寒地城市冬季道路交通需求预测方法研究
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摘要
现代城市道路交通系统规划建设的科学性主要依托于道路交通需求预测的技术成果，为了提高道路交通需求预测的科学性和合理性，国内外城市都要花费大量人力和物力进行交通大调查，建立交通需求预测模型分析预测城市现状和未来的道路交通状况，为道路交通规划建设决策提供数据支持。由于交通大调查的费用较高，动辄千万，因此对于一般城市而言，十几年甚至是几十年才进行一次交通大调查，并且交通调查通常选择在夏季，以此调查数据建立的道路交通需求预测模型只能够预测分析城市夏季的交通状况。
在我国北方，寒地城市的气候特点决定了其交通在冬季和夏季具有不同的特点，冬季道路交通系统运行状况受交通供需、严寒天气、降雪等方面的影响较大，冬季与夏季交通运行状况有很大差异。因此，要想全面分析预测寒地城市冬夏两季交通状况，就需要进行冬季和夏季两次交通调查，分别建立冬季道路交通需求预测模型和夏季道路交通需求预测模型，这需要投入巨大的人力和物力，而一般寒地城市很难实现。根据实际调查，一般寒地城市冬季道路交通供需矛盾较夏季更为突出，对于寒地城市而言其交通规划建设主要依据冬季道路交通调查数据，因此需要建立冬季道路交通需求预测模型进行冬季道路交通需求预测。然而由于气候条件的影响，寒地城市开展大规模冬季交通调查十分困难，且冬季调查费用较夏季更为高昂，调查难以实现。而一般寒地城市特别是大城市都进行了夏季交通大调查，因此有必要深入研究寒地城市冬夏两季的交通运行规律，研究气候对交通模型中人、车、路等交通要素的影响，分析建立冬季交通需求预测模型的特定因素和条件，建立一套利用既有的夏季交通调查数据来建立冬季道路交通需求预测的方法。
冬季道路交通需求预测模型有广泛的应用空间，运用冬季道路交通需求预测模型不仅可以模拟冬季各类机动车辆在道路上的行驶状况，预测远景年道路交通流量状况，而且能够对近期交通建设项目进行科学排序，运用冬季道路交通需求预测结果还可以构造寒地城市中心区冬季停车需求与动态交通量关系模型。这样在不进行大规模冬季交通调查的前提下，就可以利用夏季交通调查数据构建冬季道路交通需求预测模型和中心区冬季停车需求预测模型。用此模型来模拟分析、预测冬季交通状况，既能节省大量的交通调查费用，又能提高交通需求预测的准确度，保证交通规划项目能够顺利推进。
论文依托黑龙江省自然科学基金项目和哈尔滨市综合交通规划项目，在总结吸纳国内外相关研究成果的基础上，利用哈尔滨市和大庆市有关调查数据，对寒地城市居民出行特征进行了深入分析，对寒地城市冬季道路交通需求预测的建立方法及应用进行了深入探讨。
论文详细论述了城市道路交通需求预测的方法、理论基础和适用条件，主要介绍了交通生成预测增长率法、原单位法及函数法，交通方式划分预测分担率曲线法和函数模型法，交通分布预测增长率法、重力模型法及机会模型法，交通分配预测固定需求分配、弹性需求分配及组合分配法等。论文详细分析了道路交通需求预测模型构成指标影响因素，根据道路交通需求预测模型的特性及指标选取的原则方法建立了道路交通需求预测模型的指标体系，提出了城市道路交通需求预测模型指标体系的41项具体指标，运用综合评价理论及敏感度分析方法分析冬季低温、降雪对模型指标的敏感程度，进一步筛选出冬季低温对模型建立有较大影响的18项具体指标。
论文对不同温度条件下的居民出行特征进行了调查分析，根据指标选取的方法、原则确定了居民出行特征构成指标的选取，进行了初夏时期、初春时期及寒冬时期的居民出行调查，对比分析了不同气候条件下居民出行的差异性。
根据典型寒地城市的调查数据得到了5种不同道路等级条件下5类不同摩擦系数的路面状态分级；通过调查分析低温常态道路条件下车辆运行速度及低温条件对交通流特性的影响程度，改进了寒地城市冬季道路路段车道通行能力的计算方法；根据低温常态路面对信号交叉口起动损失时间及车辆通过停止线平均间隔时间的影响，确立了低温常态路面条件下的典型交叉口通行能力的计算方法。
通过分析冬季低温、降雪等因素对出行生成模型、方式划分模型、交通分布模型以及交通分配模型构建要素及参数的影响，提出了寒地城市冬季居民出行生成模型；提出了采用非机动方式预划分方法建立冬季道路交通需求预测方式划分模型，建立了基于土地混杂度、公交可达性因子的非机动方式预划分线性回归模型；提出了寒地城市冬季道路交通需求预测以5阶原点距为特征向量的熵分布模型；在交通分配模型中提出了冬季道路延误函数的计算方法。
根据本文提出的寒地城市冬季道路交通需求预测方法，以哈尔滨为例建立了冬季道路交通需求预测模型，应用哈尔滨市冬季道路交通需求预测模型分析评价了哈尔滨市北环路高架方案的区域交通影响；应用冬季道路交通需求预测模型构建寒地城市中心区冬季停车需求与动态交通需求的关系模型，并利用哈尔滨市道里中心区的调查数据进行了模型的验证分析，应用效果良好。
The scientificity of modern city road traffic system planning and constructiondepends on technical achievement in road traffic demand forecasting research.Therefore, in order to improve the rationality and scientificity of road traffic demandprediction, domestic and overseas cities have spent lots of manpower and materialresources conducting traffic investigation, which is used to develop the traffic demandforecasting models. These models are employed to analyze the current and future trafficoperation situation in cities, this provides data supports for city road traffic systemplanning and construction decision making. However, because of traffic survey costinga lot, most cities conduct the traffic investigation every decade, or even decades.Moreover, almost all traffic surveys are carried out in summer, the collected data is onlyutilized to predict the traffic condition during summer season.
In Northern China, the features of cold climate in large cities determine that thetraffic has different characteristics in winter and summer. Winter road traffic systemperformance affected by various influence, like traffic supply and demand, the coldweather, snow and so on, is very diffident from that in summer. Therefore, in order topredict the future traffic conditions of cold climate city with the traffic model, it needsto create a different model of traffic demand forecasting for winter and summer, andcollect traffic survey data in different periods. Due to the impact of climatic conditions,carrying out a large-scale survey of traffic in cold climate city is very difficult. So it isnecessary to study the traffic laws governing the operation of the traffic in summer andwinter, and the impact of climate on human traffic models, vehicles, roads and othertransportation elements, to analyze these factors used for winter traffic demand forecast,and to deduce winter traffic demand according to the survey data collected in summer.Hence, one of the objectives of this study is proposed an approach to predict winter roadtraffic condition based on summer traffic relevant data.
Winter road traffic demand forecasting model has broad application space, whichnot only can simulate driving conditions of all kinds of motor vehicles in winter androad traffic conditions of vision year, but also help to sort recent transportationconstruction projects scientifically. The relationship of static parking demand anddynamic demand is investigated using the road traffic demand forecasts in winter. Inthis way, the road traffic demand and central district parking demand prediction can beobtained using the data collected in summer, even if traffic survey cannot be conductedin winter. The proposed model is used to analyze road traffic operation situation.Therefore, without such a large-scale survey of the winter traffic, we can build a winterroad travel demand forecasting model to simulate the actual traffic situation analysis ofthe winter, which can save a lot of traffic investigation costs and improve the accuracy of traffic demand forecasting to ensure the project can operate smoothly.
This paper relays on Natural Science Foundation of Heilongjiang Province andHarbin City Comprehensive Transportation Planning project. Based on the summary ofrelevant research results at home and abroad and using the data related to Harbin andDaqing, it discussed deeply about the method for establishing the travel demandforecasting model of cold climate city and parking demand model for urban centers inwinter.
In this paper, the prediction method of urban road traffic demand has beenelaborated. Traffic generation forecast method mainly includes growth rate method,original unit method and function method. Traffic mode prediction has two divisionmethods: divided by multilayer or monolayer and according to the service providers.The latter’ prediction methods mainly consist of sharing rate curve method and modelmethod. Traffic distribution forecast mainly contains growth rate method, gravity modelapproach and opportunity model approach. Traffic assignment model mainly includesfixed demand distribution, elastic demand forecasting and portfolio allocation. Atheoretical foundation for the application of the text is listed. This paper established aprediction indicator system according to the factors of road traffic demand forecastingmodel, created an index system of road traffic demand forecasting model based on thecharacteristics and the principle method of selecting indexes, and come up with the41specific indicators term of urban road traffic demand forecasting model. Usecomprehensive evaluation and sensitivity theory to analyze the sensitive degree of thewinter cold, snow to the model and further screened18specific indicators which have agreater impact on building the model.
The characteristics of residents’ trip under different temperature conditions is beinvestigated and analyzed to ensure the indicators of resident trip characteristicsconstitute according to the methodological principles of picking index. Then makesurvey of residents’trip during spring and summer alternate, winter and spring alternate,particularly cold period, and analyze the difference of residents’ trip between thedifferent temperature conditions.
According to the different winter city survey, this paper got the pavement conditiongrading of five road grades under five friction coefficient conditions, and the mainimpact of the low temperature to the vehicle through the survey of vehicles speed underlow normal road conditions. Through the existing road capacity calculation methods,correct and obtain the calculation method of road sections lane capacity in winter.Finally, according to the influence of low normal road to starting lost time ofintersection and average time interval of vehicle passing the stop line, establish acalculation method of typical intersection capacity under low normal road condition.
Through the analysis of impact of factors such as low temperature, snow and etc.on elements and parameters of building trip generation model, split model, traffic distribution model and traffic assignment model, the paper revised the original functionmodel. Then it set up the function model of residents-travel effect in cold city. And itput forward to the way of building the model of means of transportation in winter by themethod of preliminary classification of non-flexible means. The linear regression modelof preliminary classification of non-flexible means with factors of land-mixed degreeand bus accessibility was established; And the applicable model of road impedancefunction among traffic distribution model in cold city was proposed; The entropydistribution model based on the Eigen vector of five order origin moment wasestablished as well. Meanwhile, it gave the calculation method of delay function on thewinter road in traffic assignment model and proposed the method of traffic demandforecasting model on the road of cold city. Finally, the paper took Harbin for exampleand established the traffic demand forecasting model on winter road. Furthermore, theproposed model was utilized to analyze the effects on periphery traffic operation ofNorth loop overhead road in Harbin.
According to the travel demand forecasting model of cold climate city in winter,the winter road travel demand forecasting model was established, in Harbin, forexample. The regional traffic impact of North Ring Road elevated program in Harbinwas evaluated using the winter road travel demand forecasting model, and therelationship of static parking demand and dynamic demand was established. Using thedata of Daoli central area in Harbin made a validation of analytical which got a goodeffect.
在我国北方，寒地城市的气候特点决定了其交通在冬季和夏季具有不同的特点，冬季道路交通系统运行状况受交通供需、严寒天气、降雪等方面的影响较大，冬季与夏季交通运行状况有很大差异。因此，要想全面分析预测寒地城市冬夏两季交通状况，就需要进行冬季和夏季两次交通调查，分别建立冬季道路交通需求预测模型和夏季道路交通需求预测模型，这需要投入巨大的人力和物力，而一般寒地城市很难实现。根据实际调查，一般寒地城市冬季道路交通供需矛盾较夏季更为突出，对于寒地城市而言其交通规划建设主要依据冬季道路交通调查数据，因此需要建立冬季道路交通需求预测模型进行冬季道路交通需求预测。然而由于气候条件的影响，寒地城市开展大规模冬季交通调查十分困难，且冬季调查费用较夏季更为高昂，调查难以实现。而一般寒地城市特别是大城市都进行了夏季交通大调查，因此有必要深入研究寒地城市冬夏两季的交通运行规律，研究气候对交通模型中人、车、路等交通要素的影响，分析建立冬季交通需求预测模型的特定因素和条件，建立一套利用既有的夏季交通调查数据来建立冬季道路交通需求预测的方法。
冬季道路交通需求预测模型有广泛的应用空间，运用冬季道路交通需求预测模型不仅可以模拟冬季各类机动车辆在道路上的行驶状况，预测远景年道路交通流量状况，而且能够对近期交通建设项目进行科学排序，运用冬季道路交通需求预测结果还可以构造寒地城市中心区冬季停车需求与动态交通量关系模型。这样在不进行大规模冬季交通调查的前提下，就可以利用夏季交通调查数据构建冬季道路交通需求预测模型和中心区冬季停车需求预测模型。用此模型来模拟分析、预测冬季交通状况，既能节省大量的交通调查费用，又能提高交通需求预测的准确度，保证交通规划项目能够顺利推进。
论文依托黑龙江省自然科学基金项目和哈尔滨市综合交通规划项目，在总结吸纳国内外相关研究成果的基础上，利用哈尔滨市和大庆市有关调查数据，对寒地城市居民出行特征进行了深入分析，对寒地城市冬季道路交通需求预测的建立方法及应用进行了深入探讨。
论文详细论述了城市道路交通需求预测的方法、理论基础和适用条件，主要介绍了交通生成预测增长率法、原单位法及函数法，交通方式划分预测分担率曲线法和函数模型法，交通分布预测增长率法、重力模型法及机会模型法，交通分配预测固定需求分配、弹性需求分配及组合分配法等。论文详细分析了道路交通需求预测模型构成指标影响因素，根据道路交通需求预测模型的特性及指标选取的原则方法建立了道路交通需求预测模型的指标体系，提出了城市道路交通需求预测模型指标体系的41项具体指标，运用综合评价理论及敏感度分析方法分析冬季低温、降雪对模型指标的敏感程度，进一步筛选出冬季低温对模型建立有较大影响的18项具体指标。
论文对不同温度条件下的居民出行特征进行了调查分析，根据指标选取的方法、原则确定了居民出行特征构成指标的选取，进行了初夏时期、初春时期及寒冬时期的居民出行调查，对比分析了不同气候条件下居民出行的差异性。
根据典型寒地城市的调查数据得到了5种不同道路等级条件下5类不同摩擦系数的路面状态分级；通过调查分析低温常态道路条件下车辆运行速度及低温条件对交通流特性的影响程度，改进了寒地城市冬季道路路段车道通行能力的计算方法；根据低温常态路面对信号交叉口起动损失时间及车辆通过停止线平均间隔时间的影响，确立了低温常态路面条件下的典型交叉口通行能力的计算方法。
通过分析冬季低温、降雪等因素对出行生成模型、方式划分模型、交通分布模型以及交通分配模型构建要素及参数的影响，提出了寒地城市冬季居民出行生成模型；提出了采用非机动方式预划分方法建立冬季道路交通需求预测方式划分模型，建立了基于土地混杂度、公交可达性因子的非机动方式预划分线性回归模型；提出了寒地城市冬季道路交通需求预测以5阶原点距为特征向量的熵分布模型；在交通分配模型中提出了冬季道路延误函数的计算方法。
根据本文提出的寒地城市冬季道路交通需求预测方法，以哈尔滨为例建立了冬季道路交通需求预测模型，应用哈尔滨市冬季道路交通需求预测模型分析评价了哈尔滨市北环路高架方案的区域交通影响；应用冬季道路交通需求预测模型构建寒地城市中心区冬季停车需求与动态交通需求的关系模型，并利用哈尔滨市道里中心区的调查数据进行了模型的验证分析，应用效果良好。
The scientificity of modern city road traffic system planning and constructiondepends on technical achievement in road traffic demand forecasting research.Therefore, in order to improve the rationality and scientificity of road traffic demandprediction, domestic and overseas cities have spent lots of manpower and materialresources conducting traffic investigation, which is used to develop the traffic demandforecasting models. These models are employed to analyze the current and future trafficoperation situation in cities, this provides data supports for city road traffic systemplanning and construction decision making. However, because of traffic survey costinga lot, most cities conduct the traffic investigation every decade, or even decades.Moreover, almost all traffic surveys are carried out in summer, the collected data is onlyutilized to predict the traffic condition during summer season.
In Northern China, the features of cold climate in large cities determine that thetraffic has different characteristics in winter and summer. Winter road traffic systemperformance affected by various influence, like traffic supply and demand, the coldweather, snow and so on, is very diffident from that in summer. Therefore, in order topredict the future traffic conditions of cold climate city with the traffic model, it needsto create a different model of traffic demand forecasting for winter and summer, andcollect traffic survey data in different periods. Due to the impact of climatic conditions,carrying out a large-scale survey of traffic in cold climate city is very difficult. So it isnecessary to study the traffic laws governing the operation of the traffic in summer andwinter, and the impact of climate on human traffic models, vehicles, roads and othertransportation elements, to analyze these factors used for winter traffic demand forecast,and to deduce winter traffic demand according to the survey data collected in summer.Hence, one of the objectives of this study is proposed an approach to predict winter roadtraffic condition based on summer traffic relevant data.
Winter road traffic demand forecasting model has broad application space, whichnot only can simulate driving conditions of all kinds of motor vehicles in winter androad traffic conditions of vision year, but also help to sort recent transportationconstruction projects scientifically. The relationship of static parking demand anddynamic demand is investigated using the road traffic demand forecasts in winter. Inthis way, the road traffic demand and central district parking demand prediction can beobtained using the data collected in summer, even if traffic survey cannot be conductedin winter. The proposed model is used to analyze road traffic operation situation.Therefore, without such a large-scale survey of the winter traffic, we can build a winterroad travel demand forecasting model to simulate the actual traffic situation analysis ofthe winter, which can save a lot of traffic investigation costs and improve the accuracy of traffic demand forecasting to ensure the project can operate smoothly.
This paper relays on Natural Science Foundation of Heilongjiang Province andHarbin City Comprehensive Transportation Planning project. Based on the summary ofrelevant research results at home and abroad and using the data related to Harbin andDaqing, it discussed deeply about the method for establishing the travel demandforecasting model of cold climate city and parking demand model for urban centers inwinter.
In this paper, the prediction method of urban road traffic demand has beenelaborated. Traffic generation forecast method mainly includes growth rate method,original unit method and function method. Traffic mode prediction has two divisionmethods: divided by multilayer or monolayer and according to the service providers.The latter’ prediction methods mainly consist of sharing rate curve method and modelmethod. Traffic distribution forecast mainly contains growth rate method, gravity modelapproach and opportunity model approach. Traffic assignment model mainly includesfixed demand distribution, elastic demand forecasting and portfolio allocation. Atheoretical foundation for the application of the text is listed. This paper established aprediction indicator system according to the factors of road traffic demand forecastingmodel, created an index system of road traffic demand forecasting model based on thecharacteristics and the principle method of selecting indexes, and come up with the41specific indicators term of urban road traffic demand forecasting model. Usecomprehensive evaluation and sensitivity theory to analyze the sensitive degree of thewinter cold, snow to the model and further screened18specific indicators which have agreater impact on building the model.
The characteristics of residents’ trip under different temperature conditions is beinvestigated and analyzed to ensure the indicators of resident trip characteristicsconstitute according to the methodological principles of picking index. Then makesurvey of residents’trip during spring and summer alternate, winter and spring alternate,particularly cold period, and analyze the difference of residents’ trip between thedifferent temperature conditions.
According to the different winter city survey, this paper got the pavement conditiongrading of five road grades under five friction coefficient conditions, and the mainimpact of the low temperature to the vehicle through the survey of vehicles speed underlow normal road conditions. Through the existing road capacity calculation methods,correct and obtain the calculation method of road sections lane capacity in winter.Finally, according to the influence of low normal road to starting lost time ofintersection and average time interval of vehicle passing the stop line, establish acalculation method of typical intersection capacity under low normal road condition.
Through the analysis of impact of factors such as low temperature, snow and etc.on elements and parameters of building trip generation model, split model, traffic distribution model and traffic assignment model, the paper revised the original functionmodel. Then it set up the function model of residents-travel effect in cold city. And itput forward to the way of building the model of means of transportation in winter by themethod of preliminary classification of non-flexible means. The linear regression modelof preliminary classification of non-flexible means with factors of land-mixed degreeand bus accessibility was established; And the applicable model of road impedancefunction among traffic distribution model in cold city was proposed; The entropydistribution model based on the Eigen vector of five order origin moment wasestablished as well. Meanwhile, it gave the calculation method of delay function on thewinter road in traffic assignment model and proposed the method of traffic demandforecasting model on the road of cold city. Finally, the paper took Harbin for exampleand established the traffic demand forecasting model on winter road. Furthermore, theproposed model was utilized to analyze the effects on periphery traffic operation ofNorth loop overhead road in Harbin.
According to the travel demand forecasting model of cold climate city in winter,the winter road travel demand forecasting model was established, in Harbin, forexample. The regional traffic impact of North Ring Road elevated program in Harbinwas evaluated using the winter road travel demand forecasting model, and therelationship of static parking demand and dynamic demand was established. Using thedata of Daoli central area in Harbin made a validation of analytical which got a goodeffect.
引文
[1]陆建,王炜.从城市交通规划发展看城市交通可持续发展规划[J].华中科技大学学报,2003,(1):90-99
[2]马林,陆锡明,杨东援,杨涛.城市交通模型一席谈[J].城市交通,2008,6(1):50-53
[3]毛保华.交通规划模型及应用[M].北京:中国铁道出版社,1999,32-45
[4]李春艳.城市交通模型集锦[J].城市交通,2008,6(1):32-49
[5] Smith B L, Williams B M, Oswald R K. Comparison of Parametric andNonparametric Modesl for Traffic Flow Forecasting[J]. Transportation ResearchPart C,2002,10(8):303-321
[6]裴玉龙,李宏萍,蒋贤才.城市交通规划[M].中国铁道出版社,2007:122~129
[7] Usdot. Urban Tranrtation Planning in the United States,An HistoricalOverview[M]. Washington, D.C.USDOT,1992:38-52
[8]邹熙,焦国安,金霞.中美城市交通模型发展展望[J].城市交通,2008,6(2):83-86
[9] Chieh-Hua Wen, Frank S.Koppenlman.The generalized nested logit model [J].Transportation Research Part B.2001,(35):627-641
[10] Vovsha P.The cross-nested logit model: application to mode choice in theTel-Avivmetropolitanarea[J]. In Transportation research Record1607.TRB,1997(5):6-15
[11] C. R. Bhat. A heteroscedastic extreme value model of intercity travel modechoice [J]. Transp-ortation Research Part B.1995,29B (6):471-483
[12] D. McFadden and K. E. Train. Mixed mnl models for discrete response [J]. Journal of Applied Econometrics,2000,(5):447-470
[13] Swait J D, Ben-Akiva M. Incorporating Random Constraints in Discrete14Models of Choice Set Generation [J].1987,(21):318-351
[14] Jones P. Understanding Travel Behavioral [M]. Gower:Aldershot,1983:112-126.
[15] Gling. Household Activity Scheduling[M]. Gower:Aldershot,1989:235-248
[16] Axhausen K, Gling. Activity-Based Approaches to Travel Analysis [J]. TransporReviews,1992:323-341
[17]李霞.城市居民出行生成预测方法研究[D].长春:吉林大学学位论文,2004:44-52
[18]姚荣涵.城市居民出行生成预测方法研究[D].长春:吉林大学学位论文,2004:49-70
[19] Ettema D, Borgers A, Timmermans H. Simulation Model of Activity SchedulingHeuristics:empirical test and simulation issues[M].1995:323-341
[20] Jifeng Wu, Gang-Len Chang. An integrated optimal control and algorithm forcommuting corridors[J]. International Transactions in Operational Research,1999,6(1):39-55
[21] Mark E T, Horn. An extended model and procedural framework for planningmulti-modal passenger journeys[J]. Transportation Research,2003,2(1):31-37
[22] Ennio Cassette, Andrea Papola. A joint mode-transit service choice model Incorporating the effect of regional transport service timetables[J]. TransportationResearch,2003,2(1):18-25
[23]毛海虓.中国城市居民出行特征研究[D].北京:北京工业大学学位论文,2005:14-25
[24]李思鼎,陈国安.高原和高寒环境对车辆的影响分析[J].城市车辆技术与研究,2009,(2):43-45
[25] Petersen E R. A highway corridor planning model: QROAD [J].TransportationResearch Part A,2002,36(2):107-125
[26] Cambridge Systematics. Long-Term Availability of Multimodal Corridor Capacity[R]. England: Res.Agency,1996,11-24
[27] Bertsekas D P. A simple and fast label correcting algorithm for shortest paths[J].Networks,1993,23-30
[28] Ries G L. Impact of Weather on Freeway Capacity[R]. Minneapolis, MN:Minnesota Department of Transportation,1981:5-8
[29] Liang W L, Kyte M, Kitchener F. The Effect of Environmental Factors on DriverSpeed[J]. Transportation Research Record1635,1998(1):155-161
[30] Knapp K, Smithson L. The Use of Mobile Video Data Collection Equipment toInvestigate Winter Weather Vehicle Speeds. Transportation Research,2001,2(1):75-84
[31] Perrin J, Martin P T. Modifying Signal Timing During62Inclement Weather[J].In Transportation Research Record1748,2001(1):45-48
[32] Usharani Sankuri. Improvements in Small to Medium Sised Community TripGeneration[M]. The United states: The University of Alabama in Huntsville,2003:32-35
[33]陆化普.交通规划理论与方法[M].北京:清华大学出版社,1998:199-207
[34]文国玮.城市交通与道路系统规划[M].北京:清华大学出版社,2001:49-76
[35]李峰,陈永茂.大城市严重交通拥堵风险评估与应对策略[J].城市交通,2011,9(2):15-21
[36]褚伟,高永.城市交通枢纽的规划要点[J].城市交通,2005,2(1)35-37
[37]林雨,方守恩.灾害天气环境下高等级公路车速管理[J].自然灾害学报,2007,16(5):96-99
[38]高华.城市道路条件及环境对交通安全的影响研究[D].成都:西南交通大学学位论文,2007:24-35
[39]刘清.高速公路交通灾害预警管理系统研究[D].武汉:武汉理工大学学位论文,2004:22-28
[40]罗丽君,高晗,裴玉龙.冰雪道路条件下最小安全行车间距的确定.黑龙江交通科技[J],1999,38:33-34
[41]任园园.冰雪条件下城市道路交通流特性及管理对策研究[D].长春:吉林大学学位论文,2007:35-43
[42]蒋贤才,裴玉龙.寒冷地区道路交通安全特征及其管理措施分析[J].交通运输系统工程与信息,2007,7(4):82-89
[43]裴玉龙,盖春英.公路网络运营可靠度研究[J].公路交通科技,2005,22(5):119~123
[44]冷军强.冰雪条件下路网行程时间可靠性研究[D].哈尔滨:哈尔滨工业大学学位论文,2010:44-50
[45]冯雨芹,张春平.冰雪条件下城市道路路段行程时间模型[J].黑龙江工程学院学报.2011,25(1):29-31
[46]董苏华,章超汉.部分国家及地区停车问题研究[J].城市交通,1999,4:37-41.
[47]邹贞元,徐亚国,安实.城市静态交通管理理论与应用[M].广州出版社,2000:1~10
[48]王丰元，邹旭东.基于用地和交通特征的停车需求预测模型[J].交通运输工程学报,2007,4
[49]安实,王健,安实.停车需求预测与管理[J].系统工程理论与方法,2001,8:212~214
[50] Donald C. Shoup. The trouble with minimum parking requirements[J].Transportation Research Part A,1999,33:549-574
[51] An Shi, Han Bo, Wang Jian. A User’s Route Choice Behavior Model Based onReal-time Road Information[C].2004International Conference On ManagementScience&Engineering,2004,6:2565-2569
[52] An Shi, Han Bo, Wang Jian. Study of the Mode of Real-time and DynamicParking Guidance and Information Systems Based on Fuzzy ClusteringAnalysis[C]. Third International Conference on Machine Learning andCybernetics,2004:2790-2794
[53] An Shi, Han Bo, Wang Jian. Study on the Early-Warning and TransactionTechnology of Traffic Accidents[C]. The15thInternational Road Federation WorldMeeting,2005:1071-1075
[54] Lasdon L S, Luo S J. Computational Experiment wicha System Optimal DynamicTraffic Assignment Model[J]. Transpn.Res,1994,2C:109-127
[55] Larsson T, Patriksson M. A Class of Gap Function for Variational Ineequilities[J].Mathematical Programming,1994,64:53-79
[56] Jayakrishnan R, Tski K W. A Dynamic Traffic Assignment Model withTraffic-Flow Relationships[J]. Transpn. Res,1995,3(C):43-47
[57] Joel L Horouwitz. Reconsidering The Multinomial Probit Model[J]. Transpn. Res,1991,25(B):32-36
[58] Lam W H, Huang H J. A Combined Trip Distribution and Assignment Model forMultiple User Classes[J]. Transpn. Res,1992,26(B):21-26
[59] Lam W H K, Huang H J. Dynamic User Optimal Traffic Assignment Model forMany to Travel Demand[J]. Transpn. Res,1995,29(B):32-36
[60] Larsson T, Patriksson M. A Class of Gap Function for Variational Inequilities[J].Mathematical Programming,1994,25(A):32-36
[61] Lasdon L S, Luo S J. Computational Experiment with a System Optimal DynamicTraffic Assignment Model[J]. Transpn. Res,1994,2(C):17-21
[62] Wu Z X, Lam W H K. Combined Modal Split and Stochastic Assignment Modelfor Congested Networks with Motorized and Nonmotorized Transport Modes[J].Transportation Research Record,2003(1831):57-64
[63] Mahnasaani H S, Peeta S. Network Performance under System Optimal and UserEquilibrium Dynamic Assignment[J]. Transpn. Res,1993,11(C):25-27
[64] Siegel J D, Cea J D, Fernandez J E.Comparisons of Urban Travel ForecastsPrepared with the Sequential Procedure and Spatial Economics,2006(6):135-148
[65] Ran B, Boyce D E. A New Class Of Instantaneous Dynamic User Optimal TrafficAssignment Model[J]. Operations Research,1993,2(B):35-38
[66] Ran B,Hall W R. A Link-Based Variational Inequality Model for DynamicDeparture Time/Route Choice[J]. Transpn. Res,1996,30(B):18-21
[67] Murat Gene. Aggregation and Heterogenaty of Choice Set Generation[J]. Transpn.Res,1994,28(B):36-39
[68] Smith M J. A New Dynamic Traffic Assignment Model and the Existence andCalculation of Dynamic User Equilibria on Congested Capacity-Constrained RoadNetworks[J]. Transpn. Res,1993,27(B):35-37
[69]邵长桥,刘小明.交通预测原则和预测模型评价方法[J].道路及交通与安全,2007,15(2):45-48
[70]刘灿奇.现代交通规划学[M].北京:人民交通出版社,2001,105-118
[71]刘建明,陈金玉.基于土地利用的交通需求预测[J].交通科技与信息,2009,12(2):38-41
[72]毛宝华,曾会欣.交通规划模型及其应用[M].北京:中国铁道出版社,1999；116-121
[73] Zhang Z B. Mutualism or cooperation among competitors pro-Motes coexistenceand competitive ability[J]. Ecological Mod-elling,2003,9(2):42-45
[74] Hunt J D, Teply S. A nested logit model of parking location choice[J].Transportation Research Part B,1999,4:253-265
[75] Jha M, Madanat S, Peeta S. Perception updating and day-to-day travel choicedynamics in traffic networks with information provision[J]. Transportationresearch Part B.1998,6:189-212
[76] Boyce, David; Mattsson, Lars-G ran. Modeling residential location choice inrelation to housing location and road tolls on congested urban highway networks.Transportation research Part B.1999,8:581-591
[77] Cascetta E, Papola A. Random utility models with implicit availability/perceptionof choice alternatives for the simulation of travel demand[J]. Transportationresearch Part C,2001,4:249-263
[78]张军.城市交通系统可持续发展综合评价研究[D].成都:西南交通大学学位论文,2007:17-20
[79]王炜,陈学武.城市交通系统可持续发展理论体系研究[M].北京:科学出版社,2004:18-22
[80]梁颖.大城市道路交通系统运营状态评价[D].北京:北京工业大学学位论文,2002:25-28
[81]邵春福.交通规划原理[M].北京:中国铁道出版社,2008: pp:174-177
[82]郝海,踪家峰.系统分析与评价方法[M].北京:经济科学出版社,2007:70~100
[83] Tang Lian-Sheng, Cheng Wen-Ming. Vehicle Routing Problem with Travel TimeReliability Constrain[C]. International Conference on Transportation Engineering,2007: pp:1831-1836
[84] Mahnasaani H S, Jayakrishnan R. System Performance and user response underrealtime information in congested traffic corridor[J]. Transpn. Res,1991,25A:35-39
[85] Asakura Y. Evaluation of Networtk Reliability Using Stochastic User Equili-brium[J]. Journal of Advanced Transportation.,1999,33(2):147-158
[86] Zhihua Xiong, Chunfu Shao, Zhisheng Yao. Integrated Method for Road NetworkReliability Under Stochastic Demand[C].5th International Conference on Trafficand Transportation Studies,2006:425-434
[87] Van Henggel. Citizens near the path of least resistance: travel behavior of CenturyFreeway corridor residents [D]. California: University of California,1996:36-40.
[88] Osuji, Lifford Ihejirika. Impact of anticipated transportation improvement on landvalues in Chicago [D]. Chicago: University of Illinois,1994:36-40
[89]张起森,张亚平.道路通行能力分析[M].北京:人民交通出版社,2002:37-41
[90]张亚平.道路通行能力理论[M].哈尔滨:哈尔滨工业大学出版社,2007:44-48
[91]中国公路学会.交通工程手册[M].北京:人民交通出版社,1998:25-29.
[92]中华人民共和国住房和城乡建设部.城市道路工程设计规范[M].北京:中国建筑工业出版社,2012:5-25
[93]隽海民,裴玉龙.冰雪覆盖条件下城市道路通行能力分析[J].哈尔滨建筑大学学报,1998,31(2):104-108
[94]陈晓明,邵春福,熊志华.混合交通信号交叉口的通行能力可靠度.中国公路学报,2008,21(4):99~104
[95]住房与城乡建设部.城市综合交通体系规划编制导则[S].2010:5-15
[96]许炎,黄富民.交通容量约束下的土地规划利用模式初探.城市发展研究[J],2010,17(1):96-100
[97]黄纯辉.大城市居民出行方式影响因素的结构模型分析.物流工程与管理[J].2009,31(11):102-105
[98]陆化普,王继峰.城市交通规划中交通可达性模型及其应用[J].清华大学学报,2009,49(6):765-769
[99]吕慎,田锋.我国大城市客运交通结构发展模式研究[J].土木工程学报,2003,36(1):31-35
[100]何瑞春,李引珍.城市居民出行选择预测模型及实证研究[J].交通运输系统工程与信息,2007,7(6):80-84
[101]徐惠农,张晓春.深圳市交通综合治理实践经验[J].城市交通.2011,9(3):48-51
[102]陆化普.城市交通供给策略与交通管理对策研究[J].城市交通.2012,10(3):25-28
[103]马荣国,刘洪营.城市客运交通结构评价指标[J].交通运输工程学报.2004,4(1):87-91
[104]王海燕,项乔君.恶劣气候对高速公路车辆出行的影响[J].交通运输工程学报,2005,5(1):124-126
[105]邹德慈.路网、交通与城市规划[J].城市交通,2011,9(1):14-19
[106]李利.浅析气候对交通发生量的影响[J].中南公路工程,2003,28(4):65-66
[107]晏克非.交通需求管理理论与方法[M].上海:同济大学出版社,2012:45-56
[108]马林.城市交通发展模式转型与战略取向[J].城市交通,2013,11(5):4-7
[109]张晓东.城市交通与土地使用协调规划机制,城市交通,2013,11(5):评论页
[110]陈琨.基于移动源数据的城市路网行程时间可靠性评价模型与算法[J].北京:北京交通大学学位论文,2008:35-39
[111]李旭宏.道路交通规划[M].南京:东南大学出版社,1997:87-125
[112] Chen A, Yang H. Capacity Reliability of a Road Network: an AssessmentMethodology and Numerical Results[J]. Transportation Research Part B,2002,36(3):225-252
[113] Dimitriou L, Stathopoulos A, Tsekeris T. Reliable Stochastic Design of RoadNetwork Systems[J]. International Journal of Industrial and Systems Engineering,2008,3(5):549-574
[114] Lu Jiangang, Yang Fan, Ban Xuegang. Moments Analysis for Improving DecisionReliability Based on Travel Time[J]. Transportation Research Record,2006,16(8):109-116
[115] Bell M G, Cassir C. Risk-averse User Equilibrium Traffic Assignment: AnApplication of Game Theory[J]. Transportation Research Part B,2002,36(8):671-682
[116] Jackson W B, Jucker J V. An Empirical Study of Travel Time Variability andTravel Choice Behavior[J]. Transportation Science,1981,16(4):460-475
[117] Lo H K, Chen A. Traffic Equilibrium Problem with Route-specific Costs:Formulation and Algorithms[J]. Transportation Research Part B,2000,34(6):493-513
[118] Liu H X, Recker W, Chen A. Uncovering the Contribution of Travel TimeReliability to Dynamic Route Choice Using Real-time Loop Data[J].Transportation Research Part A,2004,38(6):435-453
[119] Abdel M A, Kitamura R, Jovanis P P. Investigating Effect of Travel TimeVariability on Route Choice Using Repeated-Measurement Stated PreferenceData[J]. Transportation Research Record,1995,(1493):39-45
[120] Lim Y. Traffic Assignment with the Turning Movements at Signal Intersection[C].Beijing: ASCE,1998:369-378
[121]孙茜.基于广义出行费用的城市道路交通能耗控制方法研究[D].合肥:合肥工业大学学位论文,2010:27-32
[122]Yin H B, Wong S C, Xu J M. Urban Traffic Flow Predicion Using a Fuzzy-neuralApproach[J]. Transportation Research PartC,2002,10(2):85-98
[123]张勇,白玉,杨晓光.城市道路网络的行程时间可靠性[J].系统工程理论与实践,2009,29(8):171-176
[124]侯立文,谭家美.城市交通中利用Gram-Charlier分布估计行程时间可靠性[J].中国管理科学,2009,17(6):139-146
[125]Xu Tianze, Wei Heng, Ioannides A M. Modeling Capacity Reliability of MinorRoads at-grade Un-signalized Intersections for Potential PerformanceEvaluation[J]. Transportation Planning and Technology,2008,31(4):417-433
[126]贺振欢,杨肇夏.城市交通用户出行费用评价方法的研究.技术经济[J],2003,7(1):63-65
[127]赵黎明,王磐.交通网络规划中的出行费用研究.河北工业大学学报[J],2003,32(6):54-59
[128]韩波.基于行为分析及Multi-Agent的静态交通需求管理模型与控制[D].哈尔滨:哈尔滨工业大学学位论文,2005:43-49
[129]Dimitrios A. Parking fare thresholds: a policy tool[J]. Transport Policy.2001,7(8):115-124
[130]Stephen Ison, Stuart Wall. Attitudes to traffic related issues in urban areas of theUK and the role of workplace parking charges[J]. Journal of Transport Geography,2002,8(10):21-28
[131]Eva Ericsson, Hanna Larsson, Karin Brundell-Freij. Optimizing route choice forlowest fuel consumption–Potential effects of a new driver support tool [J].Transportation Research Part C,2006,15(14),369–383
[132]Gregory E. Pherson M C. Sacramento’s parking lot shading ordinance:environmental and economic costs of compliance[J]. Landscape and UrbanPlanning,2001,25(57):105-123
[133]Richard Arnott, John Rowse. Modeling parking[J]. Journal of Urban Economics,1999,45(1):97-123
[2]马林,陆锡明,杨东援,杨涛.城市交通模型一席谈[J].城市交通,2008,6(1):50-53
[3]毛保华.交通规划模型及应用[M].北京:中国铁道出版社,1999,32-45
[4]李春艳.城市交通模型集锦[J].城市交通,2008,6(1):32-49
[5] Smith B L, Williams B M, Oswald R K. Comparison of Parametric andNonparametric Modesl for Traffic Flow Forecasting[J]. Transportation ResearchPart C,2002,10(8):303-321
[6]裴玉龙,李宏萍,蒋贤才.城市交通规划[M].中国铁道出版社,2007:122~129
[7] Usdot. Urban Tranrtation Planning in the United States,An HistoricalOverview[M]. Washington, D.C.USDOT,1992:38-52
[8]邹熙,焦国安,金霞.中美城市交通模型发展展望[J].城市交通,2008,6(2):83-86
[9] Chieh-Hua Wen, Frank S.Koppenlman.The generalized nested logit model [J].Transportation Research Part B.2001,(35):627-641
[10] Vovsha P.The cross-nested logit model: application to mode choice in theTel-Avivmetropolitanarea[J]. In Transportation research Record1607.TRB,1997(5):6-15
[11] C. R. Bhat. A heteroscedastic extreme value model of intercity travel modechoice [J]. Transp-ortation Research Part B.1995,29B (6):471-483
[12] D. McFadden and K. E. Train. Mixed mnl models for discrete response [J]. Journal of Applied Econometrics,2000,(5):447-470
[13] Swait J D, Ben-Akiva M. Incorporating Random Constraints in Discrete14Models of Choice Set Generation [J].1987,(21):318-351
[14] Jones P. Understanding Travel Behavioral [M]. Gower:Aldershot,1983:112-126.
[15] Gling. Household Activity Scheduling[M]. Gower:Aldershot,1989:235-248
[16] Axhausen K, Gling. Activity-Based Approaches to Travel Analysis [J]. TransporReviews,1992:323-341
[17]李霞.城市居民出行生成预测方法研究[D].长春:吉林大学学位论文,2004:44-52
[18]姚荣涵.城市居民出行生成预测方法研究[D].长春:吉林大学学位论文,2004:49-70
[19] Ettema D, Borgers A, Timmermans H. Simulation Model of Activity SchedulingHeuristics:empirical test and simulation issues[M].1995:323-341
[20] Jifeng Wu, Gang-Len Chang. An integrated optimal control and algorithm forcommuting corridors[J]. International Transactions in Operational Research,1999,6(1):39-55
[21] Mark E T, Horn. An extended model and procedural framework for planningmulti-modal passenger journeys[J]. Transportation Research,2003,2(1):31-37
[22] Ennio Cassette, Andrea Papola. A joint mode-transit service choice model Incorporating the effect of regional transport service timetables[J]. TransportationResearch,2003,2(1):18-25
[23]毛海虓.中国城市居民出行特征研究[D].北京:北京工业大学学位论文,2005:14-25
[24]李思鼎,陈国安.高原和高寒环境对车辆的影响分析[J].城市车辆技术与研究,2009,(2):43-45
[25] Petersen E R. A highway corridor planning model: QROAD [J].TransportationResearch Part A,2002,36(2):107-125
[26] Cambridge Systematics. Long-Term Availability of Multimodal Corridor Capacity[R]. England: Res.Agency,1996,11-24
[27] Bertsekas D P. A simple and fast label correcting algorithm for shortest paths[J].Networks,1993,23-30
[28] Ries G L. Impact of Weather on Freeway Capacity[R]. Minneapolis, MN:Minnesota Department of Transportation,1981:5-8
[29] Liang W L, Kyte M, Kitchener F. The Effect of Environmental Factors on DriverSpeed[J]. Transportation Research Record1635,1998(1):155-161
[30] Knapp K, Smithson L. The Use of Mobile Video Data Collection Equipment toInvestigate Winter Weather Vehicle Speeds. Transportation Research,2001,2(1):75-84
[31] Perrin J, Martin P T. Modifying Signal Timing During62Inclement Weather[J].In Transportation Research Record1748,2001(1):45-48
[32] Usharani Sankuri. Improvements in Small to Medium Sised Community TripGeneration[M]. The United states: The University of Alabama in Huntsville,2003:32-35
[33]陆化普.交通规划理论与方法[M].北京:清华大学出版社,1998:199-207
[34]文国玮.城市交通与道路系统规划[M].北京:清华大学出版社,2001:49-76
[35]李峰,陈永茂.大城市严重交通拥堵风险评估与应对策略[J].城市交通,2011,9(2):15-21
[36]褚伟,高永.城市交通枢纽的规划要点[J].城市交通,2005,2(1)35-37
[37]林雨,方守恩.灾害天气环境下高等级公路车速管理[J].自然灾害学报,2007,16(5):96-99
[38]高华.城市道路条件及环境对交通安全的影响研究[D].成都:西南交通大学学位论文,2007:24-35
[39]刘清.高速公路交通灾害预警管理系统研究[D].武汉:武汉理工大学学位论文,2004:22-28
[40]罗丽君,高晗,裴玉龙.冰雪道路条件下最小安全行车间距的确定.黑龙江交通科技[J],1999,38:33-34
[41]任园园.冰雪条件下城市道路交通流特性及管理对策研究[D].长春:吉林大学学位论文,2007:35-43
[42]蒋贤才,裴玉龙.寒冷地区道路交通安全特征及其管理措施分析[J].交通运输系统工程与信息,2007,7(4):82-89
[43]裴玉龙,盖春英.公路网络运营可靠度研究[J].公路交通科技,2005,22(5):119~123
[44]冷军强.冰雪条件下路网行程时间可靠性研究[D].哈尔滨:哈尔滨工业大学学位论文,2010:44-50
[45]冯雨芹,张春平.冰雪条件下城市道路路段行程时间模型[J].黑龙江工程学院学报.2011,25(1):29-31
[46]董苏华,章超汉.部分国家及地区停车问题研究[J].城市交通,1999,4:37-41.
[47]邹贞元,徐亚国,安实.城市静态交通管理理论与应用[M].广州出版社,2000:1~10
[48]王丰元，邹旭东.基于用地和交通特征的停车需求预测模型[J].交通运输工程学报,2007,4
[49]安实,王健,安实.停车需求预测与管理[J].系统工程理论与方法,2001,8:212~214
[50] Donald C. Shoup. The trouble with minimum parking requirements[J].Transportation Research Part A,1999,33:549-574
[51] An Shi, Han Bo, Wang Jian. A User’s Route Choice Behavior Model Based onReal-time Road Information[C].2004International Conference On ManagementScience&Engineering,2004,6:2565-2569
[52] An Shi, Han Bo, Wang Jian. Study of the Mode of Real-time and DynamicParking Guidance and Information Systems Based on Fuzzy ClusteringAnalysis[C]. Third International Conference on Machine Learning andCybernetics,2004:2790-2794
[53] An Shi, Han Bo, Wang Jian. Study on the Early-Warning and TransactionTechnology of Traffic Accidents[C]. The15thInternational Road Federation WorldMeeting,2005:1071-1075
[54] Lasdon L S, Luo S J. Computational Experiment wicha System Optimal DynamicTraffic Assignment Model[J]. Transpn.Res,1994,2C:109-127
[55] Larsson T, Patriksson M. A Class of Gap Function for Variational Ineequilities[J].Mathematical Programming,1994,64:53-79
[56] Jayakrishnan R, Tski K W. A Dynamic Traffic Assignment Model withTraffic-Flow Relationships[J]. Transpn. Res,1995,3(C):43-47
[57] Joel L Horouwitz. Reconsidering The Multinomial Probit Model[J]. Transpn. Res,1991,25(B):32-36
[58] Lam W H, Huang H J. A Combined Trip Distribution and Assignment Model forMultiple User Classes[J]. Transpn. Res,1992,26(B):21-26
[59] Lam W H K, Huang H J. Dynamic User Optimal Traffic Assignment Model forMany to Travel Demand[J]. Transpn. Res,1995,29(B):32-36
[60] Larsson T, Patriksson M. A Class of Gap Function for Variational Inequilities[J].Mathematical Programming,1994,25(A):32-36
[61] Lasdon L S, Luo S J. Computational Experiment with a System Optimal DynamicTraffic Assignment Model[J]. Transpn. Res,1994,2(C):17-21
[62] Wu Z X, Lam W H K. Combined Modal Split and Stochastic Assignment Modelfor Congested Networks with Motorized and Nonmotorized Transport Modes[J].Transportation Research Record,2003(1831):57-64
[63] Mahnasaani H S, Peeta S. Network Performance under System Optimal and UserEquilibrium Dynamic Assignment[J]. Transpn. Res,1993,11(C):25-27
[64] Siegel J D, Cea J D, Fernandez J E.Comparisons of Urban Travel ForecastsPrepared with the Sequential Procedure and Spatial Economics,2006(6):135-148
[65] Ran B, Boyce D E. A New Class Of Instantaneous Dynamic User Optimal TrafficAssignment Model[J]. Operations Research,1993,2(B):35-38
[66] Ran B,Hall W R. A Link-Based Variational Inequality Model for DynamicDeparture Time/Route Choice[J]. Transpn. Res,1996,30(B):18-21
[67] Murat Gene. Aggregation and Heterogenaty of Choice Set Generation[J]. Transpn.Res,1994,28(B):36-39
[68] Smith M J. A New Dynamic Traffic Assignment Model and the Existence andCalculation of Dynamic User Equilibria on Congested Capacity-Constrained RoadNetworks[J]. Transpn. Res,1993,27(B):35-37
[69]邵长桥,刘小明.交通预测原则和预测模型评价方法[J].道路及交通与安全,2007,15(2):45-48
[70]刘灿奇.现代交通规划学[M].北京:人民交通出版社,2001,105-118
[71]刘建明,陈金玉.基于土地利用的交通需求预测[J].交通科技与信息,2009,12(2):38-41
[72]毛宝华,曾会欣.交通规划模型及其应用[M].北京:中国铁道出版社,1999；116-121
[73] Zhang Z B. Mutualism or cooperation among competitors pro-Motes coexistenceand competitive ability[J]. Ecological Mod-elling,2003,9(2):42-45
[74] Hunt J D, Teply S. A nested logit model of parking location choice[J].Transportation Research Part B,1999,4:253-265
[75] Jha M, Madanat S, Peeta S. Perception updating and day-to-day travel choicedynamics in traffic networks with information provision[J]. Transportationresearch Part B.1998,6:189-212
[76] Boyce, David; Mattsson, Lars-G ran. Modeling residential location choice inrelation to housing location and road tolls on congested urban highway networks.Transportation research Part B.1999,8:581-591
[77] Cascetta E, Papola A. Random utility models with implicit availability/perceptionof choice alternatives for the simulation of travel demand[J]. Transportationresearch Part C,2001,4:249-263
[78]张军.城市交通系统可持续发展综合评价研究[D].成都:西南交通大学学位论文,2007:17-20
[79]王炜,陈学武.城市交通系统可持续发展理论体系研究[M].北京:科学出版社,2004:18-22
[80]梁颖.大城市道路交通系统运营状态评价[D].北京:北京工业大学学位论文,2002:25-28
[81]邵春福.交通规划原理[M].北京:中国铁道出版社,2008: pp:174-177
[82]郝海,踪家峰.系统分析与评价方法[M].北京:经济科学出版社,2007:70~100
[83] Tang Lian-Sheng, Cheng Wen-Ming. Vehicle Routing Problem with Travel TimeReliability Constrain[C]. International Conference on Transportation Engineering,2007: pp:1831-1836
[84] Mahnasaani H S, Jayakrishnan R. System Performance and user response underrealtime information in congested traffic corridor[J]. Transpn. Res,1991,25A:35-39
[85] Asakura Y. Evaluation of Networtk Reliability Using Stochastic User Equili-brium[J]. Journal of Advanced Transportation.,1999,33(2):147-158
[86] Zhihua Xiong, Chunfu Shao, Zhisheng Yao. Integrated Method for Road NetworkReliability Under Stochastic Demand[C].5th International Conference on Trafficand Transportation Studies,2006:425-434
[87] Van Henggel. Citizens near the path of least resistance: travel behavior of CenturyFreeway corridor residents [D]. California: University of California,1996:36-40.
[88] Osuji, Lifford Ihejirika. Impact of anticipated transportation improvement on landvalues in Chicago [D]. Chicago: University of Illinois,1994:36-40
[89]张起森,张亚平.道路通行能力分析[M].北京:人民交通出版社,2002:37-41
[90]张亚平.道路通行能力理论[M].哈尔滨:哈尔滨工业大学出版社,2007:44-48
[91]中国公路学会.交通工程手册[M].北京:人民交通出版社,1998:25-29.
[92]中华人民共和国住房和城乡建设部.城市道路工程设计规范[M].北京:中国建筑工业出版社,2012:5-25
[93]隽海民,裴玉龙.冰雪覆盖条件下城市道路通行能力分析[J].哈尔滨建筑大学学报,1998,31(2):104-108
[94]陈晓明,邵春福,熊志华.混合交通信号交叉口的通行能力可靠度.中国公路学报,2008,21(4):99~104
[95]住房与城乡建设部.城市综合交通体系规划编制导则[S].2010:5-15
[96]许炎,黄富民.交通容量约束下的土地规划利用模式初探.城市发展研究[J],2010,17(1):96-100
[97]黄纯辉.大城市居民出行方式影响因素的结构模型分析.物流工程与管理[J].2009,31(11):102-105
[98]陆化普,王继峰.城市交通规划中交通可达性模型及其应用[J].清华大学学报,2009,49(6):765-769
[99]吕慎,田锋.我国大城市客运交通结构发展模式研究[J].土木工程学报,2003,36(1):31-35
[100]何瑞春,李引珍.城市居民出行选择预测模型及实证研究[J].交通运输系统工程与信息,2007,7(6):80-84
[101]徐惠农,张晓春.深圳市交通综合治理实践经验[J].城市交通.2011,9(3):48-51
[102]陆化普.城市交通供给策略与交通管理对策研究[J].城市交通.2012,10(3):25-28
[103]马荣国,刘洪营.城市客运交通结构评价指标[J].交通运输工程学报.2004,4(1):87-91
[104]王海燕,项乔君.恶劣气候对高速公路车辆出行的影响[J].交通运输工程学报,2005,5(1):124-126
[105]邹德慈.路网、交通与城市规划[J].城市交通,2011,9(1):14-19
[106]李利.浅析气候对交通发生量的影响[J].中南公路工程,2003,28(4):65-66
[107]晏克非.交通需求管理理论与方法[M].上海:同济大学出版社,2012:45-56
[108]马林.城市交通发展模式转型与战略取向[J].城市交通,2013,11(5):4-7
[109]张晓东.城市交通与土地使用协调规划机制,城市交通,2013,11(5):评论页
[110]陈琨.基于移动源数据的城市路网行程时间可靠性评价模型与算法[J].北京:北京交通大学学位论文,2008:35-39
[111]李旭宏.道路交通规划[M].南京:东南大学出版社,1997:87-125
[112] Chen A, Yang H. Capacity Reliability of a Road Network: an AssessmentMethodology and Numerical Results[J]. Transportation Research Part B,2002,36(3):225-252
[113] Dimitriou L, Stathopoulos A, Tsekeris T. Reliable Stochastic Design of RoadNetwork Systems[J]. International Journal of Industrial and Systems Engineering,2008,3(5):549-574
[114] Lu Jiangang, Yang Fan, Ban Xuegang. Moments Analysis for Improving DecisionReliability Based on Travel Time[J]. Transportation Research Record,2006,16(8):109-116
[115] Bell M G, Cassir C. Risk-averse User Equilibrium Traffic Assignment: AnApplication of Game Theory[J]. Transportation Research Part B,2002,36(8):671-682
[116] Jackson W B, Jucker J V. An Empirical Study of Travel Time Variability andTravel Choice Behavior[J]. Transportation Science,1981,16(4):460-475
[117] Lo H K, Chen A. Traffic Equilibrium Problem with Route-specific Costs:Formulation and Algorithms[J]. Transportation Research Part B,2000,34(6):493-513
[118] Liu H X, Recker W, Chen A. Uncovering the Contribution of Travel TimeReliability to Dynamic Route Choice Using Real-time Loop Data[J].Transportation Research Part A,2004,38(6):435-453
[119] Abdel M A, Kitamura R, Jovanis P P. Investigating Effect of Travel TimeVariability on Route Choice Using Repeated-Measurement Stated PreferenceData[J]. Transportation Research Record,1995,(1493):39-45
[120] Lim Y. Traffic Assignment with the Turning Movements at Signal Intersection[C].Beijing: ASCE,1998:369-378
[121]孙茜.基于广义出行费用的城市道路交通能耗控制方法研究[D].合肥:合肥工业大学学位论文,2010:27-32
[122]Yin H B, Wong S C, Xu J M. Urban Traffic Flow Predicion Using a Fuzzy-neuralApproach[J]. Transportation Research PartC,2002,10(2):85-98
[123]张勇,白玉,杨晓光.城市道路网络的行程时间可靠性[J].系统工程理论与实践,2009,29(8):171-176
[124]侯立文,谭家美.城市交通中利用Gram-Charlier分布估计行程时间可靠性[J].中国管理科学,2009,17(6):139-146
[125]Xu Tianze, Wei Heng, Ioannides A M. Modeling Capacity Reliability of MinorRoads at-grade Un-signalized Intersections for Potential PerformanceEvaluation[J]. Transportation Planning and Technology,2008,31(4):417-433
[126]贺振欢,杨肇夏.城市交通用户出行费用评价方法的研究.技术经济[J],2003,7(1):63-65
[127]赵黎明,王磐.交通网络规划中的出行费用研究.河北工业大学学报[J],2003,32(6):54-59
[128]韩波.基于行为分析及Multi-Agent的静态交通需求管理模型与控制[D].哈尔滨:哈尔滨工业大学学位论文,2005:43-49
[129]Dimitrios A. Parking fare thresholds: a policy tool[J]. Transport Policy.2001,7(8):115-124
[130]Stephen Ison, Stuart Wall. Attitudes to traffic related issues in urban areas of theUK and the role of workplace parking charges[J]. Journal of Transport Geography,2002,8(10):21-28
[131]Eva Ericsson, Hanna Larsson, Karin Brundell-Freij. Optimizing route choice forlowest fuel consumption–Potential effects of a new driver support tool [J].Transportation Research Part C,2006,15(14),369–383
[132]Gregory E. Pherson M C. Sacramento’s parking lot shading ordinance:environmental and economic costs of compliance[J]. Landscape and UrbanPlanning,2001,25(57):105-123
[133]Richard Arnott, John Rowse. Modeling parking[J]. Journal of Urban Economics,1999,45(1):97-123