浅谈隧道监控系统控制预案的编制策略

结合汾离高速公路薛公岭隧道监控机电系统建设的实际情况．针对隧道可能出现的突发事件，探讨了隧道控制预案编制的基本步骤、程序及要点，以有效发挥隧道监控系统对提高道路整体服务水平的作用。     

一类有竞争的物流配送中心选址模型

对已有多个配送中心存在的前提出，新增配送中心为获取最大市场占有量如何进行有效的选址决策问题进行了研究，建立了一个选址决策模型，把求解的问题归结为无约束的非线性规划问题，并给出了迭代算法，最后对如何解决考虑多种选址影响因素及多个新增配送中心的复杂情况进行了讨论。     

基于Nested Logit 模型的铁路旅客客运产品选择研究

通过成都-武汉既有线出行旅客的问卷调查,以及样本数据的归纳分析,对旅客客运产品选择行为特征进行描述.基于随机效用最大化理论,以乘车方式与客运产品作为选择肢,旅客主体、出行特性及列车服务特性的各项指标作为效用变量,构建了乘车方式位于上层、客运产品位于下层的Nested Logit 模型.模型的上下层参数标定结果表明,旅客的收入状况、出行目的、出行距离、列车票价及运行时间对其乘车方案选择具有显著影响,旅客的年龄、出行费用来源、收入状况、出行距离,以及列车票价、运行时间对其客运产品选择具有显著影响.模型能较为准确地反映铁路客运产品的实际需求,从而为其合理设计与调整提供理论依据.     

城市轨道交通车辆基地室外综合管沟的应用研究

室外管线综合设计是城市轨道交通车辆基地设计的重点和难点,通常室外管线多以直埋的方式敷设于地下,但这种方式在设计、施工、运营维护阶段均存在着一些问题,因此提出了在室外设置综合管沟的方式,尽可能解决目前出现的问题.针对相关问题,提出了设置室外综合管沟的必要性和意义,从入沟管线种类分析、综合管沟管线布置原则、断面设计、特殊节点设计以及管沟附属工程等方面介绍室外综合管沟在车辆基地的具体应用情况.     

汽车保险中奖惩系统的马尔可夫分析

利用马尔可夫分析,求出了驾驶员最终处于奖惩系统各阶上的概率,同时,马尔可夫分析还可以判断出在确定代表驾驶员实际风险的调整保费时奖惩系统的功效,并举例给出了求解奖惩系统的稳态保费及Loimaranta功效具体的计算方法.     

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.