基于实时路况信息的驾驶员路线选择行为模型

从驾驶员出行路线选择的影响因素出发,将实时路况信息影响引入路线选择行为中,在分析实时路况信息及其评价指标的基础上,考虑路线选择行为中可能存在的相关性因素,构建驾驶员路线选择GNL（Generalized Nested Logit）模型,并建立基于可获得实时路况信息满意度的驾驶员路线选择行为效用函数,以求更加客观地反映驾驶员实际路线选择行为。     

票价对轻轨分担率的影响研究——以广州市萝岗轻轨为例

为研究不同的定价策略下轻轨对其影响范围内不同人群的吸引力大小,运用多项 Logit 模型效用最大化理论,并以广州市萝岗轻轨为例,在大量居民出行调查数据基础上,对模型进行参数标定,分析比较小汽车出行﹑电单车、常规公交出行﹑轻轨交通出行4者的效用比,最终确定目标年不同票价政策下各种交通方式的分担率。      

出行方式与出发时间联合选择的分层Logit模型

基于随机效用最大化理论,选取出行者特征、行程特性与出行方式服务水平作为效用变量,以出行方式与出发时间作为选择肢,构建了出发时间位于下层与出行方式位于下层的2种居民出行NL模型。分析了北京市居民出行样本数据,并模拟了在早高峰时段对小汽车出行收取费用时,小汽车出行者出行行为的变化。计算结果表明:与传统MNL模型相比,NL模型具有更好的统计学特征,调整后的拟合优度由0.338增大至0.404;在2种NL模型中,出发时间位于下层的结构对样本数据的适应性更强;当早高峰时段小汽车出行收取费用为5元时,72.6%的小汽车出行者坚持原有出行方式与出发时间,22.4%的小汽车出行者坚持小汽车方式,但会改变出发时间,4.8%的小汽车出行者改用公共交通方式,但出发时间不变,仅0.2%的小汽车出行者同时改变出行方式与出发时间;当收取费用为10元时,51.7%的小汽车出行者坚持原有出行方式与出发时间,40.4%的小汽车出行者坚持小汽车方式,但会改变出发时间,7.9%的小汽车出行者改用公共交通方式,但出发时间不变;当收取费用为20元时,27.5%的小汽车出行者坚持原有出行方式与出发时间,60.6%的小汽车出行者坚持小汽车方式,但会改变出发时间,11.9%的小汽车出行者改用公共交通方式,但出发时间不变。     

Choosing Public Transport—Incorporating Richer Behavioural Elements in Modal Choice Models

The development of behaviourally richer representations of the role of well-established and increasingly important influences on modal choice, such as trip time reliability and accounting for risk attitude and process rules, has moved forward at a fast pace in the context of automobile travel. In the public transport setting, such contributions have, with rare exception, not been considered. In this paper, we discuss and empirically illustrate the merits of advanced modelling developments aimed at improving our understanding of public transport choice, namely the inclusion of reliability in extended expected utility theoretic forms, to recognize risk attitude and perceptual conditioning, the consideration of passenger crowding and its inclusion in linear additive models, and the role of multiple heuristics in representing attribute processing as a way of conditioning modal choice. We illustrate the mechanics of introducing these behaviourally appealing extensions using a modal choice data set collected in Sydney.     

A State-of-the-Art Review: Developments in Utility Theory,Prospect Theory and Regret Theory to Investigate Travellers' Behaviour in Situations Involving Travel Time Uncertainty

Abstract

Despite the wide use of utility theory to model travellers' behaviour, the interest in non-expected utility theories has increased due to their potential to capture more realistic behaviour. A main question raised is whether travellers are better described as utility maximizers or should be qualified differently.

This paper presents a literature review on the use of expected utility theory (EUT), prospect theory (PT) and regret theory (RT) to model travellers' behaviour. Gaps in the literature are identified and a discussion about advantages and disadvantages of each theory is presented. A case study illustrates the differences between the theories.

Under certain conditions, PT and RT restrict themselves to EUT. Their added value, however, is the possibility of capturing loss aversion, risk aversion and risk-seeking (PT) and regret aversion (RT). On the practical level, the use of EUT is well established, while contributions of PT and RT are marginal. On the theoretical level, however, RT seems to be (marginally) more suitable to model travellers' behaviour, while EUT and PT are equally suitable. This suggests that the large use of EUT is highly influenced by its very tractable framework. We do not claim the superiority of any theory, but propose to compare them through a systematic review.     

Accommodating risk in the valuation of expected travel time savings

Valuation of travel time savings is a critical measure in transport infrastructure appraisal, traffic modelling and network performance. It has been recognised for some time that the travel times associated with repeated trips are subject to variation, and hence there is risk embedded in the treatment of expected travel time. In the context of the expected utility framework, we use a nonlinear probability weighting function to accommodate choice made under risk. Although the empirical findings suggest small differences between the value of expected travel time savings (VETTS) in the presence and absence of risk, the mean estimate does make a noticeable difference to time benefits when applied to real projects. By incorporating nonlinear probability weighting, our model reveals that the probabilities associated with specific travel times that are shown to respondents in the choice experiment are transformed, resulting in overweighting of outcomes with low probabilities and underweighting of outcomes with high probabilities. Copyright © 2011 John Wiley & Sons, Ltd.     

���й�����ͨ������������ģ���о�

城市公共交通财政补贴是落实优先发展公共交通战略的关键环节之一,由于城市公共交通财政补贴测算涉及面广,构建具有可操作性的测算模型和完善测算方法是城市交通可持续发展的一个重要课题。本文利用效用函数导出使用者乘坐公共交通的需求函数,建立使用者收入、企业经营成本和政府财政补贴之间的博弈模型,分析对公共交通使用者实行分类补贴的优势所在,并提出实际运用中具有可操作性的补贴测算模型。最后,文章结合北京市常规公交的调查数据进行案例分析,分析结果表明分类补贴的方法和补贴测算模型不仅能很好地满足使用者的公交出行需求,而且可以有效测算公交财政补贴金额,实现政府补贴的效用最大化,为城市公共交通补贴测算提供新的思路&;#61472;。     

����Լ�������³��е�·��ͣ����������ģ�ͼ��㷨

在城市交通系统中,动态交通和静态交通之间存在着密切的关系,两者之间既相互促进又相互制约。本文对城市交通网络中的道路及停车流量分配问题进行了探讨和研究。充分考虑了影响出行者停车选择的主要因素,包括车辆行驶费用、停车费用以及步行费用等,构造了停车场广义效用函数,采用Logit模型来描述出行者的停车选择概率,并假定出行者的路径选择行为满足Wardrop平衡准则。在此基础上,综合考虑交通网络中出行者的路径选择和停车选择问题,提出了具有能力约束的城市道路及停车流量分配的用户平衡模型,并给出了求解该模型的算法。最后通过一个简单算例,对模型及算法进行了验证,分析了不同交通需求及停车收费条件下停车流量的变化情况。     

城市公交线路车辆配置模型研究

本文在研究公交客流出行特性基础上构建了公交线路车型结构优化模型,在确定线路配车数的基础上进行了运力规划的冗余优化,进而确定了该线路的车辆规模。     

机动车尾气污染对居民出行选择的影响

机动车尾气排放造成的空气污染对人体健康的危害逐渐被医学界证实。城市居民选择交通工具以及出行路线时,道路机动车尾气污染会影响其选择行为。文中通过居民出行问卷调查证实部分出行者会采取规避行为降低机动车尾气污染对个人健康的危害,建立表征出行者与污染气体接触程度的曝露指数模型,通过数据拟合建立增量时间转化模型,以出行时间增加值的形式定量得到机动车尾气污染对居民出行的影响程度,对离散选择模型的效用函数进行了修正,并给出了算例。