【作者】 周伟；

【导师】 赵胜川；

【作者基本信息】 大连理工大学 ， 交通系统工程， 2012， 博士

【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。更多还原

【Abstract】 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.更多还原