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基于公众出行感知调研与测算的交通状态实时评价指标

Keywords: 道路交通状态指数,实时评价指标,公众出行感知,综合评价法,行程时间,行程距离

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Abstract:

为弥补城市道路和走廊交通运行评价的不足、提高交通状态评价的实时性,基于对公众出行感知调研和加权测算的对比分析,提出了基于浮动车数据的交通状态指数实时评价方法.采集每1min间隔的出行交通感知,分别以时间和距离为权重,计算区间出行的综合感知,与实测区间感知数据相比较,结果表明:出行者对拥堵状况下的时间变化更加敏感.在此基础上,选择路段行程时间为权重,由路段交通状态指数建立道路交通状态综合评价指数.以北京市西二环和八达岭高速为实例,对交通走廊运行状态和拥堵强度进行了评价,论证了指标和方法的实用性.

References

[1]  北京交通发展研究中心.DB11/T785—2011城市道路交通运行评价指标体系[S].北京:北京市质量技术监督局,2011.
[2]  HNTB Corporation.Atlanta regional managed lane systemplan,technical memorandum 12:corridor evaluation andfinal recommendations[R].Atlanta USA:GeorgiaDepartment of Transportation,2010.
[3]  EISELE B,SCHRANK D,LOMAX T.TTI’s 2011congested corridors report powered by INTIX traffic data[R].Texas,USA:Texas Transportation Institute,theTexas A&M University System,2011.
[4]  刘梦涵.面向特大城市的分层次交通拥堵评价模型及算法[D].北京:北京交通大学交通运输学院,2009.LIU Meng-han.Stratified traffic congestion measurementmodels and algorithms for megacities[D].Beijing:Schoolof Traffic and Transportation,Beijing Jiaotong University,2009.(in Chinese)
[5]  张雪莲,于雷,刘梦涵.基于交通需求的路网交通拥堵评价模型[J].现代交通技术,2008,5(6):71-75.ZHANG Xue-lian,YU Lei,LIU Meng-han.Trafficdemand-based traffic congestion measurement models forroad networks[J].Modern Transportation Technology,2008,5(6):71-75.(in Chinese)
[6]  VAZIRI M.Development of highway congestion index withfuzzy set models[J].Transportation Research Record:Journal of Transportation Research Board,2002(1802):16-22.
[7]  EPPS A,MAY A D,CORTELYOU C.Developing amethodology for quantifying non-recurring freewaycongestion delay,phase one:identification of alternativemethodologies[R].California USA:Institute ofTransportation Studies,University of California atBerkeley,1993:111-126.
[8]  SCHRANK D,LOMAX T,EISELE B.TTI’s 2011 UrbanMobility Report Powered by INTIX Traffic Data[R].Texas:Texas Transportation Institute,The Texas A&MUniversity System,2011.

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