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Analytical Model for Travel Time-Based BPR Function with Demand Fluctuation and Capacity Degradation

机译:基于旅行时间的BPR功能的分析模型,需求波动和容量降级

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This study presents a stochastic model based on the link performance function of the Bureau of Public Roads to assess the reliability of travel time in the transportation network. Empirical studies have verified that the variability of travel time can be ascribed to demand fluctuation and the degradation of the capacity of the stochastic network. The mean-variance approach in previous research presented the budget model of travel time, with the capacity of the stochastic network and elastic demand as the sources of uncertainty of travel time. Previous research was devoted to the study of estimation of travel time considering a single factor or a factor independent of these two sources. Meanwhile, this study introduces the current degeneration coefficient of capacity (CDC) and the density distribution function of road section saturation (DDFS) with simultaneous network capacity and traffic demand. Sensitivity analysis method for the parameters of the proposed model is investigated theoretically using the sensitivity model of traffic capacity degradation. Results of case analysis show that the DDFS and CDC have an effect on the decision of travelers regarding the choice of route. The empirical analysis also illustrates the effectiveness of the computational approach and the proposed model.
机译:本研究提出了一种基于公共道路局的链接性能功能的随机模型,以评估运输网络的旅行时间可靠性。实证研究已经验证了旅行时间的可变性可以归因于随机网络的容量的温度和降低。先前研究中的平均方差方法提出了旅行时间的预算模型,随着随机网络的能力和弹性需求作为旅行时间不确定性的来源。以前的研究致力于考虑单个因素或独立于这两个来源的因素的旅行时间估算研究。同时,该研究介绍了具有同时网络容量和业务需求的路段饱和度(DDF)的电流退化系数(CDC)和路段饱和度(DDF)的密度分布函数。理论上,使用交通量劣化的灵敏度模型理论上研究了所提出模型参数的敏感性分析方法。案例分析结果表明,DDFS和CDC对旅行者的选择作出了影响。实证分析还说明了计算方法和所提出的模型的有效性。

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  • 来源
    《Mathematical Problems in Engineering》 |2019年第22期|5916479.1-5916479.13|共13页
  • 作者单位

    Beihang Univ Sch Elect & Informat Engn 37 Xue Yuan Lu Beijing Peoples R China|Beihang Univ Hefei Innovat Res Inst A1 Intelligent Ind Pk New Stn High Tech Ind Dev Hefei Anhui Peoples R China;

    Beihang Univ Sch Transportat Sci & Engn Beijing Key Lab Cooperat Vehicle Infrastruct Syst 37 Xue Yuan Lu Beijing Peoples R China;

    Beihang Univ Sch Elect & Informat Engn 37 Xue Yuan Lu Beijing Peoples R China;

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