Factors affecting car ownership and mode choice in rail transit-supported suburbs of a large Chinese city

As Chinese cities continue to grow rapidly and their newly developed suburbs continue to accommodate most of the enormous population increase, rail transit is seen as the key to counter automobile dependence. This paper examines the effects of rail transit-supported urban expansion using travel survey data collected from residents in four Shanghai suburban neighborhoods, including three located near metro stations. Estimated binary logit model of car ownership and nested logit model of commuting mode choice reveal that: (1) proximity to metro stations has a significant positive association with the choice of rail transit as primary commuting mode, but its association with car ownership is insignificant; (2) income, job status, and transportation subsidy are all positively associated with the probabilities of owning car and driving it to work; (3) higher population density in work location relates positively to the likelihood of commuting by the metro, but does not show a significant relationship with car ownership; (4) longer commuting distance is strongly associated with higher probabilities of riding the metro, rather than driving, to work; (5) considerations of money, time, comfort, and safety appear to exert measurable influences on car ownership and mode choice in the expected directions, and the intention to ride the metro for commuting is reflected in its actual use as primary mode for journey to work. These results strongly suggest that rail transit-supported urban expansion can produce important positive outcomes, and that this strategic approach can be effectively facilitated by transportation policies and land use plans, as well as complemented by timely provision of high quality rail transit service to suburban residents.     

A behavioral analysis of freight mode choice decisions

This paper develops a behavioral analysis of freight mode choice decisions that could provide a basis for an acceptable analytical tool for policy assessment. The paper specifically examines the way that truck and rail compete for commodity movement in the US. Two binary mode choice models are introduced in which some shipment-specific variables (e.g. distance, weight and value) and mode-specific variables (e.g. haul time and cost) are found to be determinants. The specifications of the non-selected choice are imputed in a machine learning module. Shipping cost is found to be a central factor for rail shipments, while road shipments are found to be more sensitive to haul time. Sensitivity of mode choice decisions is further analyzed under different fuel price fluctuation scenarios. A low level of mode choice sensitivity is found with respect to fuel price, such that even a 50% increase in fuel cost does not cause a significant modal shift between truck and rail.     

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.     

A Stated preference freight mode choice model

Transport policy aims to assist the transport system to work more efficiently and effectively. An understanding of the reasons why people choose to move freight in a certain manner is critical to the development of appropriate policies. This article outlines a data collection approach and the development of a disaggregate mode choice model applicable to the analysis of freight shipper decision making. It focuses on the choice between rail and road in Java, Indonesia. The model indicates that safety, reliability and responsiveness are major attributes influencing rail/road freight mode choice. Transport policies aimed at improving these dimensions should increase the attractiveness of rail transport.     

Access to railway stations and its potential in increasing rail use

The propensity to travel by rail, and not, for example by car, can be considered to be a factor of the rail service offered, the access to it and the characteristics of the population served. Efforts to increase rail use usually focus on the rail service itself while the accessibility of the rail network receives less attention. In this context, the paper has two broad aims. First, to evaluate how important the ‘access-to-the-station’ part of a rail journey is to passengers in their overall satisfaction with the rail journey and second, to investigate the balance between characteristics of the service, the access to it and the population served in determining rail use in different parts of the rail network. The analysis is carried out for the Netherlands. To achieve the first aim, we use the Dutch Railways customer satisfaction survey and apply principal component analysis and derived importance techniques to assess the relative importance of accessibility in determining the overall satisfaction with the rail journey. For the second aim, we use regression analysis to explain, at the Dutch postcode level, the propensity to use rail. We find that satisfaction with the level and quality of the access to the station is an important dimension of the rail journey which influences the overall satisfaction from that journey and that the quality and level of accessibility is an important element in explaining rail use. The conclusion reached is that in many parts of the rail network improving and expanding access services to the railway station can substitute for improving and expanding the services provided on the rail network and that it is probably more cost efficient when the aim is to increase rail use. These parts of the network are mainly in the periphery where the current level of rail service is relatively low.     

Intercity rail services: A nested logit stated choice analysis of pricing options

There is a renewed interest in intercity and long-distance rail services in many countries, with both new high-speed rail services and improvements to conventional rail under review. The current study reports on an investigation using a stated choice experiment, of the demand for sleeper services between Sydney, Northern New South Wales (NSW) and Brisbane in Australia, a 12 to 14 hour trip, just after a decision by the NSW government to temporarily suspend sleeper services and introduce seating service only, pending an inquiry into the demand for such loss-making services under alternative price and service levels. A matrix of direct fare elasticities within the rail mode and between rail and competing modes are obtained for concession and non-concession travellers from a nested logit model. The empirical evidence extends our knowledge of the sensitivity of the long distance passenger market to a range of rails fares, distinguishing between classes of fares and levels of service.     

Identifying preferences for public transport investments under a constrained budget

As urban areas face increasing demands for new transport infrastructure to promote a sustainable future with an increasing reality of constrained government budgets, the debate on whether we should focus on rail or bus-based investments continues unabated in many jurisdictions. Associated with the debate is an emotional (or ideological) bias by communities in favour of one mode, especially rail, which carries much sway at the political level as if there is no budget constraint. This paper presents a stated choice experiment to investigate this context as two unlabelled options described by 20 potential drivers of community preferences for improved public transport, where each choice scenario is conditioned on an estimated construction cost and a total annual transport infrastructure budget for the relevant geographical jurisdiction. This is followed by a labelling of each alternative to reveal whether the option is bus rapid transit (BRT) or light rail (LRT) and to establish whether this additional information influences preference revision. Data is collected in all eight capital cities of Australia in mid 2014. Mixed logit models with heteroscedastic conditioning in terms of the cost of the project infrastructure and whether the alternative is labelled BRT or LRT, provide new evidence on the nature and extent of community modal bias in a budget-constrained choice setting. The conclusions are twofold. On the one hand, if a fully compensatory choice rule is assumed (as is common in all previous modal comparison studies), LRT is predominantly preferred over BRT despite budgetary constraints, similarities in quality of service attributes and the opportunity to choose a greater network coverage for a given construction cost. However, when we allow for attribute non-attendance (a semi-compensatory choice rule), the modal bias is no longer a significant driver of preferences.     

北京市轨道交通房山线功能定位分析研究

轨道交通线路功能定位对确定线路的技术标准、运营模式、系统制式等具有决定作用.房山线作为北京近期建设的轨道交通,其功能定位存在较多不确定因素,是北京线网规划阶段一个尚未完全解决的问题,也是项目可行性研究的难点之一。通过研究各层面关键因素对房山线功能的影响,对其定位进行分析,从而为该线的设计提供参考.     

Rail network accessibility and the demand for inter-urban rail travel

This paper reviews methods that have and can be used to forecast the effect of changes in accessibility to the rail network on the demand for inter-urban rail travel and of available evidence on rail accessibility elasticities. It reveals that relatively little research has been conducted in this area and that the forecasting procedures that could be used imply large variation in accessibility elasticities, which has not been empirically justified. Fresh empirical evidence on two related matters is reported. First, the neglected area of choice set composition is examined and the extent to which rail is considered to be a realistic alternative for inter-urban journeys and the contribution that accessibility to the rail network makes to this are analysed. Second, rail trip rate models are presented that not only contain estimates of accessibility elasticities and of the effects of a range of socio-economic variables on the demand for rail travel, but also that allow tests of the accessibility elasticity variation implied by many forecasting procedures to be conducted. It is found that this elasticity variation is not empirically supported. It is concluded that there is only limited scope for increasing rail demand through improvements in rail network accessibility.     

Development of commuter and non-commuter mode choice models for the assessment of new public transport infrastructure projects: A case study

This paper uses state of the art stated choice designs to parameterise modal choice models for commuting and non-commuting travel futures in the presence of new public transport infrastructure (variations of new heavy rail, light rail and dedicated busway systems). D-optimal choice experiments are developed for a set of labelled modal alternatives in which respondents establish a reference benchmark based on the existing service levels (for access, linehaul and egress trip legs) which is used in a computer aided personal interview instrument to generate future scenarios of service levels for current and prospective new modals options. We show that a fully integrated stated choice experiment provides all the information required to obtain behaviourally relevant parameter estimates (within a nested logit framework) for all but the mode-specific constants (MSCs). The MSCs can be calibrated for the current modes within a network model setting, giving the transport planner an appropriate model for predicting the patronage potential for proposed new public transport infrastructure services. A useful by-product is a new set of behavioural values of travel time savings for access, egress, linehaul and wait times.     

Testing the decentralization effects of rail systems: Empirical findings from Israel

Many sustainable urban development approaches are based on mass public transportation ventures, especially railway development, which has been considered a panacea for the unfavorable effects of suburban development. But rail transit also improves accessibility to the fringes, thus encouraging an exodus to the suburbs. This paper explores suburbanization and sprawling effect of commuter rail transit on the rural exurbia of the Tel Aviv metropolis by analyzing its effect on residential location decisions. The findings indicate that the suburban rail system was a determinant factor in the location choice of households which migrated from the inner parts of the Tel Aviv metropolis, since it allowed them to maintain strong commuting connections to their residential origin. This suggests that rail transit, along with its potential to strengthen the inner cities, also accelerates suburbanization and counter urbanization.     

Cost and time damping: evidence from aggregate rail direct demand models

There is a significant body of evidence from both disaggregate choice modelling literature and practical travel demand forecasting that the responsiveness to cost and possibly to time diminishes with journey length. This has, in Britain at least, been termed ‘Cost Damping’, and is recognised in guidance issued by the UK Department for Transport. However, the consistency of the effect across modes and data types has not been established. Cost damping, if it exists, affects both the forecasting of demand and our understanding of behaviour. This paper aims to investigate the evidence for cost and time damping in rail demand using aggregate rail ticket sales data. The rail ticket sales data in Britain has, for many years, formed the basis of analysis of a wide range of impacts of rail demand. It records the number of tickets sold between station pairs, and it is generally felt to provide a reasonably accurate reflection of travel demand. However, the consistency of these direct demand models with choice modelling and highway demand model structures has not been investigated. Rail direct demand models estimated by ticket sales data indicate only slight variation in the fare elasticity with distance, as is evidenced in the largest meta-analysis of price elasticities conducted to date (Wardman in J Transp Econ Policy 48(3):367–384, 2014). This study of UK elasticities shows strong variation between urban and inter-urban trips, presumably a segmentation at least in part by purpose, but less remaining variation by trip length. A lack of variation by length supports the hypothesis of cost damping, because constant cost sensitivity would imply that fare elasticity would increase strongly with distance, because of the increasing impact of higher fares at longer distances. In this paper we indicate that rail direct demand models have some consistency of behavioural paradigm with utility based choice models used in highway planning. We go on to use rail demand data to estimate time and fare elasticities in the context of various cost damping functions. Our empirical contribution is to estimate time elasticities on a basis directly comparable with cost elasticities and to show that the phenomenon of cost damping is strongly present in ticket sales data. This finding implies that cost damping should be included in models intended for multimodal analysis, which may otherwise give incorrect predictions.     

Comparative analysis of transit assignment: evidence from urban railway system in the Tokyo Metropolitan Area

This paper empirically compares the performance of six traffic assignment methods using the same empirical dataset of route choice. Multinomial logit (MNL), structured multinomial probit (SMNP), user equilibrium (UE), logit-based stochastic user equilibrium (SUE), probit-based SUE, and all-or-nothing (AON) assignment methods are applied to the comparative analysis. The investigated methods include those with three types of error components in their cost functions and two types of flow dependencies. Four methods of generating the route choice set are also compared for use as stochastic traffic assignment methods. The revealed preference data of urban rail route choice in the Tokyo Metropolitan Area are used for the case analysis. The empirical case analysis shows that probit-based SUE provides the best accuracy but requires the longest computation time. It also shows that the heuristics used to generate the choice set influence the method’s accuracy, while the incorporation of route commonality and in-vehicle congestion significantly improves its accuracy. Finally, the implications for practical rail planning are discussed on the basis of the analysis results.     

Long-term planning for ring-radial urban rail transit networks

Extensive work exists on regular rail network planning. However, few studies exist on the planning and design of ring-radial rail transit systems. With more ring transit lines being planned and built in Asia, Europe and the America's, a detailed study on ring transit lines is timely. An analytical model to find the optimal number of radial lines in a city for any demand distribution is first introduced. Secondly, passenger route choice for different rail networks is analyzed, for a many-to-many Origin-Destination (OD) demand distribution, based on a total travel time cost per passenger basis. The routes considered are: (1) radial lines only; (2) ring line only or radial lines and ring line combined; or (3) direct access to a destination without using the rail system. Mathematica and Matlab are used to code the route choice model. A cost-benefit optimization model to identify the feasibility and optimality of a ring line is proposed. Unlike simulations and agent-based models, this model is shown to be easily transferable to many ring-radial transit networks. The City of Calgary is used as an example to illustrate the applicability of each model. The existing urban rail network and trip distribution are major influencing factors in judging the feasibility and optimal location of the ring line. This study shows the potential net benefit of introducing a ring line by assessing changes in passengers’ costs. The changes in passenger cost parameters, such as ride cost and access cost, are shown to greatly influence the feasibility of a ring line.     

A multiple criteria approach for the evaluation of the rail transit networks in Istanbul

The deficiencies in the Istanbul transportation system have led the local authorities to plan several alternative transportation projects. In this paper three alternative rail transit network proposals are evaluated by using Analytic Hierarchy Process (AHP), a multiple criteria decision support system. The AHP facilitates decision-making by organizing perceptions, experiences, knowledge and judgments, the forces that influence the decision, into a hierarchical framework with a goal, scenarios, criteria and alternatives of choice. Based on this analysis, the decision makers have developed a new alternative as a combination of the most closely competing two alternative rail transit networks. This combination rail transit network is currently under construction.     

Forecasting high-speed rail ridership using a simultaneous modeling approach

Abstract

The newly launched, June 2009, US High-Speed Intercity Passenger Rail Program has rekindled a renewed interest in forecasting high-speed rail (HSR) ridership. The first step to the concerted effort by the federal, state, rail, and other related agencies to develop a nationwide HSR network is the development of credible approaches to forecast the ridership. This article presents a nested logit/simultaneous choice model to improve the demand forecast in the context of intercity travel. In addition to incorporating the interrelationship between trip generation and mode choice decisions, the simultaneous model also provides a platform for the same utility function flowing between both the decision-making processes. Using American Travel Survey data, supplemented by various mode parameters, the proposed model improves the forecast accuracy and confirms the significant impact of travel costs on both mode choice and trip generation. Furthermore, the cross elasticity of mode choice and trip generation related to travel costs and other modal characteristics may shed some light on transportation policies in the area of intercity travel, especially in anticipation of HSR development.     

Incorporating Knightian uncertainty into real options analysis: Using multiple-priors in the case of rail transit investment

This paper revisits the real option investment problem from a ‘Knightian’ perspective of uncertainty. We examine the decision to invest in rail transit infrastructure (i.e., transport improvement) by treating population scale and the attitudes of decision-makers or social planners as sources of risk and ambiguity. An α-maxmin multiple-priors expected utility framework is developed to solve for the option value of rail transit investment under Knightian uncertainty. We find that the threshold for investment varies with the ambiguity attitudes (i.e., pessimism or optimism) of decision-makers regarding future population dynamics, and show that option value can in fact either increase or decrease with uncertainty subject to κ-ignorance and ambiguity. We also underline the effect of transport improvement on traffic congestion under various states of nature, and determine the specific population scale ranges for which investment is warranted under (1) risk and (2) Knightian uncertainty. These dynamics are illustrated in a numerical application adapted from a Chinese rail transit initiative specific to the Xiamen region.     

Estimating traffic demand risk – A multiscale analysis

This paper proposes a novel method for estimating the traffic demand risk associated with transportation. Using mathematical properties of wavelets, we develop a statistical measure of traffic demand sensitivity with respect to GDP. This measure can be adapted in a flexible way to capture risk levels relevant for different investment horizons. We demonstrate the timescale decomposition of risk with Swedish traffic demand data for 1950–2005. In general, rail transport shows a stronger co-movement with GDP than road transport. Moreover, we examine the volatility exhibited by traffic demand. Our findings suggest that rail investments are more risky than road investments. Since the findings can be used for optimal investment timing and for choice between public investment alternatives, they are deemed important for public policy in general.     

Using ordered attitudinal indicators in a latent variable choice model: a study of the impact of security on rail travel behaviour

There is growing interest in the use of models that recognise the role of individuals’ attitudes and perceptions in choice behaviour. Rather than relying on simple linear approaches or a potentially bias-inducing deterministic approach based on incorporating stated attitudinal indicators directly in the choice model, researchers have recently recognised the latent nature of attitudes. The uptake of such latent attitude models in applied work has however been slow, while a number of overly simplistic assumptions are also commonly made. In this article, we present an application of jointly estimated attitudinal and choice models to a real-world transport study, looking at the role of latent attitudes in a rail travel context. Our results show the impact that concern with privacy, liberty and security, and distrust of business, technology and authority have on the desire for rail travel in the face of increased security measures, as well as for universal security checks. Alongside demonstrating the applicability of the model in applied work, we also address a number of theoretical issues. We first show the equivalence of two different normalisations discussed in the literature. Unlike many other latent attitude studies, we explicitly recognise the repeated choice nature of the data. Finally, the main methodological contribution comes in replacing the typically used continuous model for attitudinal response by an ordered logit structure which more correctly accounts for the ordinal nature of the indicators.