基于公交乘客流构成的公交调度优化研究
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摘要
伴随社会经济迅猛发展,城市交通拥堵问题日趋严重,公共交通地位日益突显。如何更加科学合理地制定公交调度方案,提高公交服务水平,达到缓解交通拥堵的目的,已成为当今城市发展中的一个重要课题。
本文通过对公交乘客流的构成进行分析来研究公交调度优化问题。主要是将公交乘客分为非准乘客与准乘客,然后分别针对非准乘客与准乘客所造成公交线路拥挤问题,各自建立公交调度优化模型。
首先,本文对公交乘客流的特性和公交乘客信息的采集方法进行了综述,分析了目前所采用的公交乘客流信息采集方法的优缺点,并拟用改进的公交IC卡乘客流信息采集方法来作为本文公交乘客流信息采集的方法。
接着,针对公交调度中所需要的客流信息,分析了公交乘客流信息处理的方法；针对乘客流构成的划分,设计了非准乘客和准乘客的判别方法。
最后,文章先是对公交车辆调度模式和确定的方法进行了分析；然后分别针对非准乘客与准乘客,选择合理的调度模式并建立公交调度优化模型。其中,针对非准乘客,本文建立了基于跨线联运调度模式的网络优化模型,并运用特定情况下的最长路算法对模型进行求解；针对准乘客,本文建立了基于区间车和全程车混合调度模式下的发车间隔优化模型,并运用遗传算法对模型进行求解。另外,在每个模型求解之后,文章中也都设计了算例对模型的可行性进行了验证。
With the rapid development of the society and economy, urban traffic congestion problems have been increasingly serious, public transport becomes ever more crucial. An important issue in current city development is how to alleviate traffic congestion with scientific and rational bus scheduling scheme and higher bus service level.
Optimal bus scheduling problems are researched by analyzing bus passenger flow constitutes. This paper divides bus passengers into transfer passengers and no-transfer passengers; establishes optimal bus dispatching models aiming at crowded bus lines caused by transfer passengers and no-transfer passengers.
First, this article discusses the characteristic of bus passenger flow and information collection method, analyzes the advantages and disadvantages of bus passengers flow information collection methods and employs improved IC card passenger flow information collection methods to as this paper bus passengers flow information collection methods.
Then, according to requisite message in bus dispatching, this paper analyzes the processing method of bus passengers flow information and formulates discrimination method of transfer passengers and no-transfer passengers.
Last, this paper analyzes bus scheduling model and its determining method. Choose reasonable scheduling model and establish bus scheduling optimization model respectively on transfer and no-transfer passengers. This paper establishes cross-line intermodal scheduling mode for the situation of more transfer passengers and uses longest path algorithm under particular circumstances to solve the model. For the other situation of more no-transfer passengers, this paper develops departure intervals optimization model based on mix scheduling model of zone scheduling and regular scheduling, uses genetic algorithm to solve the model next. In addition, examples are designed to verify the feasibility after every solved model.
本文通过对公交乘客流的构成进行分析来研究公交调度优化问题。主要是将公交乘客分为非准乘客与准乘客,然后分别针对非准乘客与准乘客所造成公交线路拥挤问题,各自建立公交调度优化模型。
首先,本文对公交乘客流的特性和公交乘客信息的采集方法进行了综述,分析了目前所采用的公交乘客流信息采集方法的优缺点,并拟用改进的公交IC卡乘客流信息采集方法来作为本文公交乘客流信息采集的方法。
接着,针对公交调度中所需要的客流信息,分析了公交乘客流信息处理的方法；针对乘客流构成的划分,设计了非准乘客和准乘客的判别方法。
最后,文章先是对公交车辆调度模式和确定的方法进行了分析；然后分别针对非准乘客与准乘客,选择合理的调度模式并建立公交调度优化模型。其中,针对非准乘客,本文建立了基于跨线联运调度模式的网络优化模型,并运用特定情况下的最长路算法对模型进行求解；针对准乘客,本文建立了基于区间车和全程车混合调度模式下的发车间隔优化模型,并运用遗传算法对模型进行求解。另外,在每个模型求解之后,文章中也都设计了算例对模型的可行性进行了验证。
With the rapid development of the society and economy, urban traffic congestion problems have been increasingly serious, public transport becomes ever more crucial. An important issue in current city development is how to alleviate traffic congestion with scientific and rational bus scheduling scheme and higher bus service level.
Optimal bus scheduling problems are researched by analyzing bus passenger flow constitutes. This paper divides bus passengers into transfer passengers and no-transfer passengers; establishes optimal bus dispatching models aiming at crowded bus lines caused by transfer passengers and no-transfer passengers.
First, this article discusses the characteristic of bus passenger flow and information collection method, analyzes the advantages and disadvantages of bus passengers flow information collection methods and employs improved IC card passenger flow information collection methods to as this paper bus passengers flow information collection methods.
Then, according to requisite message in bus dispatching, this paper analyzes the processing method of bus passengers flow information and formulates discrimination method of transfer passengers and no-transfer passengers.
Last, this paper analyzes bus scheduling model and its determining method. Choose reasonable scheduling model and establish bus scheduling optimization model respectively on transfer and no-transfer passengers. This paper establishes cross-line intermodal scheduling mode for the situation of more transfer passengers and uses longest path algorithm under particular circumstances to solve the model. For the other situation of more no-transfer passengers, this paper develops departure intervals optimization model based on mix scheduling model of zone scheduling and regular scheduling, uses genetic algorithm to solve the model next. In addition, examples are designed to verify the feasibility after every solved model.
引文
[1]Furth, P.G. and Wilson, N.M.(1981). Setting frequencies on bus routes:Theory and praetiee[J]. Transportation Research Record.818,1-7
[2]Avishai Ceder. Methods for reating bus timetables [J]. Transport Part A. Vol.21.No.1.1986: 59-83
[3]A. Adamski, A.Turnau. Simulation Support Tool for Real-Time Dispatching Control in Public Transport[J]. Transportation Research(Part A).1998,2(2):73-87
[4]Maged Dessouky, Randolph Hall, Ali Nowroozi, Karen Mourikas. Bus Dispatching at Timed Transfer Transit stations Using Bus Tracking Technology. Dept. of Industrial and Systems Engineering, University of Southern California, Los Angeles, May 26,1999: 20~25
[5]RobertL. Bertini and Ahmed M.El-Geneidy. Modeling Transit Trip Time Using Archived Bus Dispatch System Data[J]. Journal of transportation engineering.2004:56~67
[6]Gentile, Guido, Sang Nguyen, Stefano Pallottino. Route choice on transit networks with online information at stops[J].TransportationSci. 2005,39(3):289~297
[7]Tony Halim, Shao-Wei Lam, Loon-Ching Tang. Multiresponse optimization of dispatch rules for public bus services. Computers and Industrial Engineering[J].2009,56(1):77-86
[8]Leandro Margulis. Hurricane Evacuation Decision-Support Model for Bus Dispatch. Mayaguez, Puerto Rico. Fourth LACCEI International Latin American and Caribbean Conference for Engineering and Technology, Miami,2006:1-9
[9]陈学武,戴霄,陈茜.公交IC卡信息采集、分析与应用研究[J].土木工程学报.2004,37(2)：105-110
[10]赵骞.基于公交IC卡调查数据的公交调度优化研究[D].大连理工大学硕士学位论文.2007：25-40
[11]王春雨.公交客流数据分析的研究[D].河北工业大学硕士学位论文.2006：17-24
[12]陈芳.城市公交调度模型研究.中南公路工程[J].2005,30(2)：162-164
[13]孙文霞,宋倜,乔国会.公交调度中发车间隔控制研究[J].河北工业大学学报.2007,36(2)：89-93
[14]宋瑞,赵航.基于机会约束的公交调度研究[J].数学的实践与认识.2005,35(1)：85-95
[15]刘鑫,何世伟.基于随机相关机会规划的公交调度[J].交通标准化.2006,12：152-155
[16]任传祥,郇宜军,尹唱唱.基于遗传禁忌搜索算法的公交调度研究[J].山东科技大学学报.2008,27(4)：53-56
[17]张健,李文权.城市公交区间车调度优化模型及算法研究.2007第三届中国智能交通年会,中国上海,2007：91-99
[18]覃运梅.城市公交调度优化方法研究[D].合肥工业大学硕士学位论文.2006：10-19
[19]万先进.城市常规公交调度问题的研究[D].中南大学硕士学位论文.2011：27-40
[20]刘镇阳等.城市智能公共交通系统[M].中国铁道出版社,2005：9-15
[21]王炜,杨新苗,陈学武.城市公共交通系统规划方法与管理[M].科学出版社,2002：35-40
[22]朱晓宏,丁卫东,孙泰屹.公交客流信息采集技术研究[J].城市车辆.2005,1：55
[23]杨盛华.基于现代信息技术的公交客流数据采集方法及应用研究[D].吉林大学硕士学位论文.2009：15-19
[24]戴霄.基于公交IC卡信息的公交数据分析方法研究[D].东南大学硕士学位论文.2006：10
[25]戴霄,陈学武.单条公交线路的IC卡数据分析处理方法[J].城市交通.2005,3(4)：73-76
[26]北京公交公司.城市公共交通运营调度管理[M].中国铁道出版社,2001：10-15
[27]刘欢,李文权.城市公交调度中满载率问题的研究[J].交通运输工程与信息学报.2008,6(4)：104-108
[28]GB/T 12428—2005.客车装载质量计算方法[Z]
[29]吴海涛.基于ITS技术的城市公交运营调度系统优化研究[D].西南交通大学硕士学位论文.2005：20-25
[30]寇玮华.基于公交乘客流构成及流向分布变化态势的公交网络优化研究以及可实施方案设计[J].前沿动态.2010,2：10-16
[31]高永,邓小勇.基于IC卡数据的公交换乘识别方法.2007第三届中国智能交通年会,中国上海,2007：125-130
[32]莫露全,刘毅,蓝相格.城市公共交通运营管理[M].机械工业出版社,2004：30-40
[33]沈家军,王炜,陈俊.基于灰色马尔可夫模型的近期公交客流量预测[J].公路交通科技.2007,34(9)：120-123
[34]冯树民,李晓冬.公交客流生成预测的神经网络模型[J].交通运输系统工程与信息.2006,6(1)：68-71
[35]杨兆升.城市智能公共交通系统理论与方法[M].中国铁道出版社,2004：183-185
[36]吕林剑,杜先汉.常规公交跨线联运中联运站点选取方法研究[J].公路与汽运.2012,(1)：47-49
[37]甘爱英等.运筹学[M].第3版.清华大学出版社,2005：261-267
[38]焦永兰.管理运筹学[M].中国铁道出版社,2000：149-153
[39]Hillier F S, Ljebrman G J. Operations Research[M]. San Francisco:Holden-day,1970
[40]屈芝莲.一种有向图最长路的算法、灵敏度分析及其应用[J].科学技术与工程.2011,11(16)：3746-3749
[41]宋增民.有向图中最长路或圈[J].东南大学学报.1987,17(4)：137-141
[42]Dirac G A. Some Theorems on Abstract Graphs. Proc. Lond. soc.1952,2:68-81
[43]Monton M. Matthews, David P. Sumner. Longest Paths and cycles inK1,2-free Graphs[J]. J Graph Theory.1985,9:269-277
[44]D Karger, R Motwani and G D S Ramkmmar. On approximating the longest path in a graph. Algorithmica.1997,18(1):82-98
[45]寇玮华,晏秋.管理运筹学[M].西南交通大学出版社,2010：130-131
[46]杨秀华.基于准时客流信息的公交调度优化研究[D].吉林大学硕士学位论文.2008：53-56
[47]朱金寿,朱琪,杨勇刚.遗传算法在公交车调度优化中的应用[J].交通与计算机.2002,(3)：62-64
[48]高瑾,邓卫,季彦婕.基于状态空间神经网络的短期公交调度模型[J].交通运输工程与信息学报.2010,8(3)：82-86
[49]Jianming Hu, Xi Shi, Jingyan Song, ete. Optimal Design for Urban Mass Transit Net-work Based on Evolutionary Algorithm. Advances Natural Computation. First Inter-national Conferences, Changsha, China, August 27-29,2005:1089-1100
[50]Hoogendoorn S.P., Bevy P.H.L. Platoon-based multiclass modeling of multilane traffic flow. Networks and Spatial Economics.2001, (1):137~166
[51]Holland J H. Adaptation in Nature and Artificial Systems. Cambridge, MIT Press. 1992
[52]雷英杰,张善文等.遗传算法工具箱及应用[M].西安电子科技大学出版社,2005：45-58
[53]程功.基于公交到站时间预测的公交调度模型研究[D].华南理工大学硕士学位论文.2010：38-42
[2]Avishai Ceder. Methods for reating bus timetables [J]. Transport Part A. Vol.21.No.1.1986: 59-83
[3]A. Adamski, A.Turnau. Simulation Support Tool for Real-Time Dispatching Control in Public Transport[J]. Transportation Research(Part A).1998,2(2):73-87
[4]Maged Dessouky, Randolph Hall, Ali Nowroozi, Karen Mourikas. Bus Dispatching at Timed Transfer Transit stations Using Bus Tracking Technology. Dept. of Industrial and Systems Engineering, University of Southern California, Los Angeles, May 26,1999: 20~25
[5]RobertL. Bertini and Ahmed M.El-Geneidy. Modeling Transit Trip Time Using Archived Bus Dispatch System Data[J]. Journal of transportation engineering.2004:56~67
[6]Gentile, Guido, Sang Nguyen, Stefano Pallottino. Route choice on transit networks with online information at stops[J].TransportationSci. 2005,39(3):289~297
[7]Tony Halim, Shao-Wei Lam, Loon-Ching Tang. Multiresponse optimization of dispatch rules for public bus services. Computers and Industrial Engineering[J].2009,56(1):77-86
[8]Leandro Margulis. Hurricane Evacuation Decision-Support Model for Bus Dispatch. Mayaguez, Puerto Rico. Fourth LACCEI International Latin American and Caribbean Conference for Engineering and Technology, Miami,2006:1-9
[9]陈学武,戴霄,陈茜.公交IC卡信息采集、分析与应用研究[J].土木工程学报.2004,37(2)：105-110
[10]赵骞.基于公交IC卡调查数据的公交调度优化研究[D].大连理工大学硕士学位论文.2007：25-40
[11]王春雨.公交客流数据分析的研究[D].河北工业大学硕士学位论文.2006：17-24
[12]陈芳.城市公交调度模型研究.中南公路工程[J].2005,30(2)：162-164
[13]孙文霞,宋倜,乔国会.公交调度中发车间隔控制研究[J].河北工业大学学报.2007,36(2)：89-93
[14]宋瑞,赵航.基于机会约束的公交调度研究[J].数学的实践与认识.2005,35(1)：85-95
[15]刘鑫,何世伟.基于随机相关机会规划的公交调度[J].交通标准化.2006,12：152-155
[16]任传祥,郇宜军,尹唱唱.基于遗传禁忌搜索算法的公交调度研究[J].山东科技大学学报.2008,27(4)：53-56
[17]张健,李文权.城市公交区间车调度优化模型及算法研究.2007第三届中国智能交通年会,中国上海,2007：91-99
[18]覃运梅.城市公交调度优化方法研究[D].合肥工业大学硕士学位论文.2006：10-19
[19]万先进.城市常规公交调度问题的研究[D].中南大学硕士学位论文.2011：27-40
[20]刘镇阳等.城市智能公共交通系统[M].中国铁道出版社,2005：9-15
[21]王炜,杨新苗,陈学武.城市公共交通系统规划方法与管理[M].科学出版社,2002：35-40
[22]朱晓宏,丁卫东,孙泰屹.公交客流信息采集技术研究[J].城市车辆.2005,1：55
[23]杨盛华.基于现代信息技术的公交客流数据采集方法及应用研究[D].吉林大学硕士学位论文.2009：15-19
[24]戴霄.基于公交IC卡信息的公交数据分析方法研究[D].东南大学硕士学位论文.2006：10
[25]戴霄,陈学武.单条公交线路的IC卡数据分析处理方法[J].城市交通.2005,3(4)：73-76
[26]北京公交公司.城市公共交通运营调度管理[M].中国铁道出版社,2001：10-15
[27]刘欢,李文权.城市公交调度中满载率问题的研究[J].交通运输工程与信息学报.2008,6(4)：104-108
[28]GB/T 12428—2005.客车装载质量计算方法[Z]
[29]吴海涛.基于ITS技术的城市公交运营调度系统优化研究[D].西南交通大学硕士学位论文.2005：20-25
[30]寇玮华.基于公交乘客流构成及流向分布变化态势的公交网络优化研究以及可实施方案设计[J].前沿动态.2010,2：10-16
[31]高永,邓小勇.基于IC卡数据的公交换乘识别方法.2007第三届中国智能交通年会,中国上海,2007：125-130
[32]莫露全,刘毅,蓝相格.城市公共交通运营管理[M].机械工业出版社,2004：30-40
[33]沈家军,王炜,陈俊.基于灰色马尔可夫模型的近期公交客流量预测[J].公路交通科技.2007,34(9)：120-123
[34]冯树民,李晓冬.公交客流生成预测的神经网络模型[J].交通运输系统工程与信息.2006,6(1)：68-71
[35]杨兆升.城市智能公共交通系统理论与方法[M].中国铁道出版社,2004：183-185
[36]吕林剑,杜先汉.常规公交跨线联运中联运站点选取方法研究[J].公路与汽运.2012,(1)：47-49
[37]甘爱英等.运筹学[M].第3版.清华大学出版社,2005：261-267
[38]焦永兰.管理运筹学[M].中国铁道出版社,2000：149-153
[39]Hillier F S, Ljebrman G J. Operations Research[M]. San Francisco:Holden-day,1970
[40]屈芝莲.一种有向图最长路的算法、灵敏度分析及其应用[J].科学技术与工程.2011,11(16)：3746-3749
[41]宋增民.有向图中最长路或圈[J].东南大学学报.1987,17(4)：137-141
[42]Dirac G A. Some Theorems on Abstract Graphs. Proc. Lond. soc.1952,2:68-81
[43]Monton M. Matthews, David P. Sumner. Longest Paths and cycles inK1,2-free Graphs[J]. J Graph Theory.1985,9:269-277
[44]D Karger, R Motwani and G D S Ramkmmar. On approximating the longest path in a graph. Algorithmica.1997,18(1):82-98
[45]寇玮华,晏秋.管理运筹学[M].西南交通大学出版社,2010：130-131
[46]杨秀华.基于准时客流信息的公交调度优化研究[D].吉林大学硕士学位论文.2008：53-56
[47]朱金寿,朱琪,杨勇刚.遗传算法在公交车调度优化中的应用[J].交通与计算机.2002,(3)：62-64
[48]高瑾,邓卫,季彦婕.基于状态空间神经网络的短期公交调度模型[J].交通运输工程与信息学报.2010,8(3)：82-86
[49]Jianming Hu, Xi Shi, Jingyan Song, ete. Optimal Design for Urban Mass Transit Net-work Based on Evolutionary Algorithm. Advances Natural Computation. First Inter-national Conferences, Changsha, China, August 27-29,2005:1089-1100
[50]Hoogendoorn S.P., Bevy P.H.L. Platoon-based multiclass modeling of multilane traffic flow. Networks and Spatial Economics.2001, (1):137~166
[51]Holland J H. Adaptation in Nature and Artificial Systems. Cambridge, MIT Press. 1992
[52]雷英杰,张善文等.遗传算法工具箱及应用[M].西安电子科技大学出版社,2005：45-58
[53]程功.基于公交到站时间预测的公交调度模型研究[D].华南理工大学硕士学位论文.2010：38-42