent traffic congestions is the primary task of transportation agencies to solve the problem of traffic congestions .By using Floating Car Data (FCD) as the data basis ,this paper first determined the time aggregation level for analyzing FCD samples .Then ,from the aspect of spatial-temporal distribution characteristics ,this paper established three-stage screening indexes of recurrent traffic congestions ,including CThreshold ,CPercentage ,and CTime .By using the GIS technology and with combination of the indexes ,a spatial-temporal-distribution-based screening platform of recur-rent traffic congestion was developed .Finally ,this paper conducted a case study in Beijing and identified the recurrent traffic congestions for the morning peak hours .Based on the result analysis and comparisons with the relevant data ,it is demonstrated that this study is able to represent the characteristics of recurrent congestions and the congestion mitigation effect in recent years .
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