XML5163XLJ13型旅居客车开发

介绍XML5163XLJ13型旅居车的总体布置、结构特点,以及开发旅居客车的前景.     

Experimental design influences on stated choice outputs: An empirical study in air travel choice

Discrete choice experiments are conducted in the transport field to obtain data for investigating travel behaviour and derived measures such as the value of travel time savings. The multinomial logit (MNL) and other more advanced discrete choice models (e.g., the mixed MNL model) have often been estimated on data from stated choice experiments and applied for planning and policy purposes. Determining efficient underlying experimental designs for these studies has become an increasingly important stream of research, in which the objective is to generate stated choice tasks that maximize the collected information, yielding more reliable parameter estimates. These theoretical advances have not been rigorously tested in practice, such that claims on whether the theoretical efficiency gains translate into practice cannot be made. Using an extensive empirical study of air travel choice behaviour, this paper presents for the first time results of different stated choice experimental design approaches, in which respective estimation results are compared. We show that D-efficient designs keep their promise in lowering standard errors in estimating, thereby requiring smaller sample sizes, ceteris paribus, compared to a more traditional orthogonal design. The parameter estimates found using an orthogonal design or an efficient design turn out to be statistically different in several cases, mainly attributed to more or less dominant alternatives existing in the orthogonal design. Furthermore, we found that small designs with a limited number of choice tasks performs just as good (or even better) than a large design. Finally, we show that theoretically predicted sample sizes using the so-called S-estimates provide a good lower bound. This paper will enable practitioners in better understanding the potential benefits of efficient designs, and enables policy makers to make decisions based on more reliable parameter estimates.     

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城市公共交通乘客出行成本的量化研究,对于科学合理地评价公共交通系统的社会效益意义重大,而出行时间价值是进行乘客出行成本估计的一个重要环节. 本文以北京市市区居民SP调查数据为依托,通过分析公共交通出行时间价值的影响因素,选取Logit模型为基础模型,引入“出行者收入”作为模型新增变量,并针对工作商务、社会娱乐两种出行目的在不同换乘情况下出行时间价值模型进行参数标定,建立了基于SP调查数据的改进型时间价值求解模型,并计算得到北京市公共交通出行者在不同出行目的和有无换乘情况下的换乘时间价值、候车时间价值以及运行时间价值. 研究发现,工作商务出行目的出行时间价值普遍高于社会娱乐的出行时间价值,出行者在不同出行目的和有无换乘情况下的候车时间价值,大于换乘时间价值以及运行时间价值,并且有换乘情况下的候车时间价值大于无换乘情况下的候车时间价值.     

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在城市轨道交通的线路网络形成、实行一票换乘并伴随投资主体多元化时,需要建立公平公正的票务清分机制,本文提出一个基于乘客旅行实际时间分布计算各路径上乘客比例的新方法.根据交通卡中的进出站的时间记录,计算出在一段时间内在一对出入站之间完成旅行的所有乘客的时间分布,以这个分布为依据计算在这段时间里各路径上的乘客比例.采用数值模拟的方法在一对有两条有效路径的出入站间产生乘客旅行时间的数据,然后根据这些数据进行客流比例计算.结果表明,即使两条路径的运营时间差异很小也能实现较准确的比例划分,这种动态计算客流分布的方法能更准确地反映实际客流分布.     

Modeling Correlation of Family Holiday Activities Based on Structural Equation Model

Previous researches in activities-decision have more in-depth study in context of individuals, while less work has been done within household activity decisions. The structural equation model is applied to analyze the relationship of three household activity categories on holiday using data from 2009 Jinan travel survey. Six attributes were first chosen as exogenous variables for the structural equation model. Meanwhile, six activity characteristic indexes were selected as endogenous variables including activity duration time and activity times in three kinds of activity, hereby Subsistence activity, maintenance activity and discretionary activity. respectively. Then, the paper attempted to discuss the correlation of all types of activities behavior through analyzing not only the influence of household economics and family members factors on activity but the correlation of holiday activities. The research shows that complex relationships among composition of the family, economic status, and activities-decision can be captured by the structural equation model structure. Specifically, the results show that flexibility of three categories activities will affect the activities of decision-making.     

交通拥堵反思

通过对交通拥堵进行反思,认为交通拥堵是充满活力的成功城市的伴生品,应从不同角度考虑拥堵问题.提出了十项有别于传统观点的提议,主要包括:机动性至关重要,交通拥堵是社会、经济活力的象征;道路扩容效果短暂,并会诱发潜在需求,但仍可带来一定的社会、经济效益;土地使用对出行行为的改变需要长期的努力;紧凑型发展会加剧交通拥堵;降低...     

城市土地利用特征对居民出行方式的影响——以深圳市为例

为缓解日益严重的城市交通问题、优化居民出行方式,有必要研究城市土地利用与交通系统的协调问题.以深圳市为例,应用多元Logit模型(MNL模型),纳入城市土地利用变量与出行者的家庭、社会、经济等变量,分析其对居民工作与非工作出行方式的影响.研究结果表明,出行起点的城市区位是影响居民出行方式的重要因素之一.相对于组团中心和...     

基于WebGIS的铁路旅客辅助决策系统的研究与开发

以旅客出行和换乘中转站的选择及优化作为实现目标,研究了针对旅客不同出行需求的查询算法,开发出基于WebGIS的铁路旅客出行辅助决策系统.系统为旅客出行决策提供综合查询信息,将最优线路以直观的方式显示出来,实现乘车线路的交互式查询和地理信息系统的实时衔接,后台决策软件综合考虑线路状况,实时更新铁路客运时刻表数据库,给出最优乘车路径选择.     

区域运输通道内影响旅客出行方式选择的因素

首先给出运输通道的概念,阐述我国现有的旅客出行方式。从我国现有的这些交通方式入手,探讨影响旅客出行方式选择的因素,即影响人们选择出行方式的因素可分为宏观因素和微观因素。宏观因素如社会经济发展水平、城市化水平、交通政策等,决定着出行方式的总结构;微观因素如出行目的和出行时间,则决定交通方式的选择。     

基于公交智能调度系统的公交换乘算法实现

通过对城市居民公交出行选择影响因素和选择逻辑的分析,利用地理信息系统（GIS）技术构建公交换乘数据模型和公交智能调度系统数据计算出行时间,以此为基础实现以最少换乘次数为第一目标,出行时间最短为第二目标的公交换乘算法。该算法考虑了步行换乘、行驶时间、换乘时间及公交线路上、下行因素对换乘查询的影响,能够较快地提供公交换乘方案。