城市动态路况信息下交通行为的研究
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摘要
为了缓解目前日益严重的城市交通拥挤问题,通过先进的出行者交通信息服务系统(Advanced Traveler Information Systems, ATIS)向出行者提供实时路况信息,协助制定合理的出行计划,调整或改变交通方式、路线和出发时间,因此有助于从时间和空间两方面分流高峰期的出行需求。路况信息的准确度会显著影响出行者对信息的信任程度,进而改变其出行行为,但是以往对信任度的研究多集中在信息费用、使用便利性等定性分析,而且路况信息中的出行时间变化属性对出行行为的影响作用的论文成果比较少见,另外,传统的出行决策分析主要是基于期望效用理论,采用有限理性行为分析方法还有待完善。针对上述不足,本文旨在研究动态路况信息条件下的交通行为(出行路线和出发时间选择行为),通过设计交通意愿问卷,在大连地区采集交通行为选择数据,定量分析影响路况信息信任度选择的关键因素,同时重点对路况信息与出行者的交通出行选择行为之间的作用机理进行研究,主要研究内容和研究成果有以下三个方面：
首先,综合考虑了可能影响出行行为的六种路况信息因素,构建了路况信息信任度选择Probit模型。通过对ATIS信息影响出行者选择行为的相关论文成果进行回顾,以此为基础,采用正交试验法设计实施了大连市有驾车经验出行者的路况信息信任度选择意愿问卷调查,重点从空间域和频率域两个维度对信息准确度进行定量考查,即出行时间预测误差的绝对值属性和时间信息在固定周期内出现较大预测误差的频率属性,深入探讨了信息准确度属性对出行者的信息信任度选择行为的影响作用,模型标定结果显示,出行时间信息出现较大预测误差的发生频率是出行者最敏感的因素,个人属性中的驾龄和学历对路况信息信任度有显著影响,同时对其它个人属性因素的影响作用分别进行讨论,并针对国内城市提供个性化ATIS信息服务提出了相关建议。
其次,针对路况信息动态特征中最典型的出行时间存在变化的特性,构建了以变化的出行时间为参数的、路况信息条件下的出行行为选择模型。针对大连市有驾车经验的出行者,设计实施出行意愿问卷调查,其中包括路线选择和出发时间选择情景调查,在调查数据的基础上,分别假定时间参数和费用参数为常数、费用参数服从正态分布、对数正态分布和SB分布,建立了出行选择Logit和Mixed Logit模型,模型中引入了两个独立的解释变量描述时间信息的变化属性,分别从时间域和空间域两个方面进行量化,并对其影响出行行为改变倾向进行定量分析,研究结果表明,出行者对静态的时间信息和出行时间在时间域上发生变化的敏感度十分接近,但是出行者对出行时间信息在空间域上的变化属性,即最大和最小出行时间的敏感度则存在显著差异,另外,个人属性中的年龄、驾龄和收入是影响出行选择行为的主要因素。
最后,针对路况信息影响出行选择行为的作用机理进行了研究。通过设计出行时间存在动态变化的不确定的出行情景算例,分别采用完全理性的期望效用理论和有限理性的前景理论、遗憾理论对出行选择行为进行分析,重点对三种方法计算结果之间的差异展开讨论。另外,根据出行意愿问卷调查数据,构建了基于期望效用理论和遗憾理论的出发时间选择Logit模型,研究结果显示,基于效用最大化和遗憾最小化原则的模型参数估值存在明显差异,这体现了完全理性和有限理性决策方法在行为分析中的区别,但是遗憾模型的性能指标与期望效用模型相比没有表现出明显优势,采用遗憾理论的有限理性决策方法还无法完全反映出行者的主观意愿,并在此基础上探讨了前景理论和遗憾理论值得完善的地方。
Advanced traveler information systems (ATIS) can provide real-time traffic information for travelers'choosing reasonable travel mode, route and departure time, which is helpful to alleviate urban traffic congestion. The accuracy of information can influence travelers' trustiness in travel information, and therefore their travel behavior. It is noted that most studies about trustiness of travelers focus on the information attributes of cost and convenience. Meanwhile, few researchers discuss the effect of the change of travel time on travelers' behavior. Also the comparison between absolutely rational and boundedly rational decision-making theory for choice behavior analysis is still lacking. In order to deal with the aforementioned problems, this study analyzes the travel behavior under urban dynamic road traffic information, including route choice and departure time choice behavior. The stated preference survey for travel data collection is conducted with drivers in Dalian city. The most significant factors influencing the trustiness in traffic information are identified and the mechanism of travel behavior under travel information is analyzed using three decision strategies. The main findings in this paper are summarized as follows:
Firstly, an Ordered Probit model is developed to evaluate the trustiness of travelers for providing urban road traffic information with six different attributes on the basis of extensive collection of literature review within travel behavior analysis under ATIS. The stated preference experiment using orthogonal method is designed and the survey is conducted with drivers in Dalian city. The attributes of traffic information accuracy are taken into account, which include the prediction error of travel time and the occurrence frequency of large prediction error. The model estimation results indicate that the occurrence frequency of large error is the most sensitive parameter affecting travelers'trustiness in traffic information. The travelers'education level and years of driving experience can influence their choices significantly. Also the effect of other socioeconomic attributes is discussed in detail. Then the relevant suggestions for the construction and operation of ATIS in China are proposed.
Secondly, a Logit model and a Mixed Logit model are developed for analyzing travel behavior with time parameter fixed and cost parameter having a normal distribution, lognormal distribution or SB distribution, which contain route choice and departure time choice considering the change of travel time in traffic information. The stated preference survey is designed and conducted to obtain data from travelers with driving experience in order to identify the most important attributes within urban road traffic information which can affect travelers'choice behavior. The model estimation results indicate that the parameters of travel time and the change of travel time are very similar, while the values are very different for the maximum travel time and minimum travel time. The travelers'age, years of driving experience and income significantly impact their travel behavior.
Finally, the mechanism of travel behavior under traffic information is analyzed using expected utility theory, prospect theory and regret theory, considering the change of travel time in traffic information. The different outcomes from three theories are discussed in detail. In order to examine the applicability of regret function in travelers'decision-making process, the stated preference survey is designed and conducted to investigate the commuting departure time choice behavior. A utility-based model and a regret-based model are developed with the collected survey data, incorporating the attribute of travel time uncertainty. The model estimation results show that the sensitivity of maximum and minimum travel time is very similar in regret-based model, which is obviously different from the estimated coefficients in utility-based model. The difference indicates that bad performance in terms of explanatory variables can not be compensated by the strong performance of other variables in the framework of regret theory. So the travelers that apply regret minimization criteria may arrive at different choices for departure time than the travelers that maximize utility. The hit ratio of regret model is lower than utility model, which implies the regret approach is not superior to expected utility theory. As an alternative to utility maximization method, prospect theory or regret theory for travel behavior analysis should be further improved.
首先,综合考虑了可能影响出行行为的六种路况信息因素,构建了路况信息信任度选择Probit模型。通过对ATIS信息影响出行者选择行为的相关论文成果进行回顾,以此为基础,采用正交试验法设计实施了大连市有驾车经验出行者的路况信息信任度选择意愿问卷调查,重点从空间域和频率域两个维度对信息准确度进行定量考查,即出行时间预测误差的绝对值属性和时间信息在固定周期内出现较大预测误差的频率属性,深入探讨了信息准确度属性对出行者的信息信任度选择行为的影响作用,模型标定结果显示,出行时间信息出现较大预测误差的发生频率是出行者最敏感的因素,个人属性中的驾龄和学历对路况信息信任度有显著影响,同时对其它个人属性因素的影响作用分别进行讨论,并针对国内城市提供个性化ATIS信息服务提出了相关建议。
其次,针对路况信息动态特征中最典型的出行时间存在变化的特性,构建了以变化的出行时间为参数的、路况信息条件下的出行行为选择模型。针对大连市有驾车经验的出行者,设计实施出行意愿问卷调查,其中包括路线选择和出发时间选择情景调查,在调查数据的基础上,分别假定时间参数和费用参数为常数、费用参数服从正态分布、对数正态分布和SB分布,建立了出行选择Logit和Mixed Logit模型,模型中引入了两个独立的解释变量描述时间信息的变化属性,分别从时间域和空间域两个方面进行量化,并对其影响出行行为改变倾向进行定量分析,研究结果表明,出行者对静态的时间信息和出行时间在时间域上发生变化的敏感度十分接近,但是出行者对出行时间信息在空间域上的变化属性,即最大和最小出行时间的敏感度则存在显著差异,另外,个人属性中的年龄、驾龄和收入是影响出行选择行为的主要因素。
最后,针对路况信息影响出行选择行为的作用机理进行了研究。通过设计出行时间存在动态变化的不确定的出行情景算例,分别采用完全理性的期望效用理论和有限理性的前景理论、遗憾理论对出行选择行为进行分析,重点对三种方法计算结果之间的差异展开讨论。另外,根据出行意愿问卷调查数据,构建了基于期望效用理论和遗憾理论的出发时间选择Logit模型,研究结果显示,基于效用最大化和遗憾最小化原则的模型参数估值存在明显差异,这体现了完全理性和有限理性决策方法在行为分析中的区别,但是遗憾模型的性能指标与期望效用模型相比没有表现出明显优势,采用遗憾理论的有限理性决策方法还无法完全反映出行者的主观意愿,并在此基础上探讨了前景理论和遗憾理论值得完善的地方。
Advanced traveler information systems (ATIS) can provide real-time traffic information for travelers'choosing reasonable travel mode, route and departure time, which is helpful to alleviate urban traffic congestion. The accuracy of information can influence travelers' trustiness in travel information, and therefore their travel behavior. It is noted that most studies about trustiness of travelers focus on the information attributes of cost and convenience. Meanwhile, few researchers discuss the effect of the change of travel time on travelers' behavior. Also the comparison between absolutely rational and boundedly rational decision-making theory for choice behavior analysis is still lacking. In order to deal with the aforementioned problems, this study analyzes the travel behavior under urban dynamic road traffic information, including route choice and departure time choice behavior. The stated preference survey for travel data collection is conducted with drivers in Dalian city. The most significant factors influencing the trustiness in traffic information are identified and the mechanism of travel behavior under travel information is analyzed using three decision strategies. The main findings in this paper are summarized as follows:
Firstly, an Ordered Probit model is developed to evaluate the trustiness of travelers for providing urban road traffic information with six different attributes on the basis of extensive collection of literature review within travel behavior analysis under ATIS. The stated preference experiment using orthogonal method is designed and the survey is conducted with drivers in Dalian city. The attributes of traffic information accuracy are taken into account, which include the prediction error of travel time and the occurrence frequency of large prediction error. The model estimation results indicate that the occurrence frequency of large error is the most sensitive parameter affecting travelers'trustiness in traffic information. The travelers'education level and years of driving experience can influence their choices significantly. Also the effect of other socioeconomic attributes is discussed in detail. Then the relevant suggestions for the construction and operation of ATIS in China are proposed.
Secondly, a Logit model and a Mixed Logit model are developed for analyzing travel behavior with time parameter fixed and cost parameter having a normal distribution, lognormal distribution or SB distribution, which contain route choice and departure time choice considering the change of travel time in traffic information. The stated preference survey is designed and conducted to obtain data from travelers with driving experience in order to identify the most important attributes within urban road traffic information which can affect travelers'choice behavior. The model estimation results indicate that the parameters of travel time and the change of travel time are very similar, while the values are very different for the maximum travel time and minimum travel time. The travelers'age, years of driving experience and income significantly impact their travel behavior.
Finally, the mechanism of travel behavior under traffic information is analyzed using expected utility theory, prospect theory and regret theory, considering the change of travel time in traffic information. The different outcomes from three theories are discussed in detail. In order to examine the applicability of regret function in travelers'decision-making process, the stated preference survey is designed and conducted to investigate the commuting departure time choice behavior. A utility-based model and a regret-based model are developed with the collected survey data, incorporating the attribute of travel time uncertainty. The model estimation results show that the sensitivity of maximum and minimum travel time is very similar in regret-based model, which is obviously different from the estimated coefficients in utility-based model. The difference indicates that bad performance in terms of explanatory variables can not be compensated by the strong performance of other variables in the framework of regret theory. So the travelers that apply regret minimization criteria may arrive at different choices for departure time than the travelers that maximize utility. The hit ratio of regret model is lower than utility model, which implies the regret approach is not superior to expected utility theory. As an alternative to utility maximization method, prospect theory or regret theory for travel behavior analysis should be further improved.
引文
[1]陆化普,李瑞敏,朱茵.智能交通系统概论[M].北京：中国铁道出版社,2004.
[2]杨佩昆.智能交通[M].上海：同济大学出版社,2002.
[3]杨兆升,初连禹.先进的出行者信息系统(ATIS)的研究进展[J].ITS通讯,2000,(1)：17-24.
[4]Ben-Akiva M, De Palma A, Kaysi I. Dynamic network models and driver information systems [J]. Transportation Research Part A,1991,25(5):251-266.
[5]陆化普,史其信.智能运输系统研究发展动向与启示[J].科技导报,1996,(10)：54-57.
[6]陆化普.智能运输系统[M].北京：人民交通出版社.2005.
[7]邵春福.交通规划原理[M].北京：中国铁道出版社.2007.
[8]王殿海.交通系统分析[M].北京：人民交通出版社.2007.
[9]贾述评,房筱莉.日本智能交通系统的发展[J].吉林交通科技,2006,(3)：67-68.
[10]王笑京.智能交通系统研发历程与动态述评[J].城市交通,2008,6(1)：6-12.
[11]迟铁军,高鹏.国外智能交通系统发展状况分析及对我国的启示[J].黑龙江交通科技,2009,(2)：111-114.
[12]徐海,武钦彩,吴勇,等.国外智能交通系统研究动态及启示[J].交通企业管理,2009,(7)：74-75.
[13]向雁.韩国：ITS有特色[N].市场报,2002,8,19(4).
[14]李德宏,汪浩.智能交通系统在新加坡的应用与发展[J].ITS通讯,2001,(4)：34-38.
[15]Li W, Maciver A. SITC1O:巴西的公交车动态信息系统[J].ITS通讯,2003,(1)：10-14.
[16]Messmer A, Papageorgiou M, Mackenzie N. Automatic control of variable message signs in the interurban Scottish highway network [J]. Transportation Research Part C,1998,6(3):173-187.
[17]Spyridakis J, Barfield W, Conquest L, et al. Surveying commuter behavior:designing motorist information systems [J]. Transportation Research Part A,1991,25(1):17-30.
[18]王笑京,齐彤岩,蔡华.智能交通系统体系框架原理与应用[M].北京：中国铁道出版社,2004.
[19]李晖,贾辉然,牛晓辉,等.智能交通系统的研究现状及发展趋势[J].产业与科技论坛,2008,7(8)：166,251.
[20]杨兆升.智能运输系统概论(第二版)[M].北京：人民交通出版社,2009.
[21]杜宏川.我国智能交通系统发展现状与对策分析[J].吉林交通科技,2009,(1)：60-63.
[22]张静,蔡伯根,吴建平.移动检测技术的研究[J].北方交通大学学报,2003,27(3)：80-83.
[23]王力,王川久,沈晓蓉,等.智能交通系统中实时交通信息采集处理的新方法[J].系统工程,2005,23(2)：86-89.
[24]董敬欣,吴建平,郭继孚.基于GPS/GIS数据的路网层次划分研究[J].城市交通,2005,29(10)：70-74.
[25]张存保,杨晓光,严新平.基于浮动车的高速公路交通事件自动判别方法研究[J].武汉理工大学学报(交通科学与工程版),2006,30(6)：973-975.
[26]Liu K, Yamamoto T, Morikawa T. An analysis of the cost efficiency of probe vehicle data at different transmission frequencies [J]. ITS Research,2006,4(1):21-28.
[27]Liu K, Yamamoto T, Morikawa T. Feasibilities and challenges of probe technologies for real-time traffic data collection [C]. Proceedings of 7th International Conference of Chinese Transportation Professionals, Shanghai, China,2007:335-344.
[28]江龙晖.城市道路交通状态判别及拥挤扩散范围估计方法研究[D].长春：吉林大学交通学院,2007.
[29]孙棣华,董均宇,廖孝勇.基于GPS探测车的道路交通状态估计技术[J].计算机应用研究,2007,24(2)：243-245.
[30]章威,徐建闽,林绵峰.基于大规模浮动车数据的地图匹配算法[J].交通运输系统L程与信息,2007,7(2)：39-45.
[31]林思,徐建闽,熊文华.基于仿真试验的GPS浮动车最佳样本容量确定方法研究[J].交通与计算机,2008,26(4)：72-74.
[32]Kim S, Lim K, Lee Y. A travel time estimation algorithm based on point and interval detector data over the national highway section [C]. Proceedings of the International Conference on Multimedia and Ubiquitous Engineering (MUE2007),2007:459-464.
[33]Shi W H, Kong Q J, Liu Y C. A GPS/GIS integrated system for urban traffic flow analysis [C]. IEEE Proceeding of Intelligent Transportation Systems, Beijing, China,2008:844-849.
[34]D'Acierno L, Carteni A, Montella B. Estimation of urban traffic conditions using an Automatic Vehicle Location (AVL) System [J]. European Journal of Operational Research,2009,196(2): 719-736.
[35]Comert G, Cetin M. Queue length estimation from probe vehicle location and the impacts of sample size [J]. European Journal of Operational Research,2009,197(1):196-202.
[36]李梅红,孙棣华,涂平.基于GPS浮动车的城市主干道交通服务水平实时评估模型[J].交通运输工程与信息学报,2008,6(1)：73-78.
[37]于泉,孙玲,荣建.基于浮动车数据调查方法的交义口延误计算[J].重庆交通大学学报(自然科学版),2009,28(2)：283-286.
[38]潘海啸,贾宁.低碳城市的高品质交通：政策、体系与创新[M].上海：同济大学出版社,2011.
[39]温慧敏,扈中伟,郭继孚,等.奥运期间北京市道路网运行分析[J].交通运输系统工程与信息,2008,8(6)：32-37.
[40]朱丽云,温慧敏,孙建平.北京市浮动车交通状况信息实时计算系统[J].城市交通,2008,6(1)：77-80.
[41]王静霞,张国华,黎明.城市智能公共交通管理系统[M].北京：中国建筑工业出版社,2008.
[42]Chorus C G, Molin E J E, Van Wee B. Use and effects of advaneed traveller information service (ATIS):a review of the literature [J]. Transport Reviews,2006,26(2):127-149.
[43]Srinivasan S, Ferreira J. Travel behavior at the household level:understanding linkages with residential choice [J]. Transportation Research Part D,2002,7(3):225-242.
[44]Srinivasan S, Rogersb P. Travel behavior of low-income residents:studying two contrasting locations in the city of Chennai, India [J]. Journal of Transport Geography,2005,13(3):265-274.
[45]Dziekan K, Vermeulen A J. Psychological effects and design preferences for real-time information displays [J]. Journal of Public Transportation,2006,9(1):71-89.
[46]Choocharuku K, Van H T, Fujii S. Psychological effeets of travel behavior on preference of residential location choice [J]. Transportation Research Part A,2008,42(1):116-124.
[47]Kim D, Lehto X Y, Morrison A M. Gender differences in online travel information search: implications for marketing communications on the internet [J]. Tourism Management,2007, 28(2):423-433.
[48]Petrella M, Lappin J. Comparative analysis of customer response to online traffie information in two cities:Los Angeles, California and Seattle, Washington [J]. Transportation Research Reeord No.1886, intelligent transportation systems and vehicle-highway automation, Washington D.C., 2004:10-17.
[49]De Palma A, Picard N. Route choice decision under travel time uncertainty [J]. Transportation Research Part A,2005,39(4):295-324.
[50]Lenz B, Nobis C. The changing allocation of activities in space and time by the use of ICT-"Fragmentation" as a new concept and empirical results [J]. Transportation Research Part A, 2007,41(2):190-204.
[51]Hato E, Taniguchi M, Sugie Y, et al. Incorporating an information acquisition process into a route choice model with multiple information sources [J]. Transportation Research Part C,1999, 7(2-3):109-129.
[52]Chorus C G, Arentze T A, Timmermans H J P, et al. Travelers'need for information in traffic and transit:results from a web survey [J]. Journal of Intelligent Transportation Systems,2007, 11(2):57-67.
[53]Reddy P D V G, Yang H, Vaughn K. M, et al. Design of an artificial simulator for analyzing route choice behavior in the presence of information system [J]. Mathematical and Computer Modelling,1995,22(4-7):119-147.
[54]Lotan T. Effects of familiarity on route choice behavior in the presence of information [J]. Transportation Research Part C,1997,5(3-4):225-243.
[55]Koutsopoulos H N, Lotan T, Yang Q. A driving simulator and its application for modeling route choice in the presence of information [J]. Transportation Research Part C,1994,2(2):91-107.
[56]Boyle L N, Mannering F. Impact of traveler advisory systems on driving speed:some new evidence [J]. Transportation Research Part C,2004,12(1):57-72.
[57]Srinivasan K K, Mahmassani H S. Analyzing heterogeneity and unobserved structural effects in route-switching behavior under ATIS:a dynamic kernel Logit formulation [J]. Transportation Research Part B,2003,37(9):793-814.
[58]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.
[59]Dia H. An agent-based approach to modeling driver route choice behavior under the influence of real-time information [J]. Transportation Research Part C,2002,10(5-6):331-349.
[60]Chen T, Chang H, Tzeng G. Using a weight-assessing model to identify route choice criteria and information effects [J]. Transportation Research Part A,2001,35(3):197-224.
[61]Adler J L, McNally M G. In-laboratory experiments to investigate driver behavior under advanced traveler information systems [J]. Transportation Research Part C,1994,2(3):149-164.
[62]Lyons G D. Towards integrated traveller information [J]. Transport Reviews,2001,21(2): 217-235.
[63]Lyons G D, Urry J. Travel time use in the information age [J]. Transportation Research Part A, 2005,39(2-3):257-276.
[64]Emmerink R H M, Verhoef E T, Nijkam P, et al. Effects of information in road transport networks with recurrent congestion [J]. Transportation,1995,22(1):21-53.
[65]Adler J L. Investigating the learning effeets of route guidance and traffic advisories on route choice behavior [J]. Transportation Research Part C,2001,9(1):1-14.
[66]Jou R, Lam S, Liu Y, et al. Route switching behavior on freeways with the provision of different types of real-time traffic information [J]. Transportation Research Part A,2005,39(5):445-461.
[67]Abdel-Aty M A. Using ordered probit modeling to study the effect of ATIS on transit ridership [J]. Transportation Research Part C,2001,9(4):265-277.
[68]Golob T F, Regan A C. Trucking industry preferences for traveler information for drivers using wireless internet-enabled devices [J]. Transportation Research Part C,2005,13(3):235-250.
[69]Kilpelainen M, Summala H. Effects of weather and weather forecasts on driver behaviour [J]. Transportation Research Part F,2007,10(4):288-299.
[70]Bonsall P. Do we know whether personal travel planning really works [J]. Transport Policy,2009, 16(6):306-314.
[71]Kenyon S, Lyons G. The value of integrated multimodal traveller information and its potential contribution to modal change [J]. Transportation Research Part F,2003,6(1):1-21.
[72]Levinson D. The value of advanced traveler information systems for route choice [J]. Transportation Research Part C,2003,11(1):75-87.
[73]Ng L, Wessels R L, Do D, et al. Statistical analysis of commercial driver and dispatcher requirements for advanced traveler information systems [J]. Transportation Research Part C, 1995,3(6):353-369.
[74]Emmerink R H M, Nijkam P, Rietveld P. Variable message signs and radio traffic information: an integrated empirical analysis of drivers' route choice behaviour [J]. Transportation Research Part A,1996,30(2):135-153.
[75]Englisher L, Juster R, Bregman S, et al. Consumer response to the SmarTraveler ATIS:findings from the second year evaluation [C]. Proceedings of the 1996 Annual Meeting of ITS America, Houston, Texas,1996.
[76]Golob T F, Regan A C. Impacts of information technology on personal travel and commercial vehicle operations:research challenges and opportunities [J]. Transportation Research Part C, 2001,9(2):87-121.
[77]Bhat C R, Sivakumar A, Axhausen K W. An analysis of the impact of information and communication technologies on non-maintenance shopping activities [J]. Transportation Research Part B,2003,37(10):857-881.
[78]Chorus C G, Molin E J E, Arentze T A, et al. Validation of a multimodal travel simulator with travel information provision [J]. Transportation Research Part C,2007,15(3):191-207.
[79]Yim Y, Kanafani A. Expanding usage of cellular phones:user profile and transportation issues [R]. Path Working Paper, UCB-ITS-PRR-91-19, University of California at Berkeley,1991.
[80]Denant-Boemont L, Petiot R. Information value and sequential decision-making in a transport setting:an experimental study [J]. Transportation Research Part B,2003,37(4):365-386.
[81]Huang H J, Li Z C. A multiclass, multicriteria logit-based traffic equilibrium assignment model under ATIS [J]. European Journal of Operational Research,2007,176(3):1464-1477.
[82]Arnott R, De Palma A, Lindsey R. Does providing information to drivers reduce traffic congestion [J]. Transportation Research Part A,1991,25(5):309-318.
[83]Thakuriah P, Sen A. Quality of information given by advanced traveler information systems [J]. Transportation Research Part C,1996,4(5):249-266.
[84]Sinuany-Stern Z, Stern E, Spharadi Z. Information effeets on commuters'behavior under varying network patronage [J]. International Transactions in Operational Research,1999,6(1):89-105.
[85]Yin Y, Yang H. Simultaneous determination of the equilibrium market penetration and compliance rate of advanced traveler information systems [J]. Transportation Research Part A, 2003,37(2):165-181.
[86]Al-Deek H M, Khattak A J, Thananjeyan P. A combined traveler behavior and system performance model with advanced traveler information systems [J]. Transportation Research Part A,1998,32(7):479-493.
[87]Ben-Elia E, Shiftan Y, Erev I. A behavioral approach to modeling route choice decisions with real time information [C]. ETC Proceedings of European Transport Conference, Amsterdam, the Netherlands,2007.
[88]Stern E. Reactions to congestion under time pressure [J]. Transportation Research Part C,1999, 7(2-3):75-90.
[89]Tsirimpa A, Polydoropoulou A, Antoniou C. Modelling the impact of advanced traveller information systems on travellers'behavior:Puget Sound Region case study [C]. ETC Proceedings of European Transport Conference, Strasbourg, France,2005.
[90]Johansson M V, Heldt T, Johansson P. The effects of attitudes and personality traits on mode choice [J]. Transportation Research Part A,2006,40(6):507-525.
[91]Kattak A J, Schofer J L, Koppelman F S. Commuters'enroute diversion and return decisions: analysis and implications for advanced traveler information systems [J]. Transportation Research Part A,1993,27(2):101-111.
[92]Chatterjee K, Mcdonald M. Effectiveness of using variable message signs to disseminate dynamic traffic information:evidenee from field trails in European cities [J]. Transport Reviews, 2004,24(5):559-585.
[93]Conquest L, Spyridakis J, Haselkorn M, et al. The effect of motorist information on commuter behavior:classification of drivers into commuter groups [J]. Transportation Research Part C, 1993,1(2):183-201.
[94]Emmerink R H M, Verhoef E T, Nijkam P, et al. Information policy in road transport with elastic demand:some welfare economic considerations [J]. European Economic Review,1998,42(1): 71-95.
[95]Hamed M M. Abdul-Hussain A A. Drivers'Familiarity with urban route network layout in Amman, Jordan [J]. Cities,2001,18(2):93-101.
[96]Liu H X, Recker W, Chen A.Uncovering the contribution of travel time reliability to dynamic route choice using real-time loop data [J]. Transportation Research Part A,2004,38(6):435-453.
[97]Molin E J E, Timmermans H J P. Traveler expectations and willingness-to-pay for web-enabled public transport information services [J]. Transportation Research Part C,2006,14(2):57-67.
[98]林震,杨浩.交通信息服务条件下的出行选择行为[J].中国公路学报,2003,16(1)：87-90.
[99]毛保华,曾会欣,袁振洲.交通规划模型及其应用[M].北京：中国铁道出版社,1999.
[100]Ben-Akiva M, Lerman S R. Discrete choice analysis:theory and application to travel demand [M]. Cambridge:The MIT Press,1985.
[101]Koppelman F S, Wen C H. The paired combinatorial logit model:properties,estimation and application [J]. Transportation Research Part B,2000,34(2):75-89.
[102]Train K E. Discrete choice methods with simulation [M]. Cambridge:Cambridge University Press,2002.
[103]Kitamura R, Chen C, Pendyala R M. Generation of synthetic daily activity-travel patterns [J]. Transportation Research Record, No.1607,1997:154-162.
[104]Koppelman F S, Wen C H. Alternative nested logit models:structure properties and estimation [J]. Transportation Research Part B,1998,32(5):289-298.
[105]Wen C H, Koppelman F S. Integrated model system of stop generation and tour formation for analysis of activity and travel patterns [J]. Transportation Research Record, No.1676,1999: 136-144.
[106]Wen C H, Koppelman F S. The generalized nested logit model [J]. Transportation Research PartB,2001,35(7):627-641.
[107]Hensher D A, Greene W H. Specification and estimation of the nested logit model:alternative normalizations [J]. Working Paper, Stern School of Business, New York University, NY,2000.
[108]Hensher D A, Ton T T. A comparison of the predictive potential of artificial neural networks and nested logit models for commuter mode choice [J]. Transportation Research Part E,2000, 36(3):155-172.
[109]Loudon W R, Luther D K, Mabry J E, et al. Assessing the effectiveness of TDM and land use strategies for a corridor study in the Puget Sound Region [C]. The 82nd Annual Meeting of the Transportation Research Board,2003.
[110]Bricka S. Analyzing women's trip-chaining patterns to identify potential TOD retail amenity mixes [C]. The 84th Annual Meeting of the Transportation Research Board,2005.
[111]严季,李东根,邵春福.基于非集计模型的城市铁路线路客流量预测研究[J].西安公路交通大学学报,2001,21(3)：68-72.
[112]关宏志,王山川,姚丽亚,等.基于SP和RP数据融合的城市轨道交通选择模型[J].北京工业大学学报,2007,33(2)：203-207.
[113]张政,毛保华,刘明君,等.北京老年人出行行为特征分析[J].交通运输系统工程与信息,2007,7(6)：11-20.
[114]何瑞春,李引珍,张峻屹,等.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.
[115]黄树森,宋瑞,陶媛.大城市居民出行方式选择行为及影响因素研究-以北京市为例[J].交通标准化,2008,(9)：124-128.
[116]李志斌,王炜,杨晨,等.机动车尾气污染对居民出行选择的影响[J].交通信息与安全,2009,27(3)：56-59.
[117]陈团生,岳芳,杨玲玲,等.老年人出行选择行为影响因素研究[J].西南交通大学学报(社会科学版),2007,8(5)：17-21.
[118]张萌,孙全欣,陈金川,等.北京市女性出行行为研究[J].交通运输系统工程与信息,2008,8(2)：19-26.
[119]何保红,王炜,陈峻.城市P&R出行者选择行为模型[J].哈尔滨工业大学学报,2009,41(4)：243-246.
[120]刘崭,高璇.基于非集计模型的公交出行选择预测模型[J].公路,2010,(5)：136-139.
[121]Khattak, A., Schofer, J., Koppelman, F. Effect of traffic reports on commuters route and departure time changes [J]. Journal of Advanced Transportation,1995,29 (2):193-212.
[122]Khattak A J, De Palma A. The impact of adverse weather conditions on the propensity to change travel decisions:A survey of Brussels commuters [J]. Transportation Research Part A, 1997,31(3):181-203.
[123]Khattak A J, Yim Y, Stalker L. Does travel information influence commuter and non-commuter behavior? Results from the San Francisco Bay Area TravInfo Project [J]. Transportation Research Record,1694, Transportation Research Board, Washington, DC,1999:48-58.
[124]Khattak A J, Yim Y, Prokopy L S. Willingness to pay for travel information [J]. Transportation Research Part C,2003,11(2):137-159.
[125]Bhat C R. Analysis of travel mode and departure time choice for urban shopping trips [J]. Transportation Research Part B,1998,32(6):361-371.
[126]Bonsall P. The influence of route guidance advice on route choice in urban networks [J]. Transportation,1992,19(1):1-23.
[127]Wardman M, Bonsall P W, Shires J D. Driver response to variable message signs:a stated preference investigation [J]. Transportation Research Part C,1997,5(6):389-405.
[128]Ben-Akiva M, Bonsall P. Increasing the relevance and utility to practice of transportation research [J]. Transport Policy,2004,11(2):101-103.
[129]Bonsall P, Palmer I. Modelling drivers' car parking behaviour using data from a travel choice simulator [J]. Transportation Research Part C,2004,12(5):321-347.
[130]Bonsall P, Kelly C. Road user charging and social exclusion:the impact of congestion charges on at-risk groups [J]. Transport Policy,2005,12(5):406-418.
[131]Hensher D A, Louviere J J, Hansen D E. The use of mixtures of market and experimental choice data in establishing guideline weights for evaluating competitive bids in a transport organisation [J]. Transport Policy,2000,7(4):279-286.
[132]Hensher D A, King J. Parking demand and responsiveness to supply, pricing and location in the Sydney central business district [J]. Transportation Research Part A,2001,35(3):177-196.
[133]Hensher D A. The sensitivity of the valuation of travel time savings to the specification of unobserved effects [J]. Transportation Research Part E,2001,37(2-3):129-142.
[134]Abdel-Aty M A, Kitamura R, Jovanis P P. Using stated preference data for studying the effect of advanced traffic information on drivers' route choice [J]. Transportation Research Part C, 1997,5(1):39-50.
[135]Ramming M S. Network Knowledge and Route Choice [D]. Massachusetts:Massachusetts Institute of Technology,2002.
[136]Yoshii T, Sasaki K. Information/Communication technologies and travel behaviour [J]. Transportation Research Part C,2010,18(1):1-2.
[137]Sasaki K, Nishii K. Measurement of intention to travel:considering the effect of telecommunications on trips [J]. Transportation Research Part C,2010,18(1):36-44.
[138]Zhao S C, Harata N, Ohta K. The effect of travel time information on route choice behavior:a market segmentation approach [C]. Proceedings of Infrastructure Planning Annual Meeting of JSCE,1995:189-192.
[139]Zhao S C, Muromachi Y, Harata N. A SP model for route choice behavior in response to travel time information with marginal errors [C]. Proceedings of 7th World Conference on Transport Research,1995:41-55.
[140]Zhao S C, Harata N, Ohta K. Using driver's perceptions to model route choice behavior under ITS [C]. Proceedings of IRF Asia-Pacific Regional Meeting,1996:39-46.
[141]Zhao S C, Harata N. Travel information, perceived travel time, and route diversion behavior [C]. Proceedings of the 9th World Conference on Transport Research, Seoul, Korea,2001.
[142]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.
[143]张存保,杨晓光,严新平.交通信息对驾驶员选择行为的影响研究[J].交通与计算机,2004,22(5)：31-34.
[144]李志纯,黄海军.先进的旅行者信息系统对出行者选择行为的影响研究[J].公路交通科技,2005,22(2)：95-99.
[145]黄智芳,鲁丛林.诱导信息条件下驾驶员路径选择行为研究[J].公路工程,2007,32(4)：167-168,177.
[146]干宏程.VMS诱导信息影响下的路径选择行为分析[J].系统工程,2008,26(3)：11-16.
[147]孟超,邵春福,李玮,等.VMS对驾驶人路径选择行为影响的仿真研究[J].城市交通,2009,7(1)：76-81.
[148]Jou R C, Hensher D A, Chen K H. Route-choice behavior of freeway travelers under real-time traffic information provision-application of the best route and the habitual route-choice mechanisms [J]. Transportation Planning and Technology,2007,30(6):545-570.
[149]Frejinger E, Bierlaire M. Capturing correlation with subnetworks in route choice models [J]. Transportation Research Part B,2007,41(3):363-378.
[150]Ben-Elia E, Erev I, Shiftan Y. The combined effect of information and experience on drivers' route-choice behavior [J]. Transportation,2008,35(2):165-177.
[151]Paz A, Peeta S. Behavior-consistent real-time traffic routing under information provision [J]. Transportation Research Part C,2009,17(6):642-661.
[152]徐天东,孙立军,郝媛,等.不同交通信息下网络交通动态路径选择行为[J].同济大学学报(自然科学版),2009,37(8)：1029-1033.
[153]熊轶.交通信息作用下不同风险属性出行者的行为演进[J].武汉理工大学学报(交通科学与工程版),2009,33(2)：279-282.
[154]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[J].交通运输工程学报,2009,9(1)：96-99.
[155]王卫杰,王炜.基于配对组合logit模型的路线选择[J].东南大学学报(自然科学版),2010,40(4)：844-847.
[156]石京,陶立.实时交通信息提供对驾驶员路径选择行为影响量化分析[J].武汉理工大学学报(交通科学与工程版),2010,34(4)：639-643.
[157]Ben-Elia E, Shiftan Y. Which road do I take? A learning-based model of route-choice behavior with real-time information [J]. Transportation Research Part A,2010,44(4):249-264.
[158]Gao S, Frejinger E, Ben-Akiva M. Adaptive route choices in risky traffic networks:a prospect theory approach [J]. Transportation Research Part C,2010,18(5):727-740.
[159]Gao S, Frejinger E, Ben-Akiva M. Cognitive cost in route choice with real-time information:an exploratory analysis [J]. Transportation Research Part A,2011,45(9):916-926.
[160]Xu H L, Zhou J, Xu W. A decision-making rule for modeling travelers' route choice behavior based on cumulative prospect theory [J]. Transportation Research Part C,2011,19(2),218-228.
[161]Kitamura R. A model of daily time allocation todiscretionary out-of-home activities and trips [J]. Transportation Research Part B,1984,18(3):255-266.
[162]Mahmassani H, Liu Y. Dynamics of commuting decision behavior under advanced traveler information systems [J]. Transportation Research Part C,1999,7(2-3):91-107.
[163]Jou R C. Modeling the impact of pre-trip information on commuter departure time and route choice [J]. Transportation Research Part B,2001,35(10):887-902.
[164]Jou, R C, Kitamura R, Weng M C, et al. Dynamic commuter departure time choice under uncertainty [J]. Transportation Research Part A,2008,42(5):774-783.
[165]Ben-Elia E, Ettema D. Rewarding rush-hour avoidance:a study of commuters'travel behavior [J]. Transportation Research Part A,2011,45(7):567-582.
[166]Lemp J D, Kockelman K M, Damien P. The continuous cross-nested logit model:formulation and application for departure time choice [J]. Transportation Research Part B,2010,44(5): 646-661.
[167]刘冬梅,齐彤岩,张可,等.北京市居民出行时间小样本调查分析[J].交通运输系统工程与信息,2009,9(2)：23-26.
[168]杨玲玲,范烨,高峰,等.基于MNL模型的私人小汽车出行时间选择研究[J].交通标准化,2011,1：63-67.
[169]Saleh W, Farrell S. Implications of congestion charging for departure time choice:work and non-work schedule flexibility [J]. Transportation Research Part A,2005,39(7-9):773-791.
[170]李志瑶,隽志才,宗芳.居民出行时间选择及拥挤收费政策[J].交通运输工程学报,2005,5(3)：105-110.
[171]任英伟,陆键,吴守荣,等.高速公路可变收费货车出行者出行时间选择模型研究[J].公路交通科技,2008,25(10)：123-129.
[172]Ozbay K, Yanmaz-Tuzel O. Valuation of travel time and departure time choice in the presence of time-of-day pricing [J]. Transportation Research Part A,2008,42(4):577-590.
[173]Lu C C, Mahmassani H S. Modeling heterogeneous network user route and departure time responses to dynamic pricing [J]. Transportation Research Part C,2011,19(2):320-337.
[174]赵胜川,王喜文,姚荣涵,等.基于Mixed Logit模型的私家车通勤出行时间价值[J].吉林大学学报(工学版),2010,40(2)：406-411.
[175]Liu W G, Zhao S C. The value of a statistical life in road safety:findings from a contingent valuation study in Dalian, China [C]. Proceedings of the 1st International Conference on Transportation Information and Safety,2011:1061-1067.
[176]杨智伟,赵胜川,张迅.公共交通出行者ATIS信息选择行为影响因素研究[J].交通运输系统工程与信息,2009,9(3)：29-35.
[177]杨智伟.基于ATIS的交通出行信息选择行为及支付意愿研究[D].大连：大连理工大学管理学院,2010.
[178]四兵锋,高自友.城市间公路客运的客票票价与其客流量之间的灵敏度分析[J].中国公路学报,2000,13(2)：91-95.
[179]安实,王健.停车需求预测与管理[J].交通运输系统工程与信息,2001,1(3)：212-216.
[180]关宏志.非集计模型-交通行为分析的工具[M].北京：人民交通出版社,2004.
[181]Guan H Z, Sun X D, Liu X M, et al. Modeling parking behavior for better control and pricing:a case study from one of the busiest retail shopping areas in Beijing, China [C]. The 84th Annual Meeting of the Transportation Research Board,2005.
[182]毛荣吕.城市轨道交通客流预测方法研究[D].南京：河海大学交通学院,2005.
[183]Kalmanje S, Kockelman K. M. Credit-based congestion pricing:travel land value and welfare impacts [J]. Transportation Research Record, No.1864,2004:45-53.
[184]Sinha A K, Thakuriah P. Relationship of occupational, industry and socioeconomic characteristics and job start times-evidence from current population survey [C]. The 83rd Annual Meeting of the Transportation Research Board,2004.
[185]Winters P L, Perez R A, Joshi A D, et al. Worksite trip reduction model and manual [C]. The 84th Annual Meeting of the Transportation Research Board,2005.
[186]Senbil M, Kitamura R. Valuing expressways under time pressures [C]. The 85th Annual Meeting of the Transportation Research Board,2006.
[187]Han Q, Timmermans H. Interactive learning in transportation networks under conditions of uncertainty, bounded rationality and strategic choice behavior:a quantal response model [C]. The 85th Annual Meeting of the Transportation Research Board,2006.
[188]柴彦威,刘志林等.中国城市的时空间结构[M].北京：北京大学出版社,2002.
[189]杜华兵,陈金川.北京市实施错时上下班的可行性分析[J].城市交通.2004,4：64-67.
[190]江薇.城市交通需求管理策略及其评价技术研究[D].南京：东南大学交通学院,2004.
[191]隽志才,李志瑶,宗芳.基于活动链的出行需求预测方法综述[J].公路交通科技,2005,22(6)：108-113.
[192]Juan Z C, Zong F, Li Z Y. Study on activity-based time choice model [C]. Urban Transport and the Environment in the 21st Century,2005:659-668.
[193]隽志才,宗芳,富晓艳.TDM政策实施及评价综述[J].中国软科学,2007,1：156-160.
[194]李志纯.交通行为建模与评价研究-网络均衡分析法[D].北京：北京航空航天大学管理学院,2006.
[195]周素红,杨利军.广州城市居民通勤空间特征研究[J].城市交通,2005,3(1)：62-67.
[196]周素红,闫小培.基于居民通勤行为分析的城市空间解读-以广州市典型街区为案例[J].地理学报,2006,61(2)：179-189.
[197]陈征,周恒.苏州居民通勤出行交通方式选择特征研究[J].道路交通与安全,2006,6(8)：34-37.
[198]李志瑶.基于活动的出行需求预测模型研究[D].长春：吉林大学交通学院,2006.
[199]褚浩然,郑猛,杨晓光,等.出行链特征指标的提取及应用研究[J].城市交通,2006,4(2)：64-67.
[200]陈团生.通勤者出行行为特征与分析方法研究[D].北京：北京交通大学交通学院,2007.
[201]宗芳.基于非集计模型的交通需求管理策略评价研究[D].长春：吉林大学交通学院,2008.
[202]周钱.基于家庭决策的交通行为和需求预测研究[D].北京：清华大学土木水利学院,2008.
[203]孙绍荣,宗利永,鲁虹.理性行为与非理性行为[M].上海：上海财经大学出版社,2007.
[204]Von Neumann J, Morgenstern O. Theories of games and economic behavior [M]. Princeton: Princeton University Press,1947.
[205]Simon H A. Rational choice and the structure of the environment [J]. Psychological Review, 1956,6(2):129-138.
[206]Kahneman D, Tversky A. Prospect Theory:an analysis of decisions under risky [J]. Econometric,1979,47(3):263-291.
[207]Katsikopoulos K V, Fisher D L. Duse-Anthony Y, et al. Risk attitude reversals in drivers' route choice when range of travel time is provided [J]. Human Factors,2002,44(3):466-473.
[208]徐红利,周晶,陈星光.基于前景理论的路径选择行为规则分析与实证[J].交通运输系统工程与信息,2007,7(6)：95-101.
[209]赵凛.张星臣.基于前景理论的路径选择行为建模及实例分析[J].土木工程学报,2007,40(7)：82-86.
[210]De Blaeij A T, VanVuuren D J. Risk perception of traffic participants [J]. Accident Analysis & Prevention,2003,35(2):167-175.
[211]Fujii S, Kitamura R. Drivers' mental representation of travel time and departure time choice in uncertain traffic network conditions [J]. Networks and Spatial Economics,2004,4(3):243-256.
[212]Senbil M, Kitamura R. Reference points in commuter departure time choice:a prospect theoretic test of alternative decision frames [J]. Journal of Intelligent Transportation Systems, 2004,8(1):19-31.
[213]Avineri E. A cumulative prospect theory approach to passengers' behavior modeling:waiting time paradox revisited [J]. Journal of Intelligent Transportation Systems,2004,8(4):195-204.
[214]张杨.不确定环境下城市交通中车辆路径选择研究[D].成都：西南交通大学交通运输学院,2006.
[215]Garling T. Behavioral assumptions overlooked in travel-choice modeling [M]. Travel Behavior Research:Updating the Stale of Play. Oxford, UK:Pergamon,1998.
[216]Ben-Akiva M, Morikawa T. Estimation of switching models from revealed preference and stated intentions [J]. Transportation Research Part A,1990,24(6):485-495.
[217]刘灿齐.现代交通规划学[M].北京：人民交通出版社,2001.
[218]Louviere J J, Henshe D A, Swait J D. Stated choice methods:analysis and application [M]. Cambridge:Cambridge University Press,2000.
[219]Louviere J J, Woodworth G. Design and analysis of simulated consumer choice or allocation experimenis:an approach based on aggregate data [J]. Journal of Marketing Research,1983, 20(4):350-367.
[220]Hensher D A, Barnard P O, Truong T P. The role of stated preference methods in studies of travel choice [J]. Journal of Transport Economics and Policy,1988,22(1):45-67.
[221]Fowkes T, Wardman M. The design of stated preference travel choice experiments [J]. Journal of Transport Economics and Policy,1988,22(1):27-44.
[222]Bradley M. Realism and adaptation in designing hypothetical travel choice concepts [J]. Journal of Transport Economics and Policy,1988,22(1):121-137.
[223]Kroes E, Sheldon R J. Stated preference method:an introduction [J]. Journal of Transport Economics and Policy,1988,22(1):22-25.
[224]Bates J J. Econometric Issues in stated preference analysis [J]. Journal of Transport Economics and Policy,1988,22(1):59-69.
[225]Ortuzar J D, Garrido R A. A practical assessment of stated preferences methods [J]. Transportation,1994,21(3):289-305.
[226]Fowkes A S, Button K L. An evaluation of car ownership forecasting techniques [J]. International Journal of Transport Economics,1996,4(2):115-143.
[227]Kuppam A R, Pendyala R M, Gollakoti M A V. Stated response analysis of effectiveness of parking pricing strategies for transportation control [J]. Transportation Research Board, No.1649, TRB, National Research Council, Washington D.C.,1998:39-46.
[228]Khattak A J, Yim Y, Stalker L. Willingness to pay for travel information:combining revealed and stated preferences with a random effects negative binomial regression model [C]. The 79th Annual Meeting of the Transportation Research Board,1999.
[229]赵鹏,藤原章正,杉惠赖宁.SP调查方法在交通预测中的应用[J].北方交通大学学报,2000,24(6)：29-32.
[230]Fowler F J,孙振东(译).调查研究方法[M].重庆：重庆大学出版社,2006.
[231]Czaja R, Blair J,沈崇麟(译).抽样调查设计导论[M].重庆：重庆大学出版社,2007.
[232]方开泰,马长兴.正交与均匀试验设计[M].北京：科学出版社,2001.
[233]隽志才,鲜于建川.交通信息作用下的活动-出行决策行为研究[J].中国公路学报,2008, 21(4)：88-92
[234]薛薇.基于SPSS的数据分析[M].北京：中国人民大学出版社,2006.
[235]鲍威斯,谢宇.分类数据分析的统计方法(第二版)[M].北京：社会科学文献出版社,2009.
[236]王济川,郭志刚Logistic回归模型-方法与应用[M].北京：高等教育出版社,2001.
[237]林光平.计算计量经济学[M].北京：清华大学出版社,2003.
[238]王树盛,黄卫,陆振波Mixed Logit模型及其在交通方式分担中的应用研究[J].公路交通科技,2006,23(5)：88-91.
[239]张羽祥,赵胜川.基于Monte Carlo模拟的Mixed Logit模型求解研究[J].交通标准化,2009(1)：112-115.
[240]李华民,黄海军,刘剑锋.混合Logit模型的参数估计与应用研究[J].交通运输系统工程与信息,2010,10(5)：73-78.
[241]张羽祥.私家车通勤出行时间价值研究[D].大连：大连理工大学管理学院,2008.
[242]田璠.基于道路拥挤收费的出行时间价值研究[D].大连：大连理工大学数学科学学院,2009.
[243]McFadden D, Train K. Mixed MNL models for discrete response [J]. Journal of Applied Econometrics,2000,15:447-470.
[244]Boyd J, Mellman J. The effect of fuel economy standards on the U.S. automotive market:a hedonic demand analysis [J]. Transportation Research Part A,1980,14:367-378.
[245]Cardell S, Dunbar F. Measuring the societal impacts of automobile downsizing [J]. Transportation Research Part A,1980,14:423-434.
[246]Train K, McFadden D, Ben-Akiva M. The demand for local telephone service:a fully discrete model of residential calling patterns and service choice [J]. The Rand Journal of Economics, 1987,18:109-123.
[247]Ben-Akiva M, Bolduc D, Bradley M. Estimation of switching models from revealed preferences and stated intentions [J]. Transportation Research Reeord,1993,1413:88-97.
[248]Bhat C. Accommodating variations in responsiveness to level-of-service variables in travel mode choice models [J]. Transportation Research PartA,1980,32:455-507.
[249]Brownstone D, Train K. Forecasting new product penetration with flexible substitution patterns [J]. Journal of Econometrics,1999,89:109-129.
[250]Erdem T. A dynamic analysis of market structure based on panel data [J]. Journal of Marketing Research,1996,32:1-16.
[251]Revelt D, Train K. Mixed logit with repeated choices [J]. Review of Economics and Statistics, 1998,80:647-657.
[252]Bhat C. Incorporating observed and unobserved heterogeneity in urban work mode choice modeling [J]. Transportation Science,2000,34:228-238.
[253]Chesher A, Santos-Silva J. Taste variation in discrete choice models [J]. Review of Economic Studies,2002,69:62-78.
[254]Wedel M, Kamakura W. Market segmentation:conceptual and methodological foundations (2nd edition) [M]. Boston:Kluwer Academic Publishers,2000.
[255]Ainsile A, Andrews R, Currim I. An empirical comparison of logit choice models with discrete versus continuous representation of heterogeneity [J]. Journal of Marketing Research,2002,39: 479-487.
[256]陈家鼎,郑忠国.概率与统计[M].北京：北京大学出版社,2007.
[257]徐钟济.蒙特卡罗方法[M].上海：上海科学技术出版社,1985.
[258]赵凛.基于前景理论的出行决策模型及ATIS仿真实验研究[D].北京：北京交通大学交通运输学院,2007.
[259]张奇瑞.基于前景理论的交通诱导行为分析与仿真实验研究[D].北京：北京交通大学交通运输学院,2008.
[260]徐红利.基于有限理性的城市交通系统均衡与拥挤收费策略研究[D].南京：南京大学管理学院,2011.
[261]Xu H L, Zhou J, Xu W. A decision-making rule for modeling travelers'route choice behavior based on cumulative prospect theory [J]. Transportation Research Part C,2011,19(2):218-228.
[262]Xu H L, Lou Y Y, Yin Y F, et al. A prospect-based user equilibrium model with endogenous reference points and its application in congestion pricing [J]. Transportation Research Part B, 2011,45(2):311-328.
[263]Tversky A, Kahneman D. Advances in prospect theory:cumulative representation of uncertainty [J]. Journal of Risk and Uncertainty,1992,9:195-230.
[264]Bell D E. Regret in decision making under uncertainty [J]. Operations Research,1982,30: 961-981.
[265]Loomes G, Sugden R. Regret theory:an alternative theory of rational choice under uncertainty [J]. The Economic Journal,1982,92:805-824.
[266]Fishburn P C. Nontransitive measurable utility [J]. Journal of Mathematical Psychology,1982, 26:31-67.
[267]Chorus C G, Arentze T A, Timmermans H J P. A random regret-minimization model of travel choice [J]. Transportation Research Part B,2008,42(1),1-18.
[268]Chorus C G, Molin E J E, VAN WEE B, et al. Responses to transit information among car-drivers:regret-based models and simulations [J]. Transportation Planning and Technology, 2006,29(4):249-271.
[269]Chorus C G, De Jong G C. Modeling experienced accessibility for utility-maximizers and regret-minimizers [J]. Journal of Transport Geography.2011,19(6):1155-1162.
[2]杨佩昆.智能交通[M].上海：同济大学出版社,2002.
[3]杨兆升,初连禹.先进的出行者信息系统(ATIS)的研究进展[J].ITS通讯,2000,(1)：17-24.
[4]Ben-Akiva M, De Palma A, Kaysi I. Dynamic network models and driver information systems [J]. Transportation Research Part A,1991,25(5):251-266.
[5]陆化普,史其信.智能运输系统研究发展动向与启示[J].科技导报,1996,(10)：54-57.
[6]陆化普.智能运输系统[M].北京：人民交通出版社.2005.
[7]邵春福.交通规划原理[M].北京：中国铁道出版社.2007.
[8]王殿海.交通系统分析[M].北京：人民交通出版社.2007.
[9]贾述评,房筱莉.日本智能交通系统的发展[J].吉林交通科技,2006,(3)：67-68.
[10]王笑京.智能交通系统研发历程与动态述评[J].城市交通,2008,6(1)：6-12.
[11]迟铁军,高鹏.国外智能交通系统发展状况分析及对我国的启示[J].黑龙江交通科技,2009,(2)：111-114.
[12]徐海,武钦彩,吴勇,等.国外智能交通系统研究动态及启示[J].交通企业管理,2009,(7)：74-75.
[13]向雁.韩国：ITS有特色[N].市场报,2002,8,19(4).
[14]李德宏,汪浩.智能交通系统在新加坡的应用与发展[J].ITS通讯,2001,(4)：34-38.
[15]Li W, Maciver A. SITC1O:巴西的公交车动态信息系统[J].ITS通讯,2003,(1)：10-14.
[16]Messmer A, Papageorgiou M, Mackenzie N. Automatic control of variable message signs in the interurban Scottish highway network [J]. Transportation Research Part C,1998,6(3):173-187.
[17]Spyridakis J, Barfield W, Conquest L, et al. Surveying commuter behavior:designing motorist information systems [J]. Transportation Research Part A,1991,25(1):17-30.
[18]王笑京,齐彤岩,蔡华.智能交通系统体系框架原理与应用[M].北京：中国铁道出版社,2004.
[19]李晖,贾辉然,牛晓辉,等.智能交通系统的研究现状及发展趋势[J].产业与科技论坛,2008,7(8)：166,251.
[20]杨兆升.智能运输系统概论(第二版)[M].北京：人民交通出版社,2009.
[21]杜宏川.我国智能交通系统发展现状与对策分析[J].吉林交通科技,2009,(1)：60-63.
[22]张静,蔡伯根,吴建平.移动检测技术的研究[J].北方交通大学学报,2003,27(3)：80-83.
[23]王力,王川久,沈晓蓉,等.智能交通系统中实时交通信息采集处理的新方法[J].系统工程,2005,23(2)：86-89.
[24]董敬欣,吴建平,郭继孚.基于GPS/GIS数据的路网层次划分研究[J].城市交通,2005,29(10)：70-74.
[25]张存保,杨晓光,严新平.基于浮动车的高速公路交通事件自动判别方法研究[J].武汉理工大学学报(交通科学与工程版),2006,30(6)：973-975.
[26]Liu K, Yamamoto T, Morikawa T. An analysis of the cost efficiency of probe vehicle data at different transmission frequencies [J]. ITS Research,2006,4(1):21-28.
[27]Liu K, Yamamoto T, Morikawa T. Feasibilities and challenges of probe technologies for real-time traffic data collection [C]. Proceedings of 7th International Conference of Chinese Transportation Professionals, Shanghai, China,2007:335-344.
[28]江龙晖.城市道路交通状态判别及拥挤扩散范围估计方法研究[D].长春：吉林大学交通学院,2007.
[29]孙棣华,董均宇,廖孝勇.基于GPS探测车的道路交通状态估计技术[J].计算机应用研究,2007,24(2)：243-245.
[30]章威,徐建闽,林绵峰.基于大规模浮动车数据的地图匹配算法[J].交通运输系统L程与信息,2007,7(2)：39-45.
[31]林思,徐建闽,熊文华.基于仿真试验的GPS浮动车最佳样本容量确定方法研究[J].交通与计算机,2008,26(4)：72-74.
[32]Kim S, Lim K, Lee Y. A travel time estimation algorithm based on point and interval detector data over the national highway section [C]. Proceedings of the International Conference on Multimedia and Ubiquitous Engineering (MUE2007),2007:459-464.
[33]Shi W H, Kong Q J, Liu Y C. A GPS/GIS integrated system for urban traffic flow analysis [C]. IEEE Proceeding of Intelligent Transportation Systems, Beijing, China,2008:844-849.
[34]D'Acierno L, Carteni A, Montella B. Estimation of urban traffic conditions using an Automatic Vehicle Location (AVL) System [J]. European Journal of Operational Research,2009,196(2): 719-736.
[35]Comert G, Cetin M. Queue length estimation from probe vehicle location and the impacts of sample size [J]. European Journal of Operational Research,2009,197(1):196-202.
[36]李梅红,孙棣华,涂平.基于GPS浮动车的城市主干道交通服务水平实时评估模型[J].交通运输工程与信息学报,2008,6(1)：73-78.
[37]于泉,孙玲,荣建.基于浮动车数据调查方法的交义口延误计算[J].重庆交通大学学报(自然科学版),2009,28(2)：283-286.
[38]潘海啸,贾宁.低碳城市的高品质交通：政策、体系与创新[M].上海：同济大学出版社,2011.
[39]温慧敏,扈中伟,郭继孚,等.奥运期间北京市道路网运行分析[J].交通运输系统工程与信息,2008,8(6)：32-37.
[40]朱丽云,温慧敏,孙建平.北京市浮动车交通状况信息实时计算系统[J].城市交通,2008,6(1)：77-80.
[41]王静霞,张国华,黎明.城市智能公共交通管理系统[M].北京：中国建筑工业出版社,2008.
[42]Chorus C G, Molin E J E, Van Wee B. Use and effects of advaneed traveller information service (ATIS):a review of the literature [J]. Transport Reviews,2006,26(2):127-149.
[43]Srinivasan S, Ferreira J. Travel behavior at the household level:understanding linkages with residential choice [J]. Transportation Research Part D,2002,7(3):225-242.
[44]Srinivasan S, Rogersb P. Travel behavior of low-income residents:studying two contrasting locations in the city of Chennai, India [J]. Journal of Transport Geography,2005,13(3):265-274.
[45]Dziekan K, Vermeulen A J. Psychological effects and design preferences for real-time information displays [J]. Journal of Public Transportation,2006,9(1):71-89.
[46]Choocharuku K, Van H T, Fujii S. Psychological effeets of travel behavior on preference of residential location choice [J]. Transportation Research Part A,2008,42(1):116-124.
[47]Kim D, Lehto X Y, Morrison A M. Gender differences in online travel information search: implications for marketing communications on the internet [J]. Tourism Management,2007, 28(2):423-433.
[48]Petrella M, Lappin J. Comparative analysis of customer response to online traffie information in two cities:Los Angeles, California and Seattle, Washington [J]. Transportation Research Reeord No.1886, intelligent transportation systems and vehicle-highway automation, Washington D.C., 2004:10-17.
[49]De Palma A, Picard N. Route choice decision under travel time uncertainty [J]. Transportation Research Part A,2005,39(4):295-324.
[50]Lenz B, Nobis C. The changing allocation of activities in space and time by the use of ICT-"Fragmentation" as a new concept and empirical results [J]. Transportation Research Part A, 2007,41(2):190-204.
[51]Hato E, Taniguchi M, Sugie Y, et al. Incorporating an information acquisition process into a route choice model with multiple information sources [J]. Transportation Research Part C,1999, 7(2-3):109-129.
[52]Chorus C G, Arentze T A, Timmermans H J P, et al. Travelers'need for information in traffic and transit:results from a web survey [J]. Journal of Intelligent Transportation Systems,2007, 11(2):57-67.
[53]Reddy P D V G, Yang H, Vaughn K. M, et al. Design of an artificial simulator for analyzing route choice behavior in the presence of information system [J]. Mathematical and Computer Modelling,1995,22(4-7):119-147.
[54]Lotan T. Effects of familiarity on route choice behavior in the presence of information [J]. Transportation Research Part C,1997,5(3-4):225-243.
[55]Koutsopoulos H N, Lotan T, Yang Q. A driving simulator and its application for modeling route choice in the presence of information [J]. Transportation Research Part C,1994,2(2):91-107.
[56]Boyle L N, Mannering F. Impact of traveler advisory systems on driving speed:some new evidence [J]. Transportation Research Part C,2004,12(1):57-72.
[57]Srinivasan K K, Mahmassani H S. Analyzing heterogeneity and unobserved structural effects in route-switching behavior under ATIS:a dynamic kernel Logit formulation [J]. Transportation Research Part B,2003,37(9):793-814.
[58]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.
[59]Dia H. An agent-based approach to modeling driver route choice behavior under the influence of real-time information [J]. Transportation Research Part C,2002,10(5-6):331-349.
[60]Chen T, Chang H, Tzeng G. Using a weight-assessing model to identify route choice criteria and information effects [J]. Transportation Research Part A,2001,35(3):197-224.
[61]Adler J L, McNally M G. In-laboratory experiments to investigate driver behavior under advanced traveler information systems [J]. Transportation Research Part C,1994,2(3):149-164.
[62]Lyons G D. Towards integrated traveller information [J]. Transport Reviews,2001,21(2): 217-235.
[63]Lyons G D, Urry J. Travel time use in the information age [J]. Transportation Research Part A, 2005,39(2-3):257-276.
[64]Emmerink R H M, Verhoef E T, Nijkam P, et al. Effects of information in road transport networks with recurrent congestion [J]. Transportation,1995,22(1):21-53.
[65]Adler J L. Investigating the learning effeets of route guidance and traffic advisories on route choice behavior [J]. Transportation Research Part C,2001,9(1):1-14.
[66]Jou R, Lam S, Liu Y, et al. Route switching behavior on freeways with the provision of different types of real-time traffic information [J]. Transportation Research Part A,2005,39(5):445-461.
[67]Abdel-Aty M A. Using ordered probit modeling to study the effect of ATIS on transit ridership [J]. Transportation Research Part C,2001,9(4):265-277.
[68]Golob T F, Regan A C. Trucking industry preferences for traveler information for drivers using wireless internet-enabled devices [J]. Transportation Research Part C,2005,13(3):235-250.
[69]Kilpelainen M, Summala H. Effects of weather and weather forecasts on driver behaviour [J]. Transportation Research Part F,2007,10(4):288-299.
[70]Bonsall P. Do we know whether personal travel planning really works [J]. Transport Policy,2009, 16(6):306-314.
[71]Kenyon S, Lyons G. The value of integrated multimodal traveller information and its potential contribution to modal change [J]. Transportation Research Part F,2003,6(1):1-21.
[72]Levinson D. The value of advanced traveler information systems for route choice [J]. Transportation Research Part C,2003,11(1):75-87.
[73]Ng L, Wessels R L, Do D, et al. Statistical analysis of commercial driver and dispatcher requirements for advanced traveler information systems [J]. Transportation Research Part C, 1995,3(6):353-369.
[74]Emmerink R H M, Nijkam P, Rietveld P. Variable message signs and radio traffic information: an integrated empirical analysis of drivers' route choice behaviour [J]. Transportation Research Part A,1996,30(2):135-153.
[75]Englisher L, Juster R, Bregman S, et al. Consumer response to the SmarTraveler ATIS:findings from the second year evaluation [C]. Proceedings of the 1996 Annual Meeting of ITS America, Houston, Texas,1996.
[76]Golob T F, Regan A C. Impacts of information technology on personal travel and commercial vehicle operations:research challenges and opportunities [J]. Transportation Research Part C, 2001,9(2):87-121.
[77]Bhat C R, Sivakumar A, Axhausen K W. An analysis of the impact of information and communication technologies on non-maintenance shopping activities [J]. Transportation Research Part B,2003,37(10):857-881.
[78]Chorus C G, Molin E J E, Arentze T A, et al. Validation of a multimodal travel simulator with travel information provision [J]. Transportation Research Part C,2007,15(3):191-207.
[79]Yim Y, Kanafani A. Expanding usage of cellular phones:user profile and transportation issues [R]. Path Working Paper, UCB-ITS-PRR-91-19, University of California at Berkeley,1991.
[80]Denant-Boemont L, Petiot R. Information value and sequential decision-making in a transport setting:an experimental study [J]. Transportation Research Part B,2003,37(4):365-386.
[81]Huang H J, Li Z C. A multiclass, multicriteria logit-based traffic equilibrium assignment model under ATIS [J]. European Journal of Operational Research,2007,176(3):1464-1477.
[82]Arnott R, De Palma A, Lindsey R. Does providing information to drivers reduce traffic congestion [J]. Transportation Research Part A,1991,25(5):309-318.
[83]Thakuriah P, Sen A. Quality of information given by advanced traveler information systems [J]. Transportation Research Part C,1996,4(5):249-266.
[84]Sinuany-Stern Z, Stern E, Spharadi Z. Information effeets on commuters'behavior under varying network patronage [J]. International Transactions in Operational Research,1999,6(1):89-105.
[85]Yin Y, Yang H. Simultaneous determination of the equilibrium market penetration and compliance rate of advanced traveler information systems [J]. Transportation Research Part A, 2003,37(2):165-181.
[86]Al-Deek H M, Khattak A J, Thananjeyan P. A combined traveler behavior and system performance model with advanced traveler information systems [J]. Transportation Research Part A,1998,32(7):479-493.
[87]Ben-Elia E, Shiftan Y, Erev I. A behavioral approach to modeling route choice decisions with real time information [C]. ETC Proceedings of European Transport Conference, Amsterdam, the Netherlands,2007.
[88]Stern E. Reactions to congestion under time pressure [J]. Transportation Research Part C,1999, 7(2-3):75-90.
[89]Tsirimpa A, Polydoropoulou A, Antoniou C. Modelling the impact of advanced traveller information systems on travellers'behavior:Puget Sound Region case study [C]. ETC Proceedings of European Transport Conference, Strasbourg, France,2005.
[90]Johansson M V, Heldt T, Johansson P. The effects of attitudes and personality traits on mode choice [J]. Transportation Research Part A,2006,40(6):507-525.
[91]Kattak A J, Schofer J L, Koppelman F S. Commuters'enroute diversion and return decisions: analysis and implications for advanced traveler information systems [J]. Transportation Research Part A,1993,27(2):101-111.
[92]Chatterjee K, Mcdonald M. Effectiveness of using variable message signs to disseminate dynamic traffic information:evidenee from field trails in European cities [J]. Transport Reviews, 2004,24(5):559-585.
[93]Conquest L, Spyridakis J, Haselkorn M, et al. The effect of motorist information on commuter behavior:classification of drivers into commuter groups [J]. Transportation Research Part C, 1993,1(2):183-201.
[94]Emmerink R H M, Verhoef E T, Nijkam P, et al. Information policy in road transport with elastic demand:some welfare economic considerations [J]. European Economic Review,1998,42(1): 71-95.
[95]Hamed M M. Abdul-Hussain A A. Drivers'Familiarity with urban route network layout in Amman, Jordan [J]. Cities,2001,18(2):93-101.
[96]Liu H X, Recker W, Chen A.Uncovering the contribution of travel time reliability to dynamic route choice using real-time loop data [J]. Transportation Research Part A,2004,38(6):435-453.
[97]Molin E J E, Timmermans H J P. Traveler expectations and willingness-to-pay for web-enabled public transport information services [J]. Transportation Research Part C,2006,14(2):57-67.
[98]林震,杨浩.交通信息服务条件下的出行选择行为[J].中国公路学报,2003,16(1)：87-90.
[99]毛保华,曾会欣,袁振洲.交通规划模型及其应用[M].北京：中国铁道出版社,1999.
[100]Ben-Akiva M, Lerman S R. Discrete choice analysis:theory and application to travel demand [M]. Cambridge:The MIT Press,1985.
[101]Koppelman F S, Wen C H. The paired combinatorial logit model:properties,estimation and application [J]. Transportation Research Part B,2000,34(2):75-89.
[102]Train K E. Discrete choice methods with simulation [M]. Cambridge:Cambridge University Press,2002.
[103]Kitamura R, Chen C, Pendyala R M. Generation of synthetic daily activity-travel patterns [J]. Transportation Research Record, No.1607,1997:154-162.
[104]Koppelman F S, Wen C H. Alternative nested logit models:structure properties and estimation [J]. Transportation Research Part B,1998,32(5):289-298.
[105]Wen C H, Koppelman F S. Integrated model system of stop generation and tour formation for analysis of activity and travel patterns [J]. Transportation Research Record, No.1676,1999: 136-144.
[106]Wen C H, Koppelman F S. The generalized nested logit model [J]. Transportation Research PartB,2001,35(7):627-641.
[107]Hensher D A, Greene W H. Specification and estimation of the nested logit model:alternative normalizations [J]. Working Paper, Stern School of Business, New York University, NY,2000.
[108]Hensher D A, Ton T T. A comparison of the predictive potential of artificial neural networks and nested logit models for commuter mode choice [J]. Transportation Research Part E,2000, 36(3):155-172.
[109]Loudon W R, Luther D K, Mabry J E, et al. Assessing the effectiveness of TDM and land use strategies for a corridor study in the Puget Sound Region [C]. The 82nd Annual Meeting of the Transportation Research Board,2003.
[110]Bricka S. Analyzing women's trip-chaining patterns to identify potential TOD retail amenity mixes [C]. The 84th Annual Meeting of the Transportation Research Board,2005.
[111]严季,李东根,邵春福.基于非集计模型的城市铁路线路客流量预测研究[J].西安公路交通大学学报,2001,21(3)：68-72.
[112]关宏志,王山川,姚丽亚,等.基于SP和RP数据融合的城市轨道交通选择模型[J].北京工业大学学报,2007,33(2)：203-207.
[113]张政,毛保华,刘明君,等.北京老年人出行行为特征分析[J].交通运输系统工程与信息,2007,7(6)：11-20.
[114]何瑞春,李引珍,张峻屹,等.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.
[115]黄树森,宋瑞,陶媛.大城市居民出行方式选择行为及影响因素研究-以北京市为例[J].交通标准化,2008,(9)：124-128.
[116]李志斌,王炜,杨晨,等.机动车尾气污染对居民出行选择的影响[J].交通信息与安全,2009,27(3)：56-59.
[117]陈团生,岳芳,杨玲玲,等.老年人出行选择行为影响因素研究[J].西南交通大学学报(社会科学版),2007,8(5)：17-21.
[118]张萌,孙全欣,陈金川,等.北京市女性出行行为研究[J].交通运输系统工程与信息,2008,8(2)：19-26.
[119]何保红,王炜,陈峻.城市P&R出行者选择行为模型[J].哈尔滨工业大学学报,2009,41(4)：243-246.
[120]刘崭,高璇.基于非集计模型的公交出行选择预测模型[J].公路,2010,(5)：136-139.
[121]Khattak, A., Schofer, J., Koppelman, F. Effect of traffic reports on commuters route and departure time changes [J]. Journal of Advanced Transportation,1995,29 (2):193-212.
[122]Khattak A J, De Palma A. The impact of adverse weather conditions on the propensity to change travel decisions:A survey of Brussels commuters [J]. Transportation Research Part A, 1997,31(3):181-203.
[123]Khattak A J, Yim Y, Stalker L. Does travel information influence commuter and non-commuter behavior? Results from the San Francisco Bay Area TravInfo Project [J]. Transportation Research Record,1694, Transportation Research Board, Washington, DC,1999:48-58.
[124]Khattak A J, Yim Y, Prokopy L S. Willingness to pay for travel information [J]. Transportation Research Part C,2003,11(2):137-159.
[125]Bhat C R. Analysis of travel mode and departure time choice for urban shopping trips [J]. Transportation Research Part B,1998,32(6):361-371.
[126]Bonsall P. The influence of route guidance advice on route choice in urban networks [J]. Transportation,1992,19(1):1-23.
[127]Wardman M, Bonsall P W, Shires J D. Driver response to variable message signs:a stated preference investigation [J]. Transportation Research Part C,1997,5(6):389-405.
[128]Ben-Akiva M, Bonsall P. Increasing the relevance and utility to practice of transportation research [J]. Transport Policy,2004,11(2):101-103.
[129]Bonsall P, Palmer I. Modelling drivers' car parking behaviour using data from a travel choice simulator [J]. Transportation Research Part C,2004,12(5):321-347.
[130]Bonsall P, Kelly C. Road user charging and social exclusion:the impact of congestion charges on at-risk groups [J]. Transport Policy,2005,12(5):406-418.
[131]Hensher D A, Louviere J J, Hansen D E. The use of mixtures of market and experimental choice data in establishing guideline weights for evaluating competitive bids in a transport organisation [J]. Transport Policy,2000,7(4):279-286.
[132]Hensher D A, King J. Parking demand and responsiveness to supply, pricing and location in the Sydney central business district [J]. Transportation Research Part A,2001,35(3):177-196.
[133]Hensher D A. The sensitivity of the valuation of travel time savings to the specification of unobserved effects [J]. Transportation Research Part E,2001,37(2-3):129-142.
[134]Abdel-Aty M A, Kitamura R, Jovanis P P. Using stated preference data for studying the effect of advanced traffic information on drivers' route choice [J]. Transportation Research Part C, 1997,5(1):39-50.
[135]Ramming M S. Network Knowledge and Route Choice [D]. Massachusetts:Massachusetts Institute of Technology,2002.
[136]Yoshii T, Sasaki K. Information/Communication technologies and travel behaviour [J]. Transportation Research Part C,2010,18(1):1-2.
[137]Sasaki K, Nishii K. Measurement of intention to travel:considering the effect of telecommunications on trips [J]. Transportation Research Part C,2010,18(1):36-44.
[138]Zhao S C, Harata N, Ohta K. The effect of travel time information on route choice behavior:a market segmentation approach [C]. Proceedings of Infrastructure Planning Annual Meeting of JSCE,1995:189-192.
[139]Zhao S C, Muromachi Y, Harata N. A SP model for route choice behavior in response to travel time information with marginal errors [C]. Proceedings of 7th World Conference on Transport Research,1995:41-55.
[140]Zhao S C, Harata N, Ohta K. Using driver's perceptions to model route choice behavior under ITS [C]. Proceedings of IRF Asia-Pacific Regional Meeting,1996:39-46.
[141]Zhao S C, Harata N. Travel information, perceived travel time, and route diversion behavior [C]. Proceedings of the 9th World Conference on Transport Research, Seoul, Korea,2001.
[142]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.
[143]张存保,杨晓光,严新平.交通信息对驾驶员选择行为的影响研究[J].交通与计算机,2004,22(5)：31-34.
[144]李志纯,黄海军.先进的旅行者信息系统对出行者选择行为的影响研究[J].公路交通科技,2005,22(2)：95-99.
[145]黄智芳,鲁丛林.诱导信息条件下驾驶员路径选择行为研究[J].公路工程,2007,32(4)：167-168,177.
[146]干宏程.VMS诱导信息影响下的路径选择行为分析[J].系统工程,2008,26(3)：11-16.
[147]孟超,邵春福,李玮,等.VMS对驾驶人路径选择行为影响的仿真研究[J].城市交通,2009,7(1)：76-81.
[148]Jou R C, Hensher D A, Chen K H. Route-choice behavior of freeway travelers under real-time traffic information provision-application of the best route and the habitual route-choice mechanisms [J]. Transportation Planning and Technology,2007,30(6):545-570.
[149]Frejinger E, Bierlaire M. Capturing correlation with subnetworks in route choice models [J]. Transportation Research Part B,2007,41(3):363-378.
[150]Ben-Elia E, Erev I, Shiftan Y. The combined effect of information and experience on drivers' route-choice behavior [J]. Transportation,2008,35(2):165-177.
[151]Paz A, Peeta S. Behavior-consistent real-time traffic routing under information provision [J]. Transportation Research Part C,2009,17(6):642-661.
[152]徐天东,孙立军,郝媛,等.不同交通信息下网络交通动态路径选择行为[J].同济大学学报(自然科学版),2009,37(8)：1029-1033.
[153]熊轶.交通信息作用下不同风险属性出行者的行为演进[J].武汉理工大学学报(交通科学与工程版),2009,33(2)：279-282.
[154]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[J].交通运输工程学报,2009,9(1)：96-99.
[155]王卫杰,王炜.基于配对组合logit模型的路线选择[J].东南大学学报(自然科学版),2010,40(4)：844-847.
[156]石京,陶立.实时交通信息提供对驾驶员路径选择行为影响量化分析[J].武汉理工大学学报(交通科学与工程版),2010,34(4)：639-643.
[157]Ben-Elia E, Shiftan Y. Which road do I take? A learning-based model of route-choice behavior with real-time information [J]. Transportation Research Part A,2010,44(4):249-264.
[158]Gao S, Frejinger E, Ben-Akiva M. Adaptive route choices in risky traffic networks:a prospect theory approach [J]. Transportation Research Part C,2010,18(5):727-740.
[159]Gao S, Frejinger E, Ben-Akiva M. Cognitive cost in route choice with real-time information:an exploratory analysis [J]. Transportation Research Part A,2011,45(9):916-926.
[160]Xu H L, Zhou J, Xu W. A decision-making rule for modeling travelers' route choice behavior based on cumulative prospect theory [J]. Transportation Research Part C,2011,19(2),218-228.
[161]Kitamura R. A model of daily time allocation todiscretionary out-of-home activities and trips [J]. Transportation Research Part B,1984,18(3):255-266.
[162]Mahmassani H, Liu Y. Dynamics of commuting decision behavior under advanced traveler information systems [J]. Transportation Research Part C,1999,7(2-3):91-107.
[163]Jou R C. Modeling the impact of pre-trip information on commuter departure time and route choice [J]. Transportation Research Part B,2001,35(10):887-902.
[164]Jou, R C, Kitamura R, Weng M C, et al. Dynamic commuter departure time choice under uncertainty [J]. Transportation Research Part A,2008,42(5):774-783.
[165]Ben-Elia E, Ettema D. Rewarding rush-hour avoidance:a study of commuters'travel behavior [J]. Transportation Research Part A,2011,45(7):567-582.
[166]Lemp J D, Kockelman K M, Damien P. The continuous cross-nested logit model:formulation and application for departure time choice [J]. Transportation Research Part B,2010,44(5): 646-661.
[167]刘冬梅,齐彤岩,张可,等.北京市居民出行时间小样本调查分析[J].交通运输系统工程与信息,2009,9(2)：23-26.
[168]杨玲玲,范烨,高峰,等.基于MNL模型的私人小汽车出行时间选择研究[J].交通标准化,2011,1：63-67.
[169]Saleh W, Farrell S. Implications of congestion charging for departure time choice:work and non-work schedule flexibility [J]. Transportation Research Part A,2005,39(7-9):773-791.
[170]李志瑶,隽志才,宗芳.居民出行时间选择及拥挤收费政策[J].交通运输工程学报,2005,5(3)：105-110.
[171]任英伟,陆键,吴守荣,等.高速公路可变收费货车出行者出行时间选择模型研究[J].公路交通科技,2008,25(10)：123-129.
[172]Ozbay K, Yanmaz-Tuzel O. Valuation of travel time and departure time choice in the presence of time-of-day pricing [J]. Transportation Research Part A,2008,42(4):577-590.
[173]Lu C C, Mahmassani H S. Modeling heterogeneous network user route and departure time responses to dynamic pricing [J]. Transportation Research Part C,2011,19(2):320-337.
[174]赵胜川,王喜文,姚荣涵,等.基于Mixed Logit模型的私家车通勤出行时间价值[J].吉林大学学报(工学版),2010,40(2)：406-411.
[175]Liu W G, Zhao S C. The value of a statistical life in road safety:findings from a contingent valuation study in Dalian, China [C]. Proceedings of the 1st International Conference on Transportation Information and Safety,2011:1061-1067.
[176]杨智伟,赵胜川,张迅.公共交通出行者ATIS信息选择行为影响因素研究[J].交通运输系统工程与信息,2009,9(3)：29-35.
[177]杨智伟.基于ATIS的交通出行信息选择行为及支付意愿研究[D].大连：大连理工大学管理学院,2010.
[178]四兵锋,高自友.城市间公路客运的客票票价与其客流量之间的灵敏度分析[J].中国公路学报,2000,13(2)：91-95.
[179]安实,王健.停车需求预测与管理[J].交通运输系统工程与信息,2001,1(3)：212-216.
[180]关宏志.非集计模型-交通行为分析的工具[M].北京：人民交通出版社,2004.
[181]Guan H Z, Sun X D, Liu X M, et al. Modeling parking behavior for better control and pricing:a case study from one of the busiest retail shopping areas in Beijing, China [C]. The 84th Annual Meeting of the Transportation Research Board,2005.
[182]毛荣吕.城市轨道交通客流预测方法研究[D].南京：河海大学交通学院,2005.
[183]Kalmanje S, Kockelman K. M. Credit-based congestion pricing:travel land value and welfare impacts [J]. Transportation Research Record, No.1864,2004:45-53.
[184]Sinha A K, Thakuriah P. Relationship of occupational, industry and socioeconomic characteristics and job start times-evidence from current population survey [C]. The 83rd Annual Meeting of the Transportation Research Board,2004.
[185]Winters P L, Perez R A, Joshi A D, et al. Worksite trip reduction model and manual [C]. The 84th Annual Meeting of the Transportation Research Board,2005.
[186]Senbil M, Kitamura R. Valuing expressways under time pressures [C]. The 85th Annual Meeting of the Transportation Research Board,2006.
[187]Han Q, Timmermans H. Interactive learning in transportation networks under conditions of uncertainty, bounded rationality and strategic choice behavior:a quantal response model [C]. The 85th Annual Meeting of the Transportation Research Board,2006.
[188]柴彦威,刘志林等.中国城市的时空间结构[M].北京：北京大学出版社,2002.
[189]杜华兵,陈金川.北京市实施错时上下班的可行性分析[J].城市交通.2004,4：64-67.
[190]江薇.城市交通需求管理策略及其评价技术研究[D].南京：东南大学交通学院,2004.
[191]隽志才,李志瑶,宗芳.基于活动链的出行需求预测方法综述[J].公路交通科技,2005,22(6)：108-113.
[192]Juan Z C, Zong F, Li Z Y. Study on activity-based time choice model [C]. Urban Transport and the Environment in the 21st Century,2005:659-668.
[193]隽志才,宗芳,富晓艳.TDM政策实施及评价综述[J].中国软科学,2007,1：156-160.
[194]李志纯.交通行为建模与评价研究-网络均衡分析法[D].北京：北京航空航天大学管理学院,2006.
[195]周素红,杨利军.广州城市居民通勤空间特征研究[J].城市交通,2005,3(1)：62-67.
[196]周素红,闫小培.基于居民通勤行为分析的城市空间解读-以广州市典型街区为案例[J].地理学报,2006,61(2)：179-189.
[197]陈征,周恒.苏州居民通勤出行交通方式选择特征研究[J].道路交通与安全,2006,6(8)：34-37.
[198]李志瑶.基于活动的出行需求预测模型研究[D].长春：吉林大学交通学院,2006.
[199]褚浩然,郑猛,杨晓光,等.出行链特征指标的提取及应用研究[J].城市交通,2006,4(2)：64-67.
[200]陈团生.通勤者出行行为特征与分析方法研究[D].北京：北京交通大学交通学院,2007.
[201]宗芳.基于非集计模型的交通需求管理策略评价研究[D].长春：吉林大学交通学院,2008.
[202]周钱.基于家庭决策的交通行为和需求预测研究[D].北京：清华大学土木水利学院,2008.
[203]孙绍荣,宗利永,鲁虹.理性行为与非理性行为[M].上海：上海财经大学出版社,2007.
[204]Von Neumann J, Morgenstern O. Theories of games and economic behavior [M]. Princeton: Princeton University Press,1947.
[205]Simon H A. Rational choice and the structure of the environment [J]. Psychological Review, 1956,6(2):129-138.
[206]Kahneman D, Tversky A. Prospect Theory:an analysis of decisions under risky [J]. Econometric,1979,47(3):263-291.
[207]Katsikopoulos K V, Fisher D L. Duse-Anthony Y, et al. Risk attitude reversals in drivers' route choice when range of travel time is provided [J]. Human Factors,2002,44(3):466-473.
[208]徐红利,周晶,陈星光.基于前景理论的路径选择行为规则分析与实证[J].交通运输系统工程与信息,2007,7(6)：95-101.
[209]赵凛.张星臣.基于前景理论的路径选择行为建模及实例分析[J].土木工程学报,2007,40(7)：82-86.
[210]De Blaeij A T, VanVuuren D J. Risk perception of traffic participants [J]. Accident Analysis & Prevention,2003,35(2):167-175.
[211]Fujii S, Kitamura R. Drivers' mental representation of travel time and departure time choice in uncertain traffic network conditions [J]. Networks and Spatial Economics,2004,4(3):243-256.
[212]Senbil M, Kitamura R. Reference points in commuter departure time choice:a prospect theoretic test of alternative decision frames [J]. Journal of Intelligent Transportation Systems, 2004,8(1):19-31.
[213]Avineri E. A cumulative prospect theory approach to passengers' behavior modeling:waiting time paradox revisited [J]. Journal of Intelligent Transportation Systems,2004,8(4):195-204.
[214]张杨.不确定环境下城市交通中车辆路径选择研究[D].成都：西南交通大学交通运输学院,2006.
[215]Garling T. Behavioral assumptions overlooked in travel-choice modeling [M]. Travel Behavior Research:Updating the Stale of Play. Oxford, UK:Pergamon,1998.
[216]Ben-Akiva M, Morikawa T. Estimation of switching models from revealed preference and stated intentions [J]. Transportation Research Part A,1990,24(6):485-495.
[217]刘灿齐.现代交通规划学[M].北京：人民交通出版社,2001.
[218]Louviere J J, Henshe D A, Swait J D. Stated choice methods:analysis and application [M]. Cambridge:Cambridge University Press,2000.
[219]Louviere J J, Woodworth G. Design and analysis of simulated consumer choice or allocation experimenis:an approach based on aggregate data [J]. Journal of Marketing Research,1983, 20(4):350-367.
[220]Hensher D A, Barnard P O, Truong T P. The role of stated preference methods in studies of travel choice [J]. Journal of Transport Economics and Policy,1988,22(1):45-67.
[221]Fowkes T, Wardman M. The design of stated preference travel choice experiments [J]. Journal of Transport Economics and Policy,1988,22(1):27-44.
[222]Bradley M. Realism and adaptation in designing hypothetical travel choice concepts [J]. Journal of Transport Economics and Policy,1988,22(1):121-137.
[223]Kroes E, Sheldon R J. Stated preference method:an introduction [J]. Journal of Transport Economics and Policy,1988,22(1):22-25.
[224]Bates J J. Econometric Issues in stated preference analysis [J]. Journal of Transport Economics and Policy,1988,22(1):59-69.
[225]Ortuzar J D, Garrido R A. A practical assessment of stated preferences methods [J]. Transportation,1994,21(3):289-305.
[226]Fowkes A S, Button K L. An evaluation of car ownership forecasting techniques [J]. International Journal of Transport Economics,1996,4(2):115-143.
[227]Kuppam A R, Pendyala R M, Gollakoti M A V. Stated response analysis of effectiveness of parking pricing strategies for transportation control [J]. Transportation Research Board, No.1649, TRB, National Research Council, Washington D.C.,1998:39-46.
[228]Khattak A J, Yim Y, Stalker L. Willingness to pay for travel information:combining revealed and stated preferences with a random effects negative binomial regression model [C]. The 79th Annual Meeting of the Transportation Research Board,1999.
[229]赵鹏,藤原章正,杉惠赖宁.SP调查方法在交通预测中的应用[J].北方交通大学学报,2000,24(6)：29-32.
[230]Fowler F J,孙振东(译).调查研究方法[M].重庆：重庆大学出版社,2006.
[231]Czaja R, Blair J,沈崇麟(译).抽样调查设计导论[M].重庆：重庆大学出版社,2007.
[232]方开泰,马长兴.正交与均匀试验设计[M].北京：科学出版社,2001.
[233]隽志才,鲜于建川.交通信息作用下的活动-出行决策行为研究[J].中国公路学报,2008, 21(4)：88-92
[234]薛薇.基于SPSS的数据分析[M].北京：中国人民大学出版社,2006.
[235]鲍威斯,谢宇.分类数据分析的统计方法(第二版)[M].北京：社会科学文献出版社,2009.
[236]王济川,郭志刚Logistic回归模型-方法与应用[M].北京：高等教育出版社,2001.
[237]林光平.计算计量经济学[M].北京：清华大学出版社,2003.
[238]王树盛,黄卫,陆振波Mixed Logit模型及其在交通方式分担中的应用研究[J].公路交通科技,2006,23(5)：88-91.
[239]张羽祥,赵胜川.基于Monte Carlo模拟的Mixed Logit模型求解研究[J].交通标准化,2009(1)：112-115.
[240]李华民,黄海军,刘剑锋.混合Logit模型的参数估计与应用研究[J].交通运输系统工程与信息,2010,10(5)：73-78.
[241]张羽祥.私家车通勤出行时间价值研究[D].大连：大连理工大学管理学院,2008.
[242]田璠.基于道路拥挤收费的出行时间价值研究[D].大连：大连理工大学数学科学学院,2009.
[243]McFadden D, Train K. Mixed MNL models for discrete response [J]. Journal of Applied Econometrics,2000,15:447-470.
[244]Boyd J, Mellman J. The effect of fuel economy standards on the U.S. automotive market:a hedonic demand analysis [J]. Transportation Research Part A,1980,14:367-378.
[245]Cardell S, Dunbar F. Measuring the societal impacts of automobile downsizing [J]. Transportation Research Part A,1980,14:423-434.
[246]Train K, McFadden D, Ben-Akiva M. The demand for local telephone service:a fully discrete model of residential calling patterns and service choice [J]. The Rand Journal of Economics, 1987,18:109-123.
[247]Ben-Akiva M, Bolduc D, Bradley M. Estimation of switching models from revealed preferences and stated intentions [J]. Transportation Research Reeord,1993,1413:88-97.
[248]Bhat C. Accommodating variations in responsiveness to level-of-service variables in travel mode choice models [J]. Transportation Research PartA,1980,32:455-507.
[249]Brownstone D, Train K. Forecasting new product penetration with flexible substitution patterns [J]. Journal of Econometrics,1999,89:109-129.
[250]Erdem T. A dynamic analysis of market structure based on panel data [J]. Journal of Marketing Research,1996,32:1-16.
[251]Revelt D, Train K. Mixed logit with repeated choices [J]. Review of Economics and Statistics, 1998,80:647-657.
[252]Bhat C. Incorporating observed and unobserved heterogeneity in urban work mode choice modeling [J]. Transportation Science,2000,34:228-238.
[253]Chesher A, Santos-Silva J. Taste variation in discrete choice models [J]. Review of Economic Studies,2002,69:62-78.
[254]Wedel M, Kamakura W. Market segmentation:conceptual and methodological foundations (2nd edition) [M]. Boston:Kluwer Academic Publishers,2000.
[255]Ainsile A, Andrews R, Currim I. An empirical comparison of logit choice models with discrete versus continuous representation of heterogeneity [J]. Journal of Marketing Research,2002,39: 479-487.
[256]陈家鼎,郑忠国.概率与统计[M].北京：北京大学出版社,2007.
[257]徐钟济.蒙特卡罗方法[M].上海：上海科学技术出版社,1985.
[258]赵凛.基于前景理论的出行决策模型及ATIS仿真实验研究[D].北京：北京交通大学交通运输学院,2007.
[259]张奇瑞.基于前景理论的交通诱导行为分析与仿真实验研究[D].北京：北京交通大学交通运输学院,2008.
[260]徐红利.基于有限理性的城市交通系统均衡与拥挤收费策略研究[D].南京：南京大学管理学院,2011.
[261]Xu H L, Zhou J, Xu W. A decision-making rule for modeling travelers'route choice behavior based on cumulative prospect theory [J]. Transportation Research Part C,2011,19(2):218-228.
[262]Xu H L, Lou Y Y, Yin Y F, et al. A prospect-based user equilibrium model with endogenous reference points and its application in congestion pricing [J]. Transportation Research Part B, 2011,45(2):311-328.
[263]Tversky A, Kahneman D. Advances in prospect theory:cumulative representation of uncertainty [J]. Journal of Risk and Uncertainty,1992,9:195-230.
[264]Bell D E. Regret in decision making under uncertainty [J]. Operations Research,1982,30: 961-981.
[265]Loomes G, Sugden R. Regret theory:an alternative theory of rational choice under uncertainty [J]. The Economic Journal,1982,92:805-824.
[266]Fishburn P C. Nontransitive measurable utility [J]. Journal of Mathematical Psychology,1982, 26:31-67.
[267]Chorus C G, Arentze T A, Timmermans H J P. A random regret-minimization model of travel choice [J]. Transportation Research Part B,2008,42(1),1-18.
[268]Chorus C G, Molin E J E, VAN WEE B, et al. Responses to transit information among car-drivers:regret-based models and simulations [J]. Transportation Planning and Technology, 2006,29(4):249-271.
[269]Chorus C G, De Jong G C. Modeling experienced accessibility for utility-maximizers and regret-minimizers [J]. Journal of Transport Geography.2011,19(6):1155-1162.
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