Specification issues in a generalised random parameters attribute nonattendance model

An extensive literature has recognised that when travel choices are made, only a subset of the attributes of the choice alternatives may be considered or attended to by each decision maker. Numerous econometric approaches have been employed to identify attribute nonattendance (ANA), with the most prevalent in the literature being an adaptation of the latent class model. However, the two latent class structures so far employed either incur a potentially very high parametric cost, or rely on an assumption that nonattendance is independent across all attributes. We present a generalised model that allows for an arbitrary degree of correlation of nonattendance across attributes. In the presented stated choice study investigating short haul flights, this generalised model outperforms the existing approaches. Like two recent papers, the model handles both ANA and preference heterogeneity by combining continuously distributed random parameters with latent classes. However, we present recommendations regarding a number of identification issues stemming from the combination of these two forms of random parameters not covered in those papers. Further, covariates can be introduced into our generalised model to allow insights to be gained into ANA behaviour. We investigate stated ANA as a covariate, and find inferred ANA rates to be more aligned with stated ANA responses than alternative methods.     

Modelling the potential for cycling in access trips to bus,train and metro in Rio de Janeiro

Most studies that address the integration of cycling and public transport (PT) focus on developed countries and deal with multi-modal bicycle-train trips. Little is known about the integration of cycling and other main modes such as bus and metro, especially in developing countries, where entirely different socio-economic and trip making conditions prevail. The aim of this study is to model the propensity of current PT users to shift to the bicycle in access trips to bus stops, train and metro stations in Rio de Janeiro, Brazil. Interviews were conducted to collect data on the socio-economic characteristics of the interviewee, trip and spatial characteristics and self-reported barriers and motivators for bicycle use. Two binary logit models were estimated to predict the main factors affecting the propensity to use a bicycle as feeder mode to PT. The results show that socio-economic characteristics as well as barriers and motivators are important factors to explain propensity for bike and ride. The barriers’ model reveals that personal constraints, living too close to the PT boarding point, current parking conditions and public safety play a role. For the motivators’ model, changing home location, owning a bicycle, implementation of cycle ways and improvement in parking conditions are explanatory. Policy recommendations are formulated to increase bicycle ownership and improve cycling infrastructure.     

Investigating preference heterogeneity in Value of Time (VOT) and Value of Reliability (VOR) estimation for managed lanes

This paper presents an empirical study in investigating user heterogeneity of Value of Time (VOT) and Value of Reliability (VOR). Combined Revealed Preference (RP) and Stated Preference (SP) data were used to understand traveler choice behavior regarding the usage of managed lanes (MLs). The data were obtained from the South Florida Expressway Stated Preference Survey, which focused on automobile drivers who had traveled on the I-75, I-95, or SR 826 corridors in South Florida. Mixed logit modeling was applied and indicated an average value of $13.55 per hour for VOT and $16.13 per hour for VOR. Potential sources of heterogeneity in user sensitivities to time, reliability, and cost were identified and quantified by adding interaction effects of the variables in the mixed logit model. The findings indicated that various socioeconomic demographic characteristics and trip attributes contributed to the variations in VOT and VOR at different magnitudes. The results of this study contribute to a better understanding on what attributes lead to higher or lower VOT and VOR and to what extent. These findings can be incorporated into the demand forecasting process and lead to better estimates and enhanced analytical capabilities in various applications, such as toll feasibility studies, pricing strategy and policy evaluations, and impact analysis.     

Longer-term changes in mode choice decisions in Chennai: a comparison between cross-sectional and dynamic models

The rapid and continuing changes in travel and mobility needs in India over the last decade necessitates the development and use of dynamic models for travel demand forecasting rather than cross-sectional models. In this context, this paper investigates mode choice dynamics among workers in Chennai city, India over a period of five years (1999–2004). Dynamics in mode choice is captured at four levels: exogenous variable change, state-dependence, changes in users’ sensitivity to attributes, and unobserved error terms. The results show that the dynamic models provide a substantial improvement (of over 500 log-likelihood points and ρ² increases from 44% to 68%) over the cross-sectional model. The performance was compared using two illustrative policy scenarios with important methodological and practical implications. The results indicate that cross-sectional models tend to provide inflated estimates of potential improvement measures. Improving the Level of Service (LOS) alone will not produce the anticipated benefits to transit agencies, as it fails to overcome the persistent inertia captured in the state-dependence factors. The results and models have important applications in the context of growing motorization and congestion management in developing countries.

Investigating the joint choice behavior of intercity transport mode and high‐speed rail cabin with a strategy map

This paper investigates the joint choice behavior of intercity transport modes and high‐speed rail cabin class within a two‐dimensional choice structure. Although numerous studies have been conducted on the mode choice behavior, little is known about the influence of cabin class on their intercity traveling choice. Hence, this study is conducted with a revealed preference survey to investigate the intercity traveling behavior for the western corridor of Taiwan. The results of nested logit model reveal that a cabin strategy has a more significant influence on cabin choice than on mode choice. Furthermore, this study proposes a new strategy map concept to assist transport operators in defining and implementing their pricing strategies. The results suggest that to capture a higher market share, high‐speed rail operators should choose an active price reduction strategy, while bus and rail operators are advised to implement a passive price increase strategy to raise unit revenue. Copyright © 2014 John Wiley & Sons, Ltd.     

呼和浩特至张家口客专本线客流预测研究

随着社会经济的快速发展,我国铁路客运业也得到迅猛发展。铁路客运量的预测是运能分配、产品设计以及制定营销策略的基础。使用我国铁路客流预测普遍采用的“四阶段”预测法对新建呼和浩特市到张家口市本线客流进行预测。在有无呼和浩特至张家口客运专线的情况下,首先,使用重力模型对本线直接客运需求进行预测;其次,使用logit模型对直接需求进行运输方式分配;最后,在有呼和浩特至张家口客运专线的情况下对产生的转移运量和诱增运量分别进行计算。计算结果证明,呼和浩特至张家口客运专线对于本线旅客出行影响较大,结论可为本线旅客列车开行方案制定提供依据。     

Vehicle type choice under the influence of a tax reform and rising fuel prices

Differentiated vehicle taxes are considered by many a useful tool for promoting environmentally friendly vehicles. Various structures have been implemented in several countries, e.g. Ireland, France, The Czech Republic, and Denmark. In many countries the tax reforms have been followed by a steep change in new vehicle purchases toward more diesel vehicles and more fuel-efficient vehicles. The paper analyses to what extent a vehicle tax reform similar to the Danish 2007 reform may explain changes in purchasing behaviour. The paper investigates the effects of a tax reform, fuel price changes, and technological development on vehicle type choice using a mixed logit model. The model allows a simulation of the effect of car price changes that resemble those induced by the tax reform. This effect is compared to the effects of fuel price changes and technology improvements. The simulations show that the effect of the tax reform on fuel efficiency is similar to the effect of rising fuel prices while the effect of technological development is much larger. The conclusion is that while the tax reform appeared in the same year as a large increase in fuel efficiency, it seems likely that it only explains a small part of the shift in fuel efficiency that occurred and that the main driver was the technological development.     

基于D-optimal试验设计的公共交通出行logit模型

以成都到龙泉片区的交通通道为研究对象,假设通道开通地铁的情况下,采用D-optimal试验设计意愿调查问卷,选择费用、时间等变量以及个人属性作为效用变量,建立公共交通出行的多项logit模型,结合意愿调查数据对模型进行求解,分析通道中公共交通出行选择行为,并预测成都到龙泉片区主要交通方式的客流分担率。分析表明,地铁将承担通道中大部分的客流。     

基于广义巢式Logit 的多用户多准则随机 用户平衡模型

介绍了广义巢式Logit 的基本理论,在此基础上,考虑具有不同时间价值的多种 用户类别出行者,构造了基于广义巢式Logit 的多用户多准则随机用户平衡的等价数学 规划模型,并对该模型的等价性和唯一性进行了证明.设计了求解所提出的随机用户平衡 模型的基于路径的相继平均法,通过一个算例验证了所设计算法的有效性. 分析了分散 系数变化对交通分配结果的影响,最后与多项式Logit 的分配结果进行对比.算例结果表 明,本文所提出的模型能够克服多项式Logit 模型的IIA 特性,设计的算法具有较高的求 解效率.