城市大规模交通网络低效路段组合定位及分析
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摘要
基于布雷斯悖论现象,根据城市交通网络中路段或路段组合对路网通行效率的影响,可将其划分为低效的或必要的,合理关闭路网中的低效路段及路段组合将减少所有出行者的出行时间成本,必要路段及路段组合的关闭将增加出行者额外的出行延误。采用改进的自适应遗传算法以有效地定位大规模真实交通网络中的低效路段组合,结合美国旧金山市大规模实际交通网络地理信息系统(GIS)数据以及该区居民通勤出行数据进行实证分析。研究结果证实低效路段和必要路段的组合可能是低效的。分析表明,低效路段组合的低效程度|ΔTS|随着所含路段数量增加呈现先增后减的变化趋势,含路段数相对少的低效路段组合对路网效率产生更大的影响也更普遍。
In this paper,road and cluster of roads in transportation network were classified as inefficient or necessary according to their effect on the efficiency of the road network,based on Braess' s paradox. Reasonable closure of inefficient links can reduce travel costs considerably,while the failure of necessary links would result in extra travel delays. We modified the adaptive genetic algorithm to pinpoint inefficient road clusters in a real large-scale traffic network. Actual transportation network data from geographical information systems( GIS) and daily commuting origin destination matrix in the San Francisco were used. Our empirical results show that inefficient road clusters include not only inefficient road but also necessary road. Meanwhile,the degree of inefficiency |ΔTS | increases first and then decreases as the number of roads in the road clusters increase. Inefficient road clusters contain less road with large | ΔTS |,which is much more common as well.
In this paper,road and cluster of roads in transportation network were classified as inefficient or necessary according to their effect on the efficiency of the road network,based on Braess' s paradox. Reasonable closure of inefficient links can reduce travel costs considerably,while the failure of necessary links would result in extra travel delays. We modified the adaptive genetic algorithm to pinpoint inefficient road clusters in a real large-scale traffic network. Actual transportation network data from geographical information systems( GIS) and daily commuting origin destination matrix in the San Francisco were used. Our empirical results show that inefficient road clusters include not only inefficient road but also necessary road. Meanwhile,the degree of inefficiency |ΔTS | increases first and then decreases as the number of roads in the road clusters increase. Inefficient road clusters contain less road with large | ΔTS |,which is much more common as well.
引文
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[2]Youn H,Gastner M T,Jcong H.Price of anarchy in transportation networks:efficiency and optimality control[J].Physical Review Letters,2008,101(12):128701-128704.
[3]Dafermos S,Nagurney A.On some traffic equilibrium theory paradoxes[J].Transportation Research Part B:Methodological,1984,18(2):101-110.
[4]PAS E I,PRINCIPIO S L.Braess'paradox:Some new insights[J].Transportation Research,1997,31(3-31):265-276.
[5]Hagstrom J N,Abrams R A.Characterizing Braess's paradox for traffic networks[C]//Proceedings of the IEEE Conference on Intelligent Transportation Systems,2001:837-842.
[6]Nagurney A.The negation of the Braess paradox as demand increases:The wisdom of crowds in transportation networks[J].EPL,2010,91(4):48002-48006.
[7]Roughgarden T.On the severity of Braess’s Paradox:Designing networks for selfish users is hard[J].Journal of Computer and System Sciences,2006,72(5):922-953.
[8]Bagloee S A,Ceder A,Tavana M,et al.A heuristic methodology to tackle the braess paradox detecting problem tailored for real road networks[J].Transportmetrica A:Transport Science,2014,10(5):437-456.
[9]SUN Li,LIU Like,XU Zhongzhi,et al.Locating inefficient links in a large-scale transport network[J].Physica A:Statistical Mechanics and its Applications,2015(419):537-545.
[10]William E S,Rapoport A,Darryl A S.Batch queues with choice of arrivals:Equilibrium analysis and experimental study[J].Games and Economic Behavior,2007,59(2):345-363.
[11]张薇薇.少即是多,从布雷斯悖论引出的话题[J].世界科学,2014(6):53-55.ZHANG Weiwei.Less is more,topics learn from Braess paradox[J].World Scientific,2014(6):53-55.
[12]Kube S,Selten R,Chmura T,et al.Commuters route choice behavior[J].Games and Economic Behavior,2007,58(2):394-406.
[13]Roughgarden T.Selfish routing and the price of anarchy[M].Cambridge:MIT Press,2005.
[14]Beckmann M J,Meguire C R,Winsten C B.Studies in the economics of transportation[M].New Haven:Yale University Press,1956.
[15]Frank M,Wolfe P.An algorithm for quadratic programming[J].Naval Research Logistics Quarterly,1956,3(1-2):95-110.
[16]张欢,卢毅,朱东铁.基于用户均衡分析的公路超限车辆补偿费率优化模型[J].铁道科学与工程学报,2012,9(6):84-89.ZHANG Huan,LU Yi,ZHU Dongtie.Optimization model on highway reimbursement rate of oversize vehicles with user equilibrium analysis[J].Journal of Railway Science and Engineering,2012,9(6):84-89.
[17]史峰,王英姿,徐光明,等.考虑支路路段双向车流相互影响的单向交通组织优化[J].铁道科学与工程学报,2012,9(2):66-71.SHI Feng,WANG Yingzi,XU Guangming,et al.Optimization approach for one-way traffic organization with bidirectional flow’s effect of local road[J].Journal of Railway Science and Engineering,2012,9(2):66-71.
[18]周和平,胡列格,晏克非.基于模糊路段流量的OD反推的不确定规划模型与算法研究[J].铁道科学与工程学报,2005,43(1):68-74.ZHOU Heping,HU Lieke,YANG Kefei.Uncertain programming model and algorithm for estimating origin-destination matrices based on fuzzy link flow[J].Journal of Railway Science and Engineering,2005,43(1):68-74.
[19]William A M,Nancy A M.Travel estimation techniques for urban planning(NCHRP Report 365)[M].Wasington,DC:National Academy Press,1998.
[20]胡列格,夏云,王佳,等.城市公共自行车高峰期需求不均衡的调度优化研究[J].铁道科学与工程学报,2015,12(2):441-448.HU Liege,XIA Yun,WANG Jia,et al.Scheduling optimization research on demand imbalance of urban public bicycles during peak period.[J].Journal of Railway Science and Engineering,2015,12(2):441-448.
[21]童晓进,符卓,刘勇,等.连续消耗应急物资调运问题研究[J].铁道科学与工程学报,2013,10(5):78-82.TONG Xiaojin,FU Zhuo,LIU Yong,et al.Study of emergency material dispatch of the continuous consumption[J].Journal of Railway Science and Engineering,2013,10(5):78-82.
[22]Navteq offciol welsike[DB/OL].http://www.navteq.com/,2016.7.4.
[23]US census bareat[DB/OL].http://www.census.gov/geo/www/tiger/tgrshp2010/tgrshp20 10.html,2016.7.4.