Abstract
Identifying bottlenecks and analyzing their characteristics are important tasks to city traffic management authorities. Although the speed difference was proposed for the bottleneck identification in the existing research, the use of a secondary indicator has not been fully discussed. This paper strived to develop a method to identify the bottleneck on expressways by using the massive floating car data (FCD) in Beijing. First, the speed characteristics of bottlenecks on expressway were analyzed based on the speed contour map. The results indicated that there was a significant difference between speeds on the bottleneck and downstream links when a bottleneck was observed. The speed difference could indeed be used as the primary indicator to identify the bottleneck. However, it was also shown that a sufficiently large speed difference does not necessitate an activation of a bottleneck. The speed-at-capacity was then used as the secondary indicator to distinguish the real bottleneck from the non-bottleneck speed difference. Second, a practical method for identifying the bottleneck on expressways was developed based on the speed difference and the speed-at-capacity. Finally, the method was applied to identifying the bottlenecks of the 3rd Outer Ring Expressway in Beijing. The duration, affected distance, delay and cause were used to evaluate and analyze the bottlenecks.
摘要
识别交通瓶颈并分析其特征是城市交通管理部门的重要任务。现有研究虽然提出应用速度差识 别瓶颈,但辅助指标的利用仍未被充分讨论。本文利用北京市浮动车数据提出了一种识别城市快速路 交通瓶颈的方法。首先,利用速度等高线图分析了城市快速路瓶颈的速度特征。结果表明,当瓶颈生 效时,瓶颈与下游路段之间存在显著的速度差。速度差可以被用为识别瓶颈的主要指标。然而,分析 也发现并不是所有显著的速度差都反映瓶颈生效。而临界速度可以作为辅助指标区分生效瓶颈和非瓶 颈下的速度差。 在此基础上,提出了一种以速度差和临界速度为主要指标的城市快速路瓶颈识别方 法。最后,应用该方法识别了北京三环快速路外环的瓶颈;并从生效时长、影响距离、延误和成因等 角度对瓶颈进行了评估和讨论。
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Foundation item: Project(2018YJS081) supported by the Fundamental Research Funds for the Central Universities, China; Projects(71273024, 51578052) supported by the National Natural Science Foundation of China (NSFC)
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Zhang, Jb., Song, Gh., Yu, L. et al. Identification and characteristics analysis of bottlenecks on urban expressways based on floating car data. J. Cent. South Univ. 25, 2014–2024 (2018). https://doi.org/10.1007/s11771-018-3891-8
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DOI: https://doi.org/10.1007/s11771-018-3891-8