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Queue-Based Headway Distribution Models at Signal Controlled Intersection under Mixed Traffic
Transportation Research Record: Journal of the Transportation Research Board ( IF 1.7 ) Pub Date : 2020-09-11 , DOI: 10.1177/0361198120949876
Satyajit Mondal 1 , Ankit Gupta 1
Affiliation  

Headway of vehicles during platoon dispersion at signalized intersection is one of the critical microscopic traffic characteristics in traffic flow theory. The distribution of the discharge headways of vehicles also has a significant impact on the traffic generation process in most of the microsimulation approaches. However, few studies have investigated the vehicle discharge headway for interrupted flow at signalized intersections under mixed traffic conditions. The present study uses data collected from 20 intersections in six cities for comprehensive analysis of discharge headway. A box-and-whiskers plot is generated for discharge headway to quantify its reasonable profile. The diagram shows that headway of vehicles decreases with the queue dispersion. A stable headway can be observed after the fifth vehicle position of a queue, giving a saturation headway of 2.05 s per vehicle. Six types of continuous distribution are tested to model the discharge headway distribution. A statistical investigation is also performed to verify the best-fitted model for each vehicle position in a queue. The ranking of a best-fitted distribution is done for each vehicle position as per the statistical significance. This study demonstrates the discharge headway characteristics and distribution at each vehicle position, which can be useful for traffic flow analysis and especially for improving microsimulation models.



中文翻译:

混合交通下信号控制交叉口基于队列的车头分配模型

信号交叉口排扩散期间的车辆行驶距离是交通流理论中的关键微观交通特性之一。在大多数微观模拟方法中,车辆的排放行程的分布也对交通产生过程具有重要影响。然而,很少有研究调查在混合交通状况下信号交叉口车辆流量的中断情况。本研究使用从六个城市的20个交叉口收集的数据来进行排放间距的综合分析。将生成一个箱须图,以进行排放,以量化其合理分布。该图表明,随着行进距离的增加,车辆的行进距离减小。在队列的第五个车辆位置之后,可以观察到稳定的行驶距离,每辆车的饱和行程为2.05 s。测试了六种类型的连续分布,以模拟排放时距分布。还执行统计调查以验证队列中每个车辆位置的最佳拟合模型。根据统计显着性,对每个车辆位置进行最佳拟合分布的排名。这项研究表明了每个车辆位置的排放时距特性和分布,这对于交通流分析尤其是改善微观仿真模型很有用。根据统计显着性,对每个车辆位置进行最佳拟合分布的排名。这项研究表明了每个车辆位置的排放时距特性和分布,这对于交通流分析尤其是改进微观仿真模型很有用。根据统计显着性,对每个车辆位置进行最佳拟合分布的排名。这项研究表明了每个车辆位置的排放时距特性和分布,这对于交通流分析尤其是改进微观仿真模型很有用。

更新日期:2020-09-12
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