基于出行行为的择路演化相关问题研究
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摘要
交通流量是研究交通问题的必要因素,而交通流量的形成离不开出行者的参与。出行者具有主观意愿、理性判断以及差异性等特点,分析出行者的心理特点以及判断过程并建立出行者出行路径选择模型,有助于研究路网上交通流量的形成、特征以及影响因素等问题。基于模型模拟出行的演化过程,可以分析和掌握路网交通流量的详细特征以及变化趋势,从而可以为各种交通控制和管理措施提供参考和依据。因此,研究出行者择路演化问题具有重要的理论价值和现实意义。
围绕出行者择路演化相关问题,论文主要进行了如下研究工作：
1、本文在Logit累计更新规则基础上设计了Logit加权更新规则、Logit加权平均更新规则和Probit累计更新规则。分析了OD量固定以及变化时演化结果的稳定性,并与UE、SUE结果进行对比分析。当OD需求为随机变量或者出行成本的函数时,进一步改进择路模型并对其进行演化分析。结果发现当OD量所服从分布的方差一定时,均值的变化会影响演化达到稳定的速度,也会影响路径流量演化的结果。当均值大到一定程度时,出行者选择路径的理性程度变低。当OD量与出行成本相关时,出行者更加理性,路网流量更加稳定。
2、考虑到实际出行中多种交通方式并存的情况,为了避免Logit模型的IIA特性,引入巢式Logit模型。通过研究出行者的特征、行为以及影响出行决策的ATIS信息,对出行者出行方式选择和路径选择进行建模。对比分析不同出行方式的演化收敛特征,并分析其中各参数的变化规律,研究发现公交车出行的随机性越大,选择公交车出行的数量越少；在本部分模型基础上,考虑政府参与下多种出行方式的演化特征,分析其中规律及原因,得出过度的加大政策力度,效果反而变差等结论。
3、研究拥挤收费对出行选择的影响,建立基于路段的收费模型,调节收费的大小分析择路演化的变化。考虑多种交通方式并存时,建立对小汽车收费的演化模型。通过模拟分析发现,当出行受到收费的影响大于路径流量的影响时,出行者基本不参考路网的状况,而是根据收费程度来选择出行路径,造成演化偏离了自适应性。研究各出行方式的演化特征,得出实行对小汽车收费的政策可以有效地减少小汽车出行量并增加公家车出行量,以及收费力度与实施效果之间呈线性关系等。
The traffic flow is the necessary factor to the traffic problem, which cannot be separated from the travelers. The travelers have the characteristics of subjective apiration, rational judgment, difference and so on. The analysis of psychological characteristics and judgment process and the establishment of the route choice models are conducive to research formation, characteristics and the influence factors of the traffic flow on road network. Based on the evolution process, we can analyze many factors in the travel process. Thus it can provide reference and basis for for traffic control and management. Research on the route choice evolution problems has important theoretic value and practical significance.
Around related problems about the route choice evolution, this paper focused on the research as followed:
1、In this paper the Logit weighted updated rules, the Logit weighted average updated rules and the Probit accumulative updated rules are designed based on the cumulative Logit update rules. The stability of the evolution results is analyzed when the OD quantity is fixed or variational, and the results are compared and analyzed with the flows of SUE and UE. When the OD demands are random variables or the function of the travel cost, the model is further improved. For the fixed variance of the OD demands, the changing mean can affect the speed of achieving stability and the flow. If it get big enough, the rational degree of the travelers will reduce. When the change of the OD demand change is related with the function of the travel cost, the travelers are more rational and the network flows are more stable.
2、Considering the multiple travel modes in the ordinary life, the nested Logit model is introduced in order to avoid the characteristics of the IIA Logit model. The model that describes travelers' choice about travel mode and route by being studied the characteristics, behavior and the ATIS which influences the decision. With comparing the evolution characteristics of different travel modes and analyzing the various parameters it can be concluded that the flow of the bus is smaller when the the randomness of travel is more obvious. Considering the evolution characteristics of the multiple travel modes with the involvement of the government, the regularity and reason are analyzed. That shows that results become bad if the excessive of the policy efforts is excessive strengthened.
3、Research the influence of the congession pricing and establish modes based on the path and section. Analyze the evolution of the route choice by adjusting the extent of the congession pricing. If there exsit different travel modes, we can establish the mode with pricing on car. It is concluded that the travelers choose the route according to the level of the pricing not to the state of the network when the influence of the pricing is big enough;the flow of the car become small and the flow of the bus become big if the car was priced. Also, it can be concluded that there is a linear relationship between the pricing strength and the implementation result, etc.
围绕出行者择路演化相关问题,论文主要进行了如下研究工作：
1、本文在Logit累计更新规则基础上设计了Logit加权更新规则、Logit加权平均更新规则和Probit累计更新规则。分析了OD量固定以及变化时演化结果的稳定性,并与UE、SUE结果进行对比分析。当OD需求为随机变量或者出行成本的函数时,进一步改进择路模型并对其进行演化分析。结果发现当OD量所服从分布的方差一定时,均值的变化会影响演化达到稳定的速度,也会影响路径流量演化的结果。当均值大到一定程度时,出行者选择路径的理性程度变低。当OD量与出行成本相关时,出行者更加理性,路网流量更加稳定。
2、考虑到实际出行中多种交通方式并存的情况,为了避免Logit模型的IIA特性,引入巢式Logit模型。通过研究出行者的特征、行为以及影响出行决策的ATIS信息,对出行者出行方式选择和路径选择进行建模。对比分析不同出行方式的演化收敛特征,并分析其中各参数的变化规律,研究发现公交车出行的随机性越大,选择公交车出行的数量越少；在本部分模型基础上,考虑政府参与下多种出行方式的演化特征,分析其中规律及原因,得出过度的加大政策力度,效果反而变差等结论。
3、研究拥挤收费对出行选择的影响,建立基于路段的收费模型,调节收费的大小分析择路演化的变化。考虑多种交通方式并存时,建立对小汽车收费的演化模型。通过模拟分析发现,当出行受到收费的影响大于路径流量的影响时,出行者基本不参考路网的状况,而是根据收费程度来选择出行路径,造成演化偏离了自适应性。研究各出行方式的演化特征,得出实行对小汽车收费的政策可以有效地减少小汽车出行量并增加公家车出行量,以及收费力度与实施效果之间呈线性关系等。
The traffic flow is the necessary factor to the traffic problem, which cannot be separated from the travelers. The travelers have the characteristics of subjective apiration, rational judgment, difference and so on. The analysis of psychological characteristics and judgment process and the establishment of the route choice models are conducive to research formation, characteristics and the influence factors of the traffic flow on road network. Based on the evolution process, we can analyze many factors in the travel process. Thus it can provide reference and basis for for traffic control and management. Research on the route choice evolution problems has important theoretic value and practical significance.
Around related problems about the route choice evolution, this paper focused on the research as followed:
1、In this paper the Logit weighted updated rules, the Logit weighted average updated rules and the Probit accumulative updated rules are designed based on the cumulative Logit update rules. The stability of the evolution results is analyzed when the OD quantity is fixed or variational, and the results are compared and analyzed with the flows of SUE and UE. When the OD demands are random variables or the function of the travel cost, the model is further improved. For the fixed variance of the OD demands, the changing mean can affect the speed of achieving stability and the flow. If it get big enough, the rational degree of the travelers will reduce. When the change of the OD demand change is related with the function of the travel cost, the travelers are more rational and the network flows are more stable.
2、Considering the multiple travel modes in the ordinary life, the nested Logit model is introduced in order to avoid the characteristics of the IIA Logit model. The model that describes travelers' choice about travel mode and route by being studied the characteristics, behavior and the ATIS which influences the decision. With comparing the evolution characteristics of different travel modes and analyzing the various parameters it can be concluded that the flow of the bus is smaller when the the randomness of travel is more obvious. Considering the evolution characteristics of the multiple travel modes with the involvement of the government, the regularity and reason are analyzed. That shows that results become bad if the excessive of the policy efforts is excessive strengthened.
3、Research the influence of the congession pricing and establish modes based on the path and section. Analyze the evolution of the route choice by adjusting the extent of the congession pricing. If there exsit different travel modes, we can establish the mode with pricing on car. It is concluded that the travelers choose the route according to the level of the pricing not to the state of the network when the influence of the pricing is big enough;the flow of the car become small and the flow of the bus become big if the car was priced. Also, it can be concluded that there is a linear relationship between the pricing strength and the implementation result, etc.
引文
[1]国家统计局北京调查总队.北京市2009年国民经济和社会发展统计公报.北京市统计局,http://www.bjstats.gov.cn/xwgb/tjgb/ndgb/201002 /t20100202165217.htm,2010-02-02
[2]王刘芳.京城每百户家庭拥有36辆汽车.北京市统计局.http://www.chinadaily.com.cn/dfpd/2010-04/06/content_9690238.htm,2010-04-06
[3]2009福田指数-北京交通拥堵经济成本“再居榜首”http://www.tranbbs.com/Techarticle/TPlan/Techarticle_63752.shtml,2010-01-07
[4]中国新闻网.2009年全国道路交通事故http://www.chinanews.com.cn/gn/news/2010/01-09/2063204.shtml,2010-01-09
[5]杨佩昆.智能交通运输系统体系结构[M].上海：同济大学出版社,2001
[6]杨兆升.城市交通流诱导系统理论与模型[M].北京：人民交通出版社,2000
[7]刘天亮,欧阳恋群,黄海军ATIS作用下的混合交通行为网络与效率损失上界[J].系统工程理论与实践,2007,27(4)：154-159
[8]Hirsh, J.N.Prashker and M.Ben-Akiva. Dynamic Model of Weekly Activity Pattern[J].Transportation Science,1986,20(1):121-157
[9]Joan Walker, Moshe Ben-mkiva. Generalized Random Utility Model[J].Mathematical Social Sciences,2002,(43):303-343
[10]李民.基于活动链的居民出行行为分析[D].吉林：吉林大学,2004：1-39
[11]石小法,王炜,杨东援.信息对出行者出行行为的影响研究.中国公路学报,2002,15(1)：89-92
[12]柯有华,云美萍.城市出行选择行为机理研究.交通运输工程与信息学报.2007,5(2)：95-102
[13]罗国青,谷正气,杨易,容哲.基于出行者行为特性的自适应最优路径评价.机械与电子,2006(12)：6-8
[14]张萌,孙全欣,陈金川,郭继孚.北京市女性出行行为研究.交通运输系统工程与信息.2008,8(2)：19-26
[15]张政,毛保华,刘明君,陈金川,郭继孚.北京老年人出行行为特征分析.交通运输系统工程与信息,2007,7(6)：11-20
[16]范文博,李志纯,蒋葛夫.基于参考依赖法的出行者日常路径选择行为建模.交通运输工程学报,2009,9(1)：96-108
[17]安实,李静,崔建勋.面向多智能体的出行前信息下通勤者出行行为研究.中国公路学报,2009,22(3)：95-100
[18]邵春福.交通规划原理[M].北京：中国铁道出版社,2004
[19]Fisk C.Some developments in equilibrium traffic assignment methodology[J].Transportation Research Part B,1980,14:243-256
[20]Daganzo C., Sheffi Y.On stochastic models of traffic assignment[J].Transportation Science,1977,11:253-274
[21]Iida Y,Bell M.G.H..The Network Reliability of Transport [M].Elsevier,Oxford,2003
[22]Yang H. Liu H. A new modeling framework for travelers' day-to-day Route choice adjustment process [A].Allsop R.E.,Bell M.G.H.,Heydecker B.G.(Eds.)Transportation and Traffic Theory [C],Elsevier,2007:813-837
[23]Yang F.An Evolutionary Game Theory Approach to the Day-to-day Traffic Dynamics[D].Dissertation,University of Wisconsim-Madision,2005
[24]郑容森,谭惠丽,孔令江,刘慕仁.双车道多速车辆混合交通流元胞自动机模型的研究,物理学报,2005,54：3516
[25]付传技,汪秉宏,殷传洋,高坤.利用智能决策的双通道交通流[J].物理学报,55：403
[26]Davis G.A.,Nihan N.L..Large population approximation of a general stochastic traffic assignment model [J].Operations Research,1993,41:169-178
[27]Selten R,Chmura T,Pitz T,Kube S.Commuters route choice behavior [J].Games and Economic Behavior,2007,58:394-406
[28]Klugl F.Bazzan A.L.C.Route decision behavior in a commuting scenario:Simple heuristics adaptation and effect of traffic forecast [J]. Journal of Artificial Societies and Social Simulation,2004,7(1):1
[29]Klugl F,Bazzan A.L.C.Simulation studies on adaptive route decision and the influence of information on commuter scenarios [J] Journal of Intelligent Transportation System,2004,8:223-232
[30]Klugl F,Bazzan A.L.C.Learning to behave socially and avoid the braess paradox in a commuting scenario [A].5th Workshop on Decision Theoretic and Game Theoretic Agent [C],2003:107-112
[31]Klugl F,Bazzan A L C.Case studies on the braess paradox:Simulating route recommendation and learning in abstract and microscopic models[J].Transportation Research Part C,2005,13(4):299-319
[32]Noland R.B.Commuter response to travel time uncertainty under congested conditions:expected costs and the provision of information [J].Journal of Urban Economics,1997,41:377-406
[33]黄海军,欧阳恋群,刘天亮.交通网络中用户均衡行为的效率损失上界[J].北京航空航天大学学报,2006,32(10)：1215-1219
[34]黄海军,吴文祥.交通事故信息发布的有效性分析[J].系统工程理论方法应用,2001,10(4)：298-301
[35]Cantarella G.E,Cascetta E.Dynamic processes and equilibrium in transportation network:towards a unifying theory [J].Transportation Science,1995,29:305-329
[36]Watling D.Stability of the stochastic equilibrium assignment problem:A dynamical systems approach [J].Transportation Research Part B,1999,33(4):281-312
[37]熊轶,黄海军,李志纯.交通信息系统作用下的随机用户均衡模型与演进[J].交通运输系统工程与信息,2003,3(3)：44-48
[38]李振龙.诱导条件下驾驶员路径选择行为的演化博弈分析[J].交通运输系统工程与信息,2003,3(2)：23-27
[39]安实,崔娜,李静.基于多智能体博弈的路径选择策略仿真研究[J].交通信息与安全,2009,27(3)：1-5
[40]Jha M,Madanat S,Peeta S.Perception updating and day-to-day travel choice dynamics in traffic networks with information provision[J].Transportation Research Part C,1998,6(3):189-212
[41]刘天亮,黄海军.2005可持续发展的中国交通[M].北京：中国铁道出版社,2005：71
[42]刘天亮,黄海军,陈剑.考虑风险规避和认知更新的日常择路行为演进[J].交通运输工程学 报,2007,8(4)
[43]刘灿齐.现代交通规划学[M].北京：人民交通出版社,2001：174-180
[44]陈艳艳,刘小明,陈金川.城市交通需求管理及应用.北京：人民交通出版社,2009
[45]石建军.交通行为控制原理.北京：人民交通出版社,2009
[46]陆化普,黄海军.交通规划理论研究前沿.北京：清华大学出版社,2007,4
[47]石小法,王炜,杨东援.信息对出行者出行行为的影响研究[J].中国公路学报,2002,15(1)：89-92
[48]黄海军.城市交通网络平衡分析-理论与实践.北京：人民交通出版社,1994,10
[49]周晶.城市交通系统分析与优化.南京：东南大学出版社,2001
[50]刘天亮.信息作用下交通博弈均衡及其经济行为研究[D].北京：北京航空航天大学博士学位论文,2008
[51]胡华,滕靖,高云峰,周雪梅.多模式公交信息服务条件下的出行方式选择行为研究[J].中国公路学报,2009,22(2)：87-92
[52]肖海燕,王先甲.政府参与模式下出行者出行方式选择行为的演化博弈分析[J].管理工程学报,2010,24(2)：115-118
[2]王刘芳.京城每百户家庭拥有36辆汽车.北京市统计局.http://www.chinadaily.com.cn/dfpd/2010-04/06/content_9690238.htm,2010-04-06
[3]2009福田指数-北京交通拥堵经济成本“再居榜首”http://www.tranbbs.com/Techarticle/TPlan/Techarticle_63752.shtml,2010-01-07
[4]中国新闻网.2009年全国道路交通事故http://www.chinanews.com.cn/gn/news/2010/01-09/2063204.shtml,2010-01-09
[5]杨佩昆.智能交通运输系统体系结构[M].上海：同济大学出版社,2001
[6]杨兆升.城市交通流诱导系统理论与模型[M].北京：人民交通出版社,2000
[7]刘天亮,欧阳恋群,黄海军ATIS作用下的混合交通行为网络与效率损失上界[J].系统工程理论与实践,2007,27(4)：154-159
[8]Hirsh, J.N.Prashker and M.Ben-Akiva. Dynamic Model of Weekly Activity Pattern[J].Transportation Science,1986,20(1):121-157
[9]Joan Walker, Moshe Ben-mkiva. Generalized Random Utility Model[J].Mathematical Social Sciences,2002,(43):303-343
[10]李民.基于活动链的居民出行行为分析[D].吉林：吉林大学,2004：1-39
[11]石小法,王炜,杨东援.信息对出行者出行行为的影响研究.中国公路学报,2002,15(1)：89-92
[12]柯有华,云美萍.城市出行选择行为机理研究.交通运输工程与信息学报.2007,5(2)：95-102
[13]罗国青,谷正气,杨易,容哲.基于出行者行为特性的自适应最优路径评价.机械与电子,2006(12)：6-8
[14]张萌,孙全欣,陈金川,郭继孚.北京市女性出行行为研究.交通运输系统工程与信息.2008,8(2)：19-26
[15]张政,毛保华,刘明君,陈金川,郭继孚.北京老年人出行行为特征分析.交通运输系统工程与信息,2007,7(6)：11-20
[16]范文博,李志纯,蒋葛夫.基于参考依赖法的出行者日常路径选择行为建模.交通运输工程学报,2009,9(1)：96-108
[17]安实,李静,崔建勋.面向多智能体的出行前信息下通勤者出行行为研究.中国公路学报,2009,22(3)：95-100
[18]邵春福.交通规划原理[M].北京：中国铁道出版社,2004
[19]Fisk C.Some developments in equilibrium traffic assignment methodology[J].Transportation Research Part B,1980,14:243-256
[20]Daganzo C., Sheffi Y.On stochastic models of traffic assignment[J].Transportation Science,1977,11:253-274
[21]Iida Y,Bell M.G.H..The Network Reliability of Transport [M].Elsevier,Oxford,2003
[22]Yang H. Liu H. A new modeling framework for travelers' day-to-day Route choice adjustment process [A].Allsop R.E.,Bell M.G.H.,Heydecker B.G.(Eds.)Transportation and Traffic Theory [C],Elsevier,2007:813-837
[23]Yang F.An Evolutionary Game Theory Approach to the Day-to-day Traffic Dynamics[D].Dissertation,University of Wisconsim-Madision,2005
[24]郑容森,谭惠丽,孔令江,刘慕仁.双车道多速车辆混合交通流元胞自动机模型的研究,物理学报,2005,54：3516
[25]付传技,汪秉宏,殷传洋,高坤.利用智能决策的双通道交通流[J].物理学报,55：403
[26]Davis G.A.,Nihan N.L..Large population approximation of a general stochastic traffic assignment model [J].Operations Research,1993,41:169-178
[27]Selten R,Chmura T,Pitz T,Kube S.Commuters route choice behavior [J].Games and Economic Behavior,2007,58:394-406
[28]Klugl F.Bazzan A.L.C.Route decision behavior in a commuting scenario:Simple heuristics adaptation and effect of traffic forecast [J]. Journal of Artificial Societies and Social Simulation,2004,7(1):1
[29]Klugl F,Bazzan A.L.C.Simulation studies on adaptive route decision and the influence of information on commuter scenarios [J] Journal of Intelligent Transportation System,2004,8:223-232
[30]Klugl F,Bazzan A.L.C.Learning to behave socially and avoid the braess paradox in a commuting scenario [A].5th Workshop on Decision Theoretic and Game Theoretic Agent [C],2003:107-112
[31]Klugl F,Bazzan A L C.Case studies on the braess paradox:Simulating route recommendation and learning in abstract and microscopic models[J].Transportation Research Part C,2005,13(4):299-319
[32]Noland R.B.Commuter response to travel time uncertainty under congested conditions:expected costs and the provision of information [J].Journal of Urban Economics,1997,41:377-406
[33]黄海军,欧阳恋群,刘天亮.交通网络中用户均衡行为的效率损失上界[J].北京航空航天大学学报,2006,32(10)：1215-1219
[34]黄海军,吴文祥.交通事故信息发布的有效性分析[J].系统工程理论方法应用,2001,10(4)：298-301
[35]Cantarella G.E,Cascetta E.Dynamic processes and equilibrium in transportation network:towards a unifying theory [J].Transportation Science,1995,29:305-329
[36]Watling D.Stability of the stochastic equilibrium assignment problem:A dynamical systems approach [J].Transportation Research Part B,1999,33(4):281-312
[37]熊轶,黄海军,李志纯.交通信息系统作用下的随机用户均衡模型与演进[J].交通运输系统工程与信息,2003,3(3)：44-48
[38]李振龙.诱导条件下驾驶员路径选择行为的演化博弈分析[J].交通运输系统工程与信息,2003,3(2)：23-27
[39]安实,崔娜,李静.基于多智能体博弈的路径选择策略仿真研究[J].交通信息与安全,2009,27(3)：1-5
[40]Jha M,Madanat S,Peeta S.Perception updating and day-to-day travel choice dynamics in traffic networks with information provision[J].Transportation Research Part C,1998,6(3):189-212
[41]刘天亮,黄海军.2005可持续发展的中国交通[M].北京：中国铁道出版社,2005：71
[42]刘天亮,黄海军,陈剑.考虑风险规避和认知更新的日常择路行为演进[J].交通运输工程学 报,2007,8(4)
[43]刘灿齐.现代交通规划学[M].北京：人民交通出版社,2001：174-180
[44]陈艳艳,刘小明,陈金川.城市交通需求管理及应用.北京：人民交通出版社,2009
[45]石建军.交通行为控制原理.北京：人民交通出版社,2009
[46]陆化普,黄海军.交通规划理论研究前沿.北京：清华大学出版社,2007,4
[47]石小法,王炜,杨东援.信息对出行者出行行为的影响研究[J].中国公路学报,2002,15(1)：89-92
[48]黄海军.城市交通网络平衡分析-理论与实践.北京：人民交通出版社,1994,10
[49]周晶.城市交通系统分析与优化.南京：东南大学出版社,2001
[50]刘天亮.信息作用下交通博弈均衡及其经济行为研究[D].北京：北京航空航天大学博士学位论文,2008
[51]胡华,滕靖,高云峰,周雪梅.多模式公交信息服务条件下的出行方式选择行为研究[J].中国公路学报,2009,22(2)：87-92
[52]肖海燕,王先甲.政府参与模式下出行者出行方式选择行为的演化博弈分析[J].管理工程学报,2010,24(2)：115-118