Factors affecting the use of bus and rail services in a deregulated environment

In 1987, the NSW Government commenced deregulation of the long-distance bus industry in NSW. This immediately led to greater inter-modal competition and contestability within the context of changing passenger markets.This study utilises categorical data analysis methods to examine the emerging passenger markets of inter-modal competitors (bus and rail) and to assess the relative importance of socioeconomic and travel related variables which affect the use of bus and rail services along the high volume Sydney-Canberra and Sydney-North Coast corridors.Conclusions from the study indicate varied passenger markets within a relatively new contestable environment which are mode and corridor specific. Results are indicative of the need for competitors to develop marketing strategies conducive to the demands of the travelling public in order to enhance viability and commercial opportunities.     

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.     

Integrated modeling of high performance passenger and freight train planning on shared-use corridors in the US

This paper studies strategic level train planning for high performance passenger and freight train operations on shared-use corridors in the US. We develop a hypergraph-based, two-level approach to sequentially minimize passenger and freight costs while scheduling train services. Passenger schedule delay and freight lost demand are explicitly modeled. We explore different solution strategies and conclude that a problem-tailored linearized reformulation yields superior computational performance. Using realistic parameter values, our numerical experiments show that passenger cost due to schedule delay is comparable to in-vehicle travel time cost and rail fare. In most cases, marginal freight cost increase from scheduling more passenger trains is higher than marginal reduction in passenger schedule delay cost. The heterogeneity of train speed reduces the number of freight trains that can run on a corridor. Greater tolerance for delays could reduce lost demand and overall cost on the freight side. The approach developed in the paper could be applied to other scenarios with different parameter values.     

Long-term impact of the Shinkansen on rail and air demand: analysis with data from Northeast Japan

This paper analyses how the high-speed rail construction in Northeast Japan (Tohoku) has affected total demand and interregional travel patterns. We use annual interregional passenger data from 1989 to 2012 and apply regression analysis with the demand between Tokyo and the Tohoku prefectures as the dependent variable. We distinguish particularly between the ‘Full-’ and the ‘Mini-’ Shinkansen, where the latter are branch services running with reduced speed. We find that the ‘Full-Shinkansen’ quickly increases rail and total public transport trips and generates additional rail demand year on year. The ‘Mini-Shinkansen’ impacts are less pronounced. Furthermore, our analysis shows that the Shinkansen has shifted some demand from air to rail once it started operation and increased rail share gradually. We therefore suggest that predictions of demand impacts should carefully distinguish immediate from gradual impacts. We also discuss differences in regional demand in that not all prefectures have gained equally from Shinkansen construction.     

High-Speed Rail Operations on an Existing Network: An Assessment Model for China

High-speed rail operations have the potential to reduce the long-term decline in rail passenger travel demand for the medium to long distance inter-urban markets. Such decline has been evident through most of the industrialized countries where air and road transport tend to be the dominant modes. In China, the operations of long distance high-speed rail on fully dedicated track is not very easy to implement, due to the high proportion of passengers who travel between high-speed and conventional railways. An alternative approach would be to allow for mixed operations with trains of various speeds on the same track. This article puts forward a simulation model designed to allow an evaluation of the most efficient distance for high-speed rail operations under mixed train speed scenarios. The model takes into account the main operating parameters such as passenger volumes, train speeds, capital and maintenance costs, train operating costs and energy consumption. The distance of high-speed train running on conventional rail that will yield the most economic benefit can be estimated using the model. The article includes the results of using the model for a specific example. It is concluded that large-scale high-speed trains have the potential to be successfully operated on conventional rail networks.     

Assessing the energy and greenhouse gas emissions mitigation effectiveness of potential US modal freight policies

This paper estimates the total embodied energy and emissions modal freight requirements across the supply chain for each of over 400 sectors using Bureau of Transportation Statistics Commodity Flow Survey data and Bureau of Economic Analysis economic input-output tables for 2002. Across all sectors, direct domestic truck and rail transportation are similar in magnitude for embodied freight transportation of goods and services in terms of ton-km. However, the sectors differ significantly in energy consumption, greenhouse gas emissions, and costs per ton-km. Recent pressure to reduce energy consumption and emissions has motivated a search for more efficient freight mode choices. One solution would be to shift freight transportation away from modes that require more energy and emit more (e.g., truck) to modes that consume and emit less (e.g., rail and water).Our results show there are no individual sectors for which targeting changes would significantly decrease the total freight transportation energy and emissions, therefore we have also looked at the prospect of policies encouraging many sectors to shift modes. There are four scenarios analyzed: (1) shifting all truck to rail, shifting top 20% sector mode choice, (2) based on their emissions, (3) based on a multi-attribute analysis, and (4) increasing truck efficiency (e.g., mpg). Increasing truck efficiency by 10% results in similar energy and emissions reductions (approximately 7% for energy and 6% for emissions) as targeting the top 20% of sectors when selected based on emissions, whereas selecting the top 20% based on availability to shift from truck results in slightly less reductions of energy and emissions. Implementing policies to encourage higher efficiency in freight trucks may be a sufficient short term goal while efforts to reduce truck freight transportation through sectoral policies are implemented in the long term.     

New routes on old railways: increasing rail’s mode share within the constraints of the existing railway network

This paper describes an integrated methodology for identifying potential ‘quick wins’ for mode shift from road to passenger rail transport. Firstly, a procedure for analysing rail’s relative competitiveness in the market for passenger transport between large urban areas is developed and then applied to a UK case study. The purpose of such analysis is to allow the identification of flows where rail is currently relatively uncompetitive (in terms of journey time in particular) and to assess the reasons for this poor performance, so that the issues which suppress rail use may be addressed. In parallel, a framework, methodology and tool for the assessment of existing and potential capacity (trains, seats, TEUs, etc.) is developed for both passenger and freight traffic, to identify and address network constraints. An illustrative example of the use of these demand and capacity assessment tools is then presented, with the tools used to identify and evaluate flows where rail demand is suppressed by poor service quality and where spare capacity exists which would allow the passenger rail service to be improved without requiring significant investments in infrastructure. The effects of such improvements on demand are predicted, and the cost implications of operating such additional services are discussed. The analysis suggests that there may be significant potential for increasing rail’s mode share by providing additional inter-urban services where rail currently offers an inferior service.     

Entropy-based estimation of transfers in a terminal

An intermodal transportation terminal is a facility that provides commuters with easy transfer between transit modes and providers such as buses, light rail, subway, taxis, airport shuttles, and commuter rail. The probability of a passenger transferring from one mode to another and the estimation of total transfer demand are of great importance to both practitioners and researchers when determining optimal design alternatives as well as the best control and management policies for daily operation of the terminal. This article presents a study that uses an entropy-based optimization approach to estimate the transfer demands between the available transportation modes in an intermodal transportation terminal. The development and calibration of the entropy model is presented in the first part of the article, which is followed by a case study of the SiHui Intermodal Terminal in Beijing, China.     

Own and cross-price elasticities of demand for domestic flights and intercity trains in the U.S.

In 2009, the U.S. Federal Government announced its plan to invest in the expansion of the passenger rail system, instead of adding to the freeway or aviation systems. On the other hand, environmental studies show that passenger rails have a lower polluting impact than flights or cars. In order to evaluate whether consumers would switch from flights to trains and use the new rail system, this paper estimates the own and cross-price elasticities of demand for domestic flights and passenger trains using the methodology described in Berry (1994). Specifically, the changes in demand for domestic flights and trains with respect to their prices are evaluated. The static model in this study suggests that the substitutability between these two modes of transport is minimal, in other words, travelers will to change their choices is very small given the configuration of the transportation system when the notice was made. In particular, train trips are substituted more easily.     

Rail travel and the Leisure market in great Britain

The purpose of this paper is to examine the factors influencing and inducing leisure travel; to convey the sensitivity of rail travel receipts to the performance of the economy and more particularly family and personal disposable incomes; to examine the potential for further market research; and finally, to determine ways and means of attracting marginal revenue in the sustainable recreation/tourism sphere to a major public sector asset.

The paper focuses on leisure marketing by Britain's national railway corporation, British Rail (BR), and the relevant activities of its three passenger business sectors: Network SouthEast (NSE), which operates regional and local services in London and the South East (though not the London ‘tube’ system); Regional Railways, which operates regional and local services elsewhere in Great Britain; and InterCity, which operates the long distance express services.

The paper reviews BR's fares promotions of recent years and in particular draws on some examples taken from Regional Railways. This sector is now the only business of British Rail which in principle is subject to a significant public grant, to meet the obligation of a minimum level of service on social grounds. Of the other two passenger businesses, Network SouthEast receives a grant but the current intention is that it should operate on a breakeven basis from the 1992/93 financial year; InterCity runs on a purely commercial basis.     

A structural model of temporal change in multi-modal travel demand

A simultaneous equation model is developed to describe temporal trends and shifts in demand among five modes of passenger transportation in the Netherlands. The modes are car driver, car passenger, train, bicycle, and public transit (bus, tram, and subway). The time period is one year (1984–1985). The data are from the week-long travel diaries at six-month intervals of a national panel of households in the Netherlands. The model explains the weekly trip rates for each mode in terms of three types of relationships: links from demand for the same mode at previous points in time (temporal stability or inertia); links to and from demand for other modes at the same point in time (complementarity and competition on a synchronous basis); and links from demand for other modes at previous points in time (substitution effects). a significant model is found with 15 inertial links, 21 synchronous links, and 16 cross-lag links among the variables. It is proposed in interpretations of the link coefficients and overall effects of one variable on another that relationships among the modes are evolving over time. In particular, the model captures the effect of a public transit fare increase that occurred during the time frame of the panel data.     

Crowding in public transport systems: Effects on users,operation and implications for the estimation of demand

The effects of high passenger density at bus stops, at rail stations, inside buses and trains are diverse. This paper examines the multiple dimensions of passenger crowding related to public transport demand, supply and operations, including effects on operating speed, waiting time, travel time reliability, passengers’ wellbeing, valuation of waiting and in-vehicle time savings, route and bus choice, and optimal levels of frequency, vehicle size and fare. Secondly, crowding externalities are estimated for rail and bus services in Sydney, in order to show the impact of crowding on the estimated value of in-vehicle time savings and demand prediction. Using Multinomial Logit (MNL) and Error Components (EC) models, we show that alternative assumptions concerning the threshold load factor that triggers a crowding externality effect do have an influence on the value of travel time (VTTS) for low occupancy levels (all passengers sitting); however, for high occupancy levels, alternative crowding models estimate similar VTTS. Importantly, if demand for a public transport service is estimated without explicit consideration of crowding as a source of disutility for passengers, demand will be overestimated if the service is designed to have a number of standees beyond a threshold, as analytically shown using a MNL choice model. More research is needed to explore if these findings hold with more complex choice models and in other contexts.     

A GIS-based planning approach to locating urban rail terminals

This paper develops a flexible GIS-based methodology for evaluating the potential locations of terminal park-and-ride facilities along urban rail lines. The methodology differs from political-based approaches and traditional travel demand modeling in its use of an objective measure of accessibility to gage the suitability of a site. The methodology begins by constructing an index of derived demand for rail usage based on the local demographics. Principal component analysis (PCA) is used as a means of constructing an index of derived demand consistent with other passenger surveys. Next, trade areas or commutersheds are calculated for each candidate park-and-ride location based on realistic measures of accessibility and network based drive times, taking into account competition among candidates for riders. Following the analysis, the candidate locations and their commutersheds are delineated and visualized in the GIS environment. In summary, application of this method produces a site-specific suitability index that may be used to rank and compare potential park-and-ride locations. We illustrate how our approach fits within the context of the larger-scale corridor study as a complimentary means of refining the location of urban rail stations. The analysis uses the proposed rail system for Columbus Ohio as a case study. This revised version was published online in June 2006 with corrections to the Cover Date.     

基于高速铁路常旅客计划的全流程智慧行李服务方案构建

随着"铁路畅行"和"客运提质计划"的提出,提供高质量、个性化的旅客服务成为高速铁路客运发展的关键方向。为打造全新旅客行李服务概念,基于"铁路畅行"会员常旅客计划,构建全流程、门到门智慧行李服务方案,从旅客需求角度出发,采取"人货分离"模式,突破传统站内行李服务的模式,拓宽业务场景,延长商业链,形成一套系统完整的方案。全流程智慧行李服务作为一项新的服务模式,为培育旅客需求,提高顾客粘合度,挖掘高铁行李服务的潜在市场,优化铁路盈利结构,加快构建铁路客运服务体系,提升铁路在运输市场的竞争力提供支持。     

Forecasting demand for high speed rail

It is sometimes argued that standard state-of-practice logit-based models cannot forecast the demand for substantially reduced travel times, for instance due to High Speed Rail (HSR). The present paper investigates this issue by reviewing the literature on travel time elasticities for long distance rail travel and comparing these with elasticities observed when new HSR lines have opened. This paper also validates the Swedish long distance model, Sampers, and its forecast demand for a proposed new HSR, using aggregate data revealing how the air–rail modal split varies with the difference in generalized travel time between rail and air. The Sampers long distance model is also compared to a newly developed model applying Box–Cox transformations. The paper contributes to the empirical literature on long distance travel, long distance elasticities and HSR passenger demand forecasts. Results indicate that the Sampers model is indeed able to predict the demand for HSR reasonably well. The new non-linear model has even better model fit and also slightly higher elasticities.     

Structural equation modeling for national travel demand: an examination of the relationships between communication modes

This paper examines the relationships among different transportation modes, and between transportation and telecommunications, by applying the structural equation modeling (SEM) technique. For this purpose, we collected and compiled time series data on national travel demand, and socioeconomic and telecommunications conditions in Taiwan, and built national travel demand models using SEM. The estimation results show that the relationship between telecommunications and transportation demand (either car ownership or public transportation) is more complementary than substitutional. Moreover, car ownership is a type of inelastic necessity good, and its relationship with public transportation is more substitutional than complementary. Finally, among the three public transportation modes – rail, bus and domestic air – it is found that air is weakest in terms of competitive power. From the viewpoint of long-term forecasting trends, the bus holds its competitive power in comparison with other public transportation modes and would not be replaced in the future.     

Carsharing’s life-cycle impacts on energy use and greenhouse gas emissions

This paper examines the life-cycle inventory impacts on energy use and greenhouse gas (GHG) emissions as a result of candidate travelers adopting carsharing in US settings. Here, households residing in relatively dense urban neighborhoods with good access to transit and traveling relatively few miles in private vehicles (roughly 10% of the U.S. population) are considered candidates for carsharing. This analysis recognizes cradle-to-grave impacts of carsharing on vehicle ownership levels, travel distances, fleet fuel economy (partly due to faster turnover), parking demand (and associated infrastructure), and alternative modes. Results suggest that current carsharing members reduce their average individual transportation energy use and GHG emissions by approximately 51% upon joining a carsharing organization. Collectively, these individual-level effects translate to roughly 5% savings in all household transport-related energy use and GHG emissions in the U.S. These energy and emissions savings can be primarily attributed to mode shifts and avoided travel, followed by savings in parking infrastructure demands and fuel consumption. When indirect rebound effects are accounted for (assuming travel-cost savings is then spent on other goods and services), net savings are expected to be 3% across all U.S. households.     

A direct demand model for downtown work trips

This article documents the development of a direct travel demand model for bus and rail modes. In the model, the number of interzonal work trips is dependent on travel times and travel costs on each available mode, size and socioeconomic characteristics of the labor force, and the number of jobs. In estimating the models’ coefficients constraints are imposed to insure that the travel demand elasticities behave according to the economic theory of consumer behavior. The direct access time elasticities for both transit modes are estimated to be approximately minus two, and the direct linehaul time elasticities approximately minus one. The cross-elasticities with respect to the travel time components are estimated to be less than the corresponding direct elasticities. In general, the time cross-elasticities are such that rail trip characteristics but not car trip characteristics affect bus travel, and car trip characteristics but not bus trip characteristics affect rail travel. The cost elasticities lie between zero and one-half. Thus, the success of mass transit serving a strong downtown appears to depend on good access arrangements. This success can be confirmed with competitive linehaul speeds. The cost of travel appears to assume a minor role in choice of mode and tripmaking decisions. In the paper, a comparison is also made between the predictive performance of the models developed and that of a traditional transit model. The results indicate that the econometric models developed attain both lower percent error and lower variation of the error than the traditional model.     

A hierarchical line planning approach for a large-scale high speed rail network: The China case

Planning a set of train lines in a large-scale high speed rail (HSR) network is typically influenced by issues of longer travel distance, high transport demand, track capacity constraints, and a non-periodic timetable. In this paper, we describe an integrated hierarchical approach to determine line plans by defining the stations and trains according to two classes. Based on a bi-level programming model, heuristics are developed for two consecutive stages corresponding to each classification. The approach determines day-period based train line frequencies as well as a combination of various stopping patterns for a mix of fast trunk line services between major stations and a variety of slower body lines that offer service to intermediate stations, so as to satisfy the predicted passenger transport demand. Efficiencies of the line plans described herein concern passenger travel times, train capacity occupancy, and the number of transfers. Moreover, our heuristics allow for combining many additional conflicting demand–supply factors to design a line plan with predominantly cost-oriented and/or customer-oriented objectives. A range of scenarios are developed to generate three line plans for a real-world example of the HSR network in China using a decision support system. The performance of potential train schedules is evaluated to further examine the feasibility of the obtained line plans through graphical timetables.