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基于速度-密度模型的路网连通可靠度分析
引用本文:裴玉龙,王宇,彭挺.基于速度-密度模型的路网连通可靠度分析[J].城市交通,2013(4):66-69,12.
作者姓名:裴玉龙  王宇  彭挺
作者单位:1. 哈尔滨工业大学交通科学与工程学院,黑龙江哈尔滨,150090
2. 中国城市规划设计研究院,北京,100037
摘    要:传统的连通可靠度评价方法往往将路段分为连通和不连通两种状态,对于实际路网的评价存在计算量过犬的问题,缺乏可操作性。首先结合安德伍德指数模型和格林伯格对数模型,构建能够反映各种交通流状态的速度一密度模型。在此基础上,以行车速度和交通量为基本参数构造路段综合连通指数,提出路段和路网连通可靠度的计算方法。以行车速度为分类依据,提出连通可靠度评价标准。最后,对辽宁省锦州市某区域早高峰时段路网连通可靠度进行分析,结果表明:基于速度一密度模型的路网连通可靠度计算方法能够比较真实地反映道路交通实际状况,且计算过程得到较大简化。

关 键 词:交通工程  连通可靠度  速度-密度模型  综合连通指数

Connection Reliability Analysis of Road Network based on the Speed-Density Model
Pei Yulong , Wang Yu , Peng Ting.Connection Reliability Analysis of Road Network based on the Speed-Density Model[J].Urban Transport of China,2013(4):66-69,12.
Authors:Pei Yulong  Wang Yu  Peng Ting
Institution:1(1.School of Transportation Science and Engineering,Harbin Institute of Technology,Harbin Heilongjiang 150090,China;2.China Academy of Urban Planning & Design,Beijing 100037)
Abstract:Traditional connection reliability assessment methods usually classify the states of road section into two types: connected and interrupted. These methods are not computation friendly, which limits their applications in real-world networks. This paper first establishes a speed-density model which can reflect variation of traffic flow states according to the Underwood index model and Greenberg logarithmic model. Then the paper develops a compre- hensive connectivity index for the road segment using speed and traffic volume as basic parameters, and proposes the approach to compute the connection reliability for road segments and the network. The paper also develops evaluation criteria of connection reliability according to the speed classifications. Finally, a case study was conducted on a network in Jinzhou city of Liaoning province during morning peaks. Results indicate that the proposed approach can better reflect the actual traffic conditions and simplify the calculation process.
Keywords:traffic engineering  connection reliability  speed-densi-ty model  comprehensive connectivity index
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