一定风险水平下的交通网络可靠性改进模型
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- 英文论文题名：An Improved Transportation Network Reliability Model under a Certain Level of Risk
- 论文作者：喻饶 ; 鲁光泉 ; 陈鹏 ; 王云鹏
- 英文论文作者：Yu Rao ; Lu Guangquan ; Chen Peng ; Wang Yunpeng ; Beihang University ; Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control
- 年：2016
- 作者机构：北京航空航天大学车路协同与安全控制北京市重点实验室;
- 论文关键词：交通工程 ; 出行时间可靠性 ; 风险 ; 高斯核函数 ; 路阻函数 ; 城市路网
- 英文论文关键词：Traffic Engineering ; Travel Time Reliability ; Risk ; Radial Basis Function ; Road Impedance Function ; Urban Network
- 会议召开时间：2016-11-16
- 会议录名称：第十一届中国智能交通年会大会论文集
- 语种：中文
- 分类号：U491.13
- 学会代码：ZJTX
- 会议名称：第十一届中国智能交通年会
- 会议地点：中国重庆
- 主办单位：中国智能交通协会
- 学会名称：中国智能交通协会
- 页数：10
- 文件大小：3072k
- 原文格式：D
- 会议级别：全国
摘要
传统基于风险的交通网络可靠性模型中的一些基本参数(如道路网络路段的实时交通量等)与速度相比更难大量获取。为了提高模型实际应用的意义,通过路阻函数模型对基于风险的交通网络可靠性模型进行改进,计算出置信度为0.95时北京市一典型路网在工作日早高峰时间(7:00至8:30)的RBR(Reliability Based on Risk)值,即在置信度为0.95时,出行者到达目的地最大可能花费的单位距离出行时间为3.873min。结果表明,提出的改进方法有效克服了某些路网中路段的实时交通量难以海量获取的不足,使得模型能够在仅有速度数据的情况下对当前城市路段、路网的RBR值进行计算并评价交通网络的运行情况。
Some basic parameters in the traditional risk-based transportation network reliability model,e.g.,network-scale traffic volume,were difficult to obtain with large amounts in practical applications.To improve the applicability of the traditional model,the road impedance function was employed in this study.The case study was conducted at a typical network in Beijing.The results show that RBR of the network is 3.873 min during the morning peak(i.e.,7:00-8:30) on workdays under the confidence level of 95%,and demonstrate the efficiency of the proposed model.Note that the model overcomes the difficulty of over-dependence upon large-scale network data and makes it possible to evaluate the network performance only based on traffic speed data.
Some basic parameters in the traditional risk-based transportation network reliability model,e.g.,network-scale traffic volume,were difficult to obtain with large amounts in practical applications.To improve the applicability of the traditional model,the road impedance function was employed in this study.The case study was conducted at a typical network in Beijing.The results show that RBR of the network is 3.873 min during the morning peak(i.e.,7:00-8:30) on workdays under the confidence level of 95%,and demonstrate the efficiency of the proposed model.Note that the model overcomes the difficulty of over-dependence upon large-scale network data and makes it possible to evaluate the network performance only based on traffic speed data.
引文
[1]陈建军,于雷,陈旭梅,陈琨.路网可靠性评价方法综述[J].城市交通,2008,6(1):67-70.
[2]李志纯,朱道立.随机动态交通网络可靠度分析与评价[J].交通运输工程学报,2008,8(1).
[3]Mine H,Kawai H.Mathematics for reliability analysis[J].Tokyo:Asakura-shoten,1982.
[4]Iida Y,Wakabayashi H.An approximation method of terminal reliability of road network using partial minimal path and cut sets[C].Transport Policy,Management&Technology Towards 2001:Selected Proceedings of the Fifth World Conference on Transport Research,1989.
[5]Asakura Y,Kashiwadani M.Road network reliability caused by daily fluctuation of traffic flow[C].PTRC Summer Annual Meeting,19th,1991,University of Sussex,United Kingdom,1991.
[6]Chen A,Yang H,Lo H K,Tang WH.A capacity related reliability for transportation networks[J].Journal of Advanced Transportation,1999,33(2):183-200.
[7]Chen A,Yang H,Lo H K,Tang WH.Capacity reliability of a road network:an assessment methodology and numerical results[J].Transportation Research Part B:Methodological,2002,36(3):225-252.
[8]Lam W H K,Zhang N.A new concept of travel demand satisfaction reliability for assessing road network performance[C].Matsuyama Workshop on Transport Network Analysis,Matsuyama,Japan,2000.
[9]D’Este G M,Taylor M.A.P.Modelling network vulnerability at the level of the national strategic transport network[J].Journal of the Eastern Asia Society for transportation studies,2001,4(2):1-14.
[10]Jenelius E.Network structure and travel patterns:explaining the geographical disparities of road network vulnerability[J].Journal of Transport Geography,2009,17(3):234-244.
[11]Taylor M.A.P.Modelling travel time reliability with the Burr distribution[J].Procedia-Social and Behavioral Sciences,2012(54):75-83.
[12]林徐勋,隽志才,倪安宁.城市道路交通系统可靠性研究综述[J].计算机应用研究,2012,29(8):2817-2820.
[13]马寿峰,贺正冰,等.基于风险的交通网络可靠性分析方法[J].系统工程理论与实践,2010(3):550-556.
[14]陈盛.城市道路交通流速度流量实用关系模型研究[D].东南大学,2004
[2]李志纯,朱道立.随机动态交通网络可靠度分析与评价[J].交通运输工程学报,2008,8(1).
[3]Mine H,Kawai H.Mathematics for reliability analysis[J].Tokyo:Asakura-shoten,1982.
[4]Iida Y,Wakabayashi H.An approximation method of terminal reliability of road network using partial minimal path and cut sets[C].Transport Policy,Management&Technology Towards 2001:Selected Proceedings of the Fifth World Conference on Transport Research,1989.
[5]Asakura Y,Kashiwadani M.Road network reliability caused by daily fluctuation of traffic flow[C].PTRC Summer Annual Meeting,19th,1991,University of Sussex,United Kingdom,1991.
[6]Chen A,Yang H,Lo H K,Tang WH.A capacity related reliability for transportation networks[J].Journal of Advanced Transportation,1999,33(2):183-200.
[7]Chen A,Yang H,Lo H K,Tang WH.Capacity reliability of a road network:an assessment methodology and numerical results[J].Transportation Research Part B:Methodological,2002,36(3):225-252.
[8]Lam W H K,Zhang N.A new concept of travel demand satisfaction reliability for assessing road network performance[C].Matsuyama Workshop on Transport Network Analysis,Matsuyama,Japan,2000.
[9]D’Este G M,Taylor M.A.P.Modelling network vulnerability at the level of the national strategic transport network[J].Journal of the Eastern Asia Society for transportation studies,2001,4(2):1-14.
[10]Jenelius E.Network structure and travel patterns:explaining the geographical disparities of road network vulnerability[J].Journal of Transport Geography,2009,17(3):234-244.
[11]Taylor M.A.P.Modelling travel time reliability with the Burr distribution[J].Procedia-Social and Behavioral Sciences,2012(54):75-83.
[12]林徐勋,隽志才,倪安宁.城市道路交通系统可靠性研究综述[J].计算机应用研究,2012,29(8):2817-2820.
[13]马寿峰,贺正冰,等.基于风险的交通网络可靠性分析方法[J].系统工程理论与实践,2010(3):550-556.
[14]陈盛.城市道路交通流速度流量实用关系模型研究[D].东南大学,2004