城市轨道交通换乘站列车时刻表的协调和优化
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摘要
城市轨道交通作为城市公共交通的骨干,对于缓解城市道路交通拥堵,构建低碳、节能环保的出行方式,发挥着重要的作用。随着轨道交通的快速发展,轨道交通线路逐渐形成网络,而目前各线路基本独立运营、相互间的协调性不强,给乘客换乘带来不便,网络运营条件下的换乘协调成为研究的一项新课题。
本文以网络运营条件下,城市轨道交通模式内不同线路间换乘协调为研究内容,运用概率论和数理统计的方法,分别对同站台换乘和通道换乘条件下的时刻表优化问题进行建模,设计了模型求解的启发式算法。在建模之前,介绍了网络换乘协调的理论方法,研究了通道换乘走行时间的分布规律,以便为建模提供理论方法和数据支持。
首先分析了轨道交通网络中的换乘理论,对换乘进行了分类,介绍了国外有关换乘站布局、换乘协调组织等的规划思想和设计理念。然后,对通道换乘走行时间进行了抽样调查,从累积分布函数的角度,运用Weibull函数来描述换乘走行时间的分布,采用极大似然估计法对参数取值进行了估计。
在此研究基础上,运用定时换乘的思想和方法,分别对同站台换乘和通道换乘条件下,换乘站的列车时刻表进行了优化设计。同站台换乘协调中,将列车的周期性到达定义为列车到达方波脉冲,运用波的理论来分析列车的运行,建立了方波脉冲同步优化模型,通过调整方波脉冲的相位差,实现列车的同步到达；通道换乘协调中,对换乘等待时间进行了严格界定,以换乘等待时间最小为目标函数,建立了换乘协调优化模型,并设计了模型求解的遗传算法。最后,以北京地铁雍和宫站为例进行了案例研究。
研究结果表明,Weibull分布能较好地描述通道换乘走行时间,平峰时段对换乘站列车时刻表的协调优化更有意义,高峰时段不需要进行协调。方波脉冲能形象地描述列车的周期性到达,将列车运行视为波的传播,并用数学语言Fourier级数进行表达,提供了一种新的研究思路和方法。雍和宫站列车时间表经过优化后,单个乘客在研究时段内的平均换乘等待时间较现状减少了70s、减幅达到29.7%,总换乘等待时间减少了54145 s,折合15 h。本文设计的换乘协调模型和遗传算法对换乘站列车时刻表的优化是有效的,具有一定的实际适用性。
论文中图24幅,表10个,参考文献51篇。
Urban rail transit, as the backbone of urban public transit, plays an important part in relieving traffic jams and shaping low-carbon, energy conservation and environmental protection trip mode. With the rapid development of urban rail transit, transit network is formed from isolated lines; however, the operation of each line is independent and lack of coordination, which makes great inconvenious to passenger transfers. Thus, transfer coordination between different lines under network operation becomes a new research subject.
This paper studies the transfer coordination between different lines in urban rail transit under network operation. Using the probility theory and mathematical statistics method, the paper has proposed models for optimizing across-platform transfers and passage transfers respectively. Genetic Algorithm is designed to solve the optimization model. Besides, the network transfer optimization theories and methods have been introduced and transfer walking time in passage analysed to provide tools and data for modeling on transfer coordination.
Firstly, the paper analyses transfer theories in rail transit networks, including the planning principles and operation ideas of transfer classification, transfer station layout, transfer coordination from abroad. Meanwhile, sampling survey of transfer walking time in subway passages has been made and Weibull function is used to describe the walking time distribution from the perspective of Cumulative Distribution. Parameter values in Weibull function are derived through maximum likelihood estimation.
Secondly, transfer coordination models on across-platform transfers and passage transfers have been proposed to optimize schedules of transfer station. The arrivals of train are considered to be period square pulse, and the train operation is analysed using wave theory. Transfer synchronization is achieved by adjusting phase difference of square pulse to make trains arrive at transfer stations simultaneously under across platform transfers. To the passage transfers, transfer waiting time is strictly defined and used as objective function. The model of minimizing transfer waiting time is formulated and Genetic Algorithm is adopted to solve the problem.
Finally, a case study of scheduling optimization in Yonghegong Lama Temple transfer station is carried out using methods proposed by the paper.
The results of the paper suggest that Weibull function could well describe transfer walking time distribution in subway passages; timetable coordination in non-peak hours is worthier of optimization than peak hours; square pulse could vividly present the periodical arrivals of trains, the paper provides a new approach for rail scheduling by considering train movement as wave propagation and using mathematics function to express square pulse; case study shows that transfer waiting time per pedestrian has been reduced by 70 seconds (29.7%) and total transfer waiting time 54145 seconds, equivalent to 15 hours during study period after schedule optimization; the models and Genetic Algorithm proposed by the paper is effective to timetable optimization and could be applied to transfer coordination in actual urban rail transit networks.
本文以网络运营条件下,城市轨道交通模式内不同线路间换乘协调为研究内容,运用概率论和数理统计的方法,分别对同站台换乘和通道换乘条件下的时刻表优化问题进行建模,设计了模型求解的启发式算法。在建模之前,介绍了网络换乘协调的理论方法,研究了通道换乘走行时间的分布规律,以便为建模提供理论方法和数据支持。
首先分析了轨道交通网络中的换乘理论,对换乘进行了分类,介绍了国外有关换乘站布局、换乘协调组织等的规划思想和设计理念。然后,对通道换乘走行时间进行了抽样调查,从累积分布函数的角度,运用Weibull函数来描述换乘走行时间的分布,采用极大似然估计法对参数取值进行了估计。
在此研究基础上,运用定时换乘的思想和方法,分别对同站台换乘和通道换乘条件下,换乘站的列车时刻表进行了优化设计。同站台换乘协调中,将列车的周期性到达定义为列车到达方波脉冲,运用波的理论来分析列车的运行,建立了方波脉冲同步优化模型,通过调整方波脉冲的相位差,实现列车的同步到达；通道换乘协调中,对换乘等待时间进行了严格界定,以换乘等待时间最小为目标函数,建立了换乘协调优化模型,并设计了模型求解的遗传算法。最后,以北京地铁雍和宫站为例进行了案例研究。
研究结果表明,Weibull分布能较好地描述通道换乘走行时间,平峰时段对换乘站列车时刻表的协调优化更有意义,高峰时段不需要进行协调。方波脉冲能形象地描述列车的周期性到达,将列车运行视为波的传播,并用数学语言Fourier级数进行表达,提供了一种新的研究思路和方法。雍和宫站列车时间表经过优化后,单个乘客在研究时段内的平均换乘等待时间较现状减少了70s、减幅达到29.7%,总换乘等待时间减少了54145 s,折合15 h。本文设计的换乘协调模型和遗传算法对换乘站列车时刻表的优化是有效的,具有一定的实际适用性。
论文中图24幅,表10个,参考文献51篇。
Urban rail transit, as the backbone of urban public transit, plays an important part in relieving traffic jams and shaping low-carbon, energy conservation and environmental protection trip mode. With the rapid development of urban rail transit, transit network is formed from isolated lines; however, the operation of each line is independent and lack of coordination, which makes great inconvenious to passenger transfers. Thus, transfer coordination between different lines under network operation becomes a new research subject.
This paper studies the transfer coordination between different lines in urban rail transit under network operation. Using the probility theory and mathematical statistics method, the paper has proposed models for optimizing across-platform transfers and passage transfers respectively. Genetic Algorithm is designed to solve the optimization model. Besides, the network transfer optimization theories and methods have been introduced and transfer walking time in passage analysed to provide tools and data for modeling on transfer coordination.
Firstly, the paper analyses transfer theories in rail transit networks, including the planning principles and operation ideas of transfer classification, transfer station layout, transfer coordination from abroad. Meanwhile, sampling survey of transfer walking time in subway passages has been made and Weibull function is used to describe the walking time distribution from the perspective of Cumulative Distribution. Parameter values in Weibull function are derived through maximum likelihood estimation.
Secondly, transfer coordination models on across-platform transfers and passage transfers have been proposed to optimize schedules of transfer station. The arrivals of train are considered to be period square pulse, and the train operation is analysed using wave theory. Transfer synchronization is achieved by adjusting phase difference of square pulse to make trains arrive at transfer stations simultaneously under across platform transfers. To the passage transfers, transfer waiting time is strictly defined and used as objective function. The model of minimizing transfer waiting time is formulated and Genetic Algorithm is adopted to solve the problem.
Finally, a case study of scheduling optimization in Yonghegong Lama Temple transfer station is carried out using methods proposed by the paper.
The results of the paper suggest that Weibull function could well describe transfer walking time distribution in subway passages; timetable coordination in non-peak hours is worthier of optimization than peak hours; square pulse could vividly present the periodical arrivals of trains, the paper provides a new approach for rail scheduling by considering train movement as wave propagation and using mathematics function to express square pulse; case study shows that transfer waiting time per pedestrian has been reduced by 70 seconds (29.7%) and total transfer waiting time 54145 seconds, equivalent to 15 hours during study period after schedule optimization; the models and Genetic Algorithm proposed by the paper is effective to timetable optimization and could be applied to transfer coordination in actual urban rail transit networks.
引文
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[2]中国公路网.我国城市轨道交通发展现状[EB/OL]. http://www.chinahighway.com/news/2009/326805.php.2009-04-09.
[3]曲建,余凌曲.观点：解读我国城市轨道交通发展的现实选择[EB/OL]. http://www.p5w.net/news/xwpl/200912/t2743951.htm.2009-12-25.
[4]新华社.城市轨道交通在城市公共交通中所占比重逐渐增大[EB/OL]. http://www.gov.cn/jrzg/2008-11/07/content_1142735.htm.2008-11-07.
[5]Nigel H.M. Wilson. Lecture Notes of Public Transportation Service and Operations Planning, 1.258J/11.541J/ESD.226J [EB/OL]. MIT Open Courseware.
[6]姜帆.关于轨道交通需求预测与城市客运交通枢纽关系的研究[J].交通运输系统工程与信息,2001,1(4)：311-315.
[7]盛志前,赵波平.基于轨道交通换乘的枢纽交通设计方法研究[J].城市规划,2004,28(10)：87-90.
[8]袁振洲.城市轨道交通规划中与其它交通衔接问题的分析[J].科技导报(北京),2001(11)：48-50.
[9]Ting, C.J. Transfer Coordination in Transit Networks [D]. University of Maryland,1997.
[10]Chowdhury S.M., Chien S.I-Jy. Intermodal Transit System Coordination. Transportation Planning and Technology [J],2002,25 (4):257-287.
[11]Rapp, M H; Gehner, C D. Transfer optimization in an interactive graphic system for transit planning [J]. Transportation Research Record 619,1976,27-33.
[12]Andreasson, I. Volvo approach to computer-aided transportation planning [J]. Transportation Research Record 657, Transportation Research Board, Washington, D.C.,1977:9-14.
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[14]Lee, K.K.T. and Schonfeld, P.M. Optimal Slack Times for Timed Transfers at a Transit Terminal [J]. Journal of Advanced Transportation,1991,25 (3):281-308.
[15]James H. Bookbinder, Alain Desilets. Transfer Optimization in a Transit Network [J]. Transportation Science,1992,26 (2):106-118.
[16]Knoppers, P. and Muller, T. Optimized Transfer Opportunities in Public Transport [J]. Transportation Science,1995,29 (1):101-105.
[17]Partha Chakroborty, Kalyanmoy Deb, P. S. Subrahmanyam. Optimal Scheduling of Urban Transit Systems Using Genetic Algorithms [J]. Journal of Transportation Engineering,1995, 121 (6):544-553.
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[19]Chowdhury, S. M.and Chien, S.I-Jy. Optimization of Transfer Coordination for Intermodal Transit Networks [C]. Transportation Research Board 80th Annual Meeting, Washington D.C., USA,2001.
[20]Teodorovic D, Lucic P. Schedule synchronization in public transit using the Fuzzy Ant System [J]. Transportation Planning and Technology,2005,28(1):47-76.
[21]Ting CJ, Schonfeld P. Schedule coordination in a multiple hub transit network [J]. Journal of Urban Planning and Development,2005,131(2):112-124.
[22]Jeffrey, J. H.; Pierce, B.; Pate, A. Evaluation of the effectiveness of connection protection in improving successful light rail-to-bus transfers [J]. Transportation Research Record, 2005(1930):3-11.
[23]Verma A., Dhingra S.L. Developing Integrated Schedules for Urban Rail and Feeder Bus Operation [J]. Journal of Urban Planning and Development,2006,132 (3):138-146.
[24]Liebchen C. The First Optimized Railway Timetable in Practice [J]. Transportation Science, 2008,42(4):420-435.
[25]Wong.R. C. W, Yuen.T. W. Y, Fung. K.W, et al. Optimizing Timetable Synchronization for Rail Mass Transit [J]. Transportation Science,2008,42 (1):57-69.
[26]王秋平,李峰.城市其他客运交通换乘轨道交通协调探讨[J].西安建筑科技大学学报,2003,35(2)：136-139,150.
[27]罗雁云,董国鹏,陈薇萍.关于城市轨道交通换乘的几点思考[J].城市轨道交通研究,2004,7(6)：14-16.
[28]吴友梅,张秀媛.城市轨道交通的公交换乘问题与对策分析[J].铁道运输与经济,2005,27(8)：19-21.
[29]沙滨,袁振洲,缪江华,等.城市轨道交通换乘方式对比分析[J].城市交通,2006,4(2)：11-15.
[30]ZHANG H.Q, LI H. Optimization Research on Transfer between Urban Subway and Bus Based On the Adjacency Matrix[C]. International Conference on Transportation Engineering,2007: 2822-2827.
[31]张铭,徐瑞华.轨道交通网络列车衔接组织的递阶协调优化[J].系统工程,2007,25(9)：33-37.
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[3]曲建,余凌曲.观点：解读我国城市轨道交通发展的现实选择[EB/OL]. http://www.p5w.net/news/xwpl/200912/t2743951.htm.2009-12-25.
[4]新华社.城市轨道交通在城市公共交通中所占比重逐渐增大[EB/OL]. http://www.gov.cn/jrzg/2008-11/07/content_1142735.htm.2008-11-07.
[5]Nigel H.M. Wilson. Lecture Notes of Public Transportation Service and Operations Planning, 1.258J/11.541J/ESD.226J [EB/OL]. MIT Open Courseware.
[6]姜帆.关于轨道交通需求预测与城市客运交通枢纽关系的研究[J].交通运输系统工程与信息,2001,1(4)：311-315.
[7]盛志前,赵波平.基于轨道交通换乘的枢纽交通设计方法研究[J].城市规划,2004,28(10)：87-90.
[8]袁振洲.城市轨道交通规划中与其它交通衔接问题的分析[J].科技导报(北京),2001(11)：48-50.
[9]Ting, C.J. Transfer Coordination in Transit Networks [D]. University of Maryland,1997.
[10]Chowdhury S.M., Chien S.I-Jy. Intermodal Transit System Coordination. Transportation Planning and Technology [J],2002,25 (4):257-287.
[11]Rapp, M H; Gehner, C D. Transfer optimization in an interactive graphic system for transit planning [J]. Transportation Research Record 619,1976,27-33.
[12]Andreasson, I. Volvo approach to computer-aided transportation planning [J]. Transportation Research Record 657, Transportation Research Board, Washington, D.C.,1977:9-14.
[13]Abkowitz, M. Josef, R. Tozzi J.et al.Operational feasibility of timed transfer in transit systems [J]. Journal of Transportation Engineering,1987,113(2):168-177.
[14]Lee, K.K.T. and Schonfeld, P.M. Optimal Slack Times for Timed Transfers at a Transit Terminal [J]. Journal of Advanced Transportation,1991,25 (3):281-308.
[15]James H. Bookbinder, Alain Desilets. Transfer Optimization in a Transit Network [J]. Transportation Science,1992,26 (2):106-118.
[16]Knoppers, P. and Muller, T. Optimized Transfer Opportunities in Public Transport [J]. Transportation Science,1995,29 (1):101-105.
[17]Partha Chakroborty, Kalyanmoy Deb, P. S. Subrahmanyam. Optimal Scheduling of Urban Transit Systems Using Genetic Algorithms [J]. Journal of Transportation Engineering,1995, 121 (6):544-553.
[18]Corey J. Wong. Improving the Network Performance of Urban Transit Systems [D]. University of California, Berkeley,1997.
[19]Chowdhury, S. M.and Chien, S.I-Jy. Optimization of Transfer Coordination for Intermodal Transit Networks [C]. Transportation Research Board 80th Annual Meeting, Washington D.C., USA,2001.
[20]Teodorovic D, Lucic P. Schedule synchronization in public transit using the Fuzzy Ant System [J]. Transportation Planning and Technology,2005,28(1):47-76.
[21]Ting CJ, Schonfeld P. Schedule coordination in a multiple hub transit network [J]. Journal of Urban Planning and Development,2005,131(2):112-124.
[22]Jeffrey, J. H.; Pierce, B.; Pate, A. Evaluation of the effectiveness of connection protection in improving successful light rail-to-bus transfers [J]. Transportation Research Record, 2005(1930):3-11.
[23]Verma A., Dhingra S.L. Developing Integrated Schedules for Urban Rail and Feeder Bus Operation [J]. Journal of Urban Planning and Development,2006,132 (3):138-146.
[24]Liebchen C. The First Optimized Railway Timetable in Practice [J]. Transportation Science, 2008,42(4):420-435.
[25]Wong.R. C. W, Yuen.T. W. Y, Fung. K.W, et al. Optimizing Timetable Synchronization for Rail Mass Transit [J]. Transportation Science,2008,42 (1):57-69.
[26]王秋平,李峰.城市其他客运交通换乘轨道交通协调探讨[J].西安建筑科技大学学报,2003,35(2)：136-139,150.
[27]罗雁云,董国鹏,陈薇萍.关于城市轨道交通换乘的几点思考[J].城市轨道交通研究,2004,7(6)：14-16.
[28]吴友梅,张秀媛.城市轨道交通的公交换乘问题与对策分析[J].铁道运输与经济,2005,27(8)：19-21.
[29]沙滨,袁振洲,缪江华,等.城市轨道交通换乘方式对比分析[J].城市交通,2006,4(2)：11-15.
[30]ZHANG H.Q, LI H. Optimization Research on Transfer between Urban Subway and Bus Based On the Adjacency Matrix[C]. International Conference on Transportation Engineering,2007: 2822-2827.
[31]张铭,徐瑞华.轨道交通网络列车衔接组织的递阶协调优化[J].系统工程,2007,25(9)：33-37.
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