Multicriteria high-speed rail route selection: application to Malaysia's high-speed rail corridor prioritization

This paper reviews the literature on multicriteria decision analysis in transportation and provides a case study of high-speed rail (HSR) corridor/route selection using multicriteria methods in the context of HSR corridor prioritization in Malaysia. Using the screening method proposed by Hagler and Todorovich and the ELECTRE I multicriteria method, it is found that the southbound corridor from Kuala Lumpur to Singapore has the highest priority, followed by the eastbound corridor to Kuantan, and northbound to Georgetown. HSR trains could potentially reduce the trip times to Singapore, Kuantan, and Georgetown from Kuala Lumpur, as compared to driving, by 65–73%. The results of this study can be used to assist in the planning of HSR and/or integrated transportation systems in Malaysia. The same methods can be used to evaluate potential HSR corridors/routes in other countries or regions.     

Modelling passenger demand for parkway rail stations

Interest in Parkway stations emerged in the 1980s. These act as convenient out-of-town stations for inter-urban rail journeys. There were 13 so-called Parkway stations in Great Britain in 1999 and two have subsequently been opened. This paper reports the development and application of a new Parkway forecasting model which was conducted for the Association of Train Operating Companies (ATOC), undertaken as part of an extensive update to the Passenger Demand Forecasting Handbook, which recommends demand forecasting frameworks and associated parameters that are widely used in the railway industry in Great Britain. The objective was to develop a model that had more desirable properties and was more straightforward to apply than the previously recommended procedure. The focus is entirely upon inter-urban journeys of over 80 km.The model forecasts the demand for Parkway stations based solely on rail ticket sales data and its properties are illustrated with two case study applications. The nature of Parkway stations forces consideration of competition, and it is demonstrated that the inclusion of a station choice component leads to a somewhat improved explanatory power and a more plausible generalised cost elasticity.In addition to the methodological developments, the model has provided generally reasonable elasticities and forecasts and shown that Parkway users have different preferences to rail travellers in general. In a test based around a newly opened Parkway station, its forecasts are more accurate than the procedure it replaces.     

Demand for rail travel to and from airports

Rail access to airports is becoming increasingly important for both train operators and the airports themselves. This paper reports analysis of inter-urban rail demand to and from Manchester and Stansted Airports and the sensitivity of this market segment to growth in air traffic and the cost and service quality of rail services. The estimated demand parameters vary in an expected manner between outward and inward air travellers as well as between airport users and general rail travellers. These parameters can be entered into the demand forecasting framework widely used in the rail industry in Great Britain to provide an appropriate means of forecasting for this otherwise neglected market segment. The novel features of this research, at least in the British context, are that it provides the first detailed analysis of aggregate rail flows to and from airports, it has disaggregated the traditional generalised time measure of rail service quality in order to estimate separate elasticities to journey time, service headway and interchange, and it has successfully explored departures from the conventional constant elasticity position.     

The impact of high-speed rail investment on economic and environmental change in China: A dynamic CGE analysis

This study investigates the impact of high-speed rail investment on the economy and environment in China using a computable general equilibrium (CGE) model. The analysis is implemented in a dynamic recursive framework capturing long-run capital accumulation and labor market equilibrium. A national level impact was simulated through direct impact drivers including land use conversion, output expansion, cost reduction, productivity increase, transport demand substitution and induced demand. The results suggest that rail investment in China over the past decade has been a positive stimulus to the economy, while the effect on CO₂ emissions generation has been large. Overall, the economic impacts of rail investment are achieved primarily through induced demand and output expansion, whereas the contribution from a reduction of rail transportation costs and rail productivity increases were modest. In addition, negligible negative impacts were found from land use for rail development and the substitution effect among other modes. Emissions reduction from substitution of rail for other modes was small and offset by output expansion due to lowered rail transport costs and induced demand.     

Probabilistic risk analysis of flying ballast hazard on high-speed rail lines

Flying ballast is a significant safety concern for high-speed train operations on ballasted tracks. It is the phenomenon of a ballast particle displaced from the track, due to the aerodynamic force induced by a passing train traveling above a certain speed. Flying ballast can potentially damage tracks and rolling stock, thereby posing a risk to high-speed rail operations. This paper develops a Probabilistic Risk Analysis (PRA) model based on the information available from the field and the literature. The model enables a quantitative assessment of the probability of ballast particle displacement at a particular position on the track, as well as the probabilistic distribution of the total number of ballast particles that are expected to move. The model accounts for various risk factors, such as train speed, ballast gradation, and track position. The model application is illustrated using a ballasted track on the Yellow River Bridge on the Beijing-Shanghai high-speed rail line in China. The analysis finds that flying ballast probability increases when train speed increases, in particular, the problem of flying ballast becomes more pronounced when train speed exceeds 350 km per hour (217 miles per hour). Flying ballast probability might be reduced when the ballast profile is lower, given all else being equal. In addition, flying ballast probability is expected to be higher at the center of the track than in other positions. The proposed risk model can be further developed and ultimately be used to evaluate route-specific flying ballast risk, enabling the identification, assessment, and comparison of risk mitigation strategies in order to support emerging high-speed rail operations.     

Grand challenges for high-speed rail environmental assessment in the United States

The comprehensiveness of environmental assessments of future long-distance travel that include high-speed rail (HSR) are constrained by several methodological, institutional, and knowledge gaps that must and can be addressed. These gaps preclude a robust understanding of the changes in environmental, human health, resource, and climate change impacts that result from the implementation of HSR in the United States. The gaps are also inimical to an understanding of how HSR can be positioned for 21st century sustainability goals. Through a synthesis of environmental studies, the gaps are grouped into five overarching grand challenges. They include a spatial incompatibility between HSR and other long-distance modes that is often ignored, an environmental review process that obviates modal alternatives, siloed interest in particular environmental impacts, a dearth of data on future vehicle and energy sources, and a poor understanding of secondary impacts, particularly in land use. Recommendations are developed for institutional investment in multimodal research, knowledge and method building around several topics. Ultimately, the environmental assessment of HSR should be integrated in assessments that seek to understand the complementary and competitive configurations of transportation services, as well as future accessibility.     

Optimizing train stopping patterns and schedules for high-speed passenger rail corridors

High-speed railway (HSR) systems have been developing rapidly in China and various other countries throughout the past decade; as a result, the question of how to efficiently operate such large-scale systems is posing a new challenge to the railway industry. A high-quality train timetable should take full advantage of the system’s capacity to meet transportation demands. This paper presents a mathematical model for optimizing a train timetable for an HSR system. We propose an innovative methodology using a column-generation-based heuristic algorithm to simultaneously account for both passenger service demands and train scheduling. First, we transform a mathematical model into a simple linear programming problem using a Lagrangian relaxation method. Second, we search for the optimal solution by updating the restricted master problem (RMP) and the sub-problems in an iterative process using the column-generation-based algorithm. Finally, we consider the Beijing–Shanghai HSR line as a real-world application of the methodology; the results show that the optimization model and algorithm can improve the defined profit function by approximately 30% and increase the line capacity by approximately 27%. This methodology has the potential to improve the service level and capacity of HSR lines with no additional high-cost capital investment (e.g., the addition of new tracks, bridges and tunnels on the mainline and/or at stations).     

An integrated assessment of alternative land-based passenger transport policies: A case study in Tenerife

Over recent decades, there have been numerous cases of land-based transport policies that have lacked clear and coherent strategies. This has not only hampered the resolution of issues like road congestion, but has also created new ones (e.g. strong social opposition to new train infrastructures). The absence of such strategies highlights the need for long-term transport policies with a wider vision of the issues, since land-based transport cannot be considered from just a technical perspective.The main objective of this article is to implement a participatory integrated approach to facilitate the understanding of land-based passenger transport governance issues on Tenerife, in the Canary Islands. Relevant policy issues and alternatives are identified by the stakeholders involved. The inclusion of stakeholders in the assessment process is crucial to frame transport governance issues appropriately and to define and assess plausible policy alternatives. This assessment process even included a final step of validation of the results by stakeholders to foster discussion among them about transport issues and policy alternatives.Finally, due to the obstructive role played by some stakeholders in influencing past transport policies, an analysis of possible coalitions among stakeholders is also discussed.     

Cost-benefit analysis of alternative vehicles in the Philippines using immediate and distant future scenarios

Alternative vehicle technologies promise a sustainable future by reducing carbon emissions and pollution. However, their widespread adoption tends to be slow due to high costs and uncertainties in benefits. Using a life cycle-based approach, this study calculates ownership savings and societal benefits for various alternative vehicle technologies against their baseline vehicle technology (e.g. gasoline or diesel). The assessment is performed from a developing country context – in the Philippines. Furthermore, immediate and distant future scenarios are modeled. The immediate future scenario assesses costs and benefits if the shift is to happen now, while the distant future scenario considers the effect of widespread autonomous driving and ridesharing. The results of the study echo the significant societal benefits from electric- and fuel cell-powered vehicles found in literature, but they are hindered by high ownership costs. In the immediate future, the diesel hybrid electric vehicle can potentially have both positive societal and operational costs for public transportation. For a gasoline-powered private passenger car, a simple shift to diesel, 20% biodiesel or 85% methanol can be beneficial. In the distant future, it is expected that autonomous, rideshared vehicles can potentially lure people away from driving their own vehicles, because of lower costs per passenger-kilometer while sustaining the privacy and comfort of a private car.     

A data perception model for the safe operation of high-speed rail in rainstorms

In order to solve the safety operation problems of High-speed rail (HSR) in different areas and different sections under the rainstorm condition, an early warning process for the rainstorm disaster is designed. Furthermore, in order to control the operation risk, a HSR operation program with different rainstorm degrees is given out based on the analysis of rainstorm warning mechanism and rainstorm warning threshold in this paper. In addition, considering the reality that natural conditions vary greatly and the rainfall is very uneven, a data perception model of rainstorm (DPM) is proposed with correction coefficients for solving the calculation problem of precipitation for rainstorm warning. The DPM mainly adopts Paulhus’s empirical equation and uses the linear function to improve it for calculating the precipitation, which is able to calculate the hourly precipitation in different regional environments, and also effectively evaluate the rainstorm warning level of high-speed rail in this period. It can calculate and monitor the process by big data and MATLAB. The result of case analysis shows that the DPM has good practical value for solving the safety operation problem of HSR in different areas under rainstorm environment.     

Rail Infrastructure: Challenges for Cost–Benefit Analysis and Other ex ante Evaluations

Abstract

Cost–benefit analysis (CBA) plays a major role in the ex ante evaluation of rail projects in many western countries. At first sight carrying out a CBA for rail projects seems straightforward, since cost estimates are almost always available, and the most dominant benefits are generally known, being the travel time saved and the increase in consumer surplus due to induced demand. However, the practice is much more complex: the quality of current estimates for costs and benefits is often poor and several benefits-related aspects are ignored. This article gives an overview of the challenges in improving the quality of CBAs for rail projects.     

Use of ecological footprinting to explore alternative transport policy scenarios in an Irish city-region

The objective of this paper is to compare the ecological footprint for travel-commuting patterns for the residents of an Irish city-region, that is Limerick city-region, in 1996 and 2002. Scenario building, based on ecological footprint analysis, is used to estimate the impact of different policy choices for 2010. The optimal policy mix for sustainable travel is proposed and consists of a mix of reduced demand through travel demand measures, better spatial planning and technological improvements in fuel economy.     

An investigation into the feasibility of increasing rail use as an alternative to the car

With rail travel largely seen to be a more sustainable method than road-based transport, this paper examines the market segments amongst existing motorists that would be most likely to travel by train in the UK. The analysis is based on a large survey in London and the south-east of England, the area surrounding the routes operated by the train company First Capital Connect. Findings show that train travellers tend to be middle-aged and of a higher social grade, typically taking commuting or business trips. Individuals living within four miles of a station are considerably more likely to travel by rail than those further away. Given the competition from road-based transport, it is of particular interest that the measure highlighted to increase rail use for those living further away from the rail network is to enhance car parking at train stations.     

Modeling traveler mode choice behavior of a new high-speed rail corridor in China

This study examines mode choice behavior for intercity business and personal/recreational trips. It uses multinomial logit and nested logit methods to analyze revealed preference data provided by travelers along the Yong-Tai-Wen multimodal corridor in Zhejiang, China. Income levels are found to be positively correlated with mode share increases for high-speed rail (HSR), expressway-based bus, and auto modes, while travel time and trip costs are negatively correlated with modal shift. Longer distance trips trigger modal shifts to HSR services but prevent modal shift to expressway-based auto use due to escalation of fuel cost and toll charges. Travelers are less elastic in their travel time and cost for trips by nonexpressway-based auto use modes. The magnitude of elasticity for travel time is higher than trip costs for business trips and lower for personal/recreational trips. The study provides some policy suggestions for transportation planners and decision-makers.     

Real-time traveler information for urban arterials: a method for selecting metropolitan routes of significance

Although multi-criteria analysis (MCA) has been commonly used to guide transportation decisions related to traditional infrastructure, limited applications are reported for intelligent transportation systems. The objective of this study is to apply MCA for selecting arterial routes for real-time traveler information, to conform with recent US federal regulations. This study applies the method in two metropolitan areas and the paper describes which criteria were chosen and how important each were considered. In all, this study guided the selection of seven arterial routes for deployment of real-time traveler information collection and dissemination. This study demonstrates how a transportation agency can apply MCA for traveler information planning and the method provides value for other agencies seeking to come into compliance with traveler information regulations.     

Risk of increasing temperature due to climate change on high-speed rail network in Spain

With more than 3,200 km of track, the Spanish high-speed rail network is the longest network in Europe and the second largest in the world after China. Due to its geographical location in southern Europe, the entire network is exposed to periods of elevated temperatures that can cause disturbances and severe disruptions such as rail deformation, or in the worst case, lateral track buckling. In this study, the vulnerability of the current Spanish high-speed rail network is analysed in terms of track buckling failures with a Monte Carlo simulation. Downscaled temperature projections from a range of Global Climate Models (GCMs), under three Representative Concentration Pathways (RCP4.5, RCP6.0 and RCP8.5), were forced in a buckling model and particularized for different segments of the network. With that, the proposed methodology provides the number of rail buckles expected per year by assuming current maintenance standards and procedures. The result reveals significant increase in the occurrence of buckling events for future years, mainly in the central and southern areas of mainland Spain. However, relevant variations are found in different climates and time horizon scenarios in Spain. The anticipated buckling occurrences highlight the vulnerability of the Spanish rail network in the context of global warming scenarios. Overall, the proposed methodology is designed to be applicable in large-scale railway networks to identify potential buckling sites for the purpose of understanding and predicting their behaviour.     

Assessment of schedule-based and frequency-based assignment models for strategic and operational planning of high-speed rail services

Despite some substantial limitations in the simulation of low-frequency scheduled services, frequency-based (FB) assignment models are by far the most widely used in practice. They are less expensive to build and less demanding from the computational viewpoint with respect to schedule-based (SB) models, as they require neither explicit simulation of the timetable (on the supply side), nor segmentation of OD matrices by desired departure/arrival time (on the demand side).The objective of this paper is to assess to what extent the lack of modeling capabilities of FB models is acceptable, and, on the other hand, the cases in which such approximations are substantial and more detailed SB models are needed. This is a first attempt to shed light on the trade-off between (frequency-based) model inaccuracy and (scheduled-based) model development costs in the field of long-distance (e.g. High-speed Rail, HSR) service modeling.To this aim, we considered two modeling specifications estimated using mixed Revealed Preferences (RP) and Stated Preferences (SP) surveys and validated with respect to the same case study. Starting from an observed (baseline) scenario, we artificially altered the demand distributions (uniform vs. time-varying demand) and the supply configuration (i.e. train departure times), and analyzed the differences in modal split estimates and flows on individual trains, using the two different model specifications.It resulted that when the demand distribution is uniform within the period of analysis, such differences are significant only when departure times of trains are strongly unevenly spaced in time. In such cases, the difference in modal shares, using FB w.r.t. SB, is in the range of [0%, +5%] meaning that FB models tend to overestimate HSR modal shares. When the demand distribution is not uniform, the difference in modal shares, using FB w.r.t. SB, is in the range of [−10%, +10%] meaning that FB models can overestimate or underestimate HSR modal shares, depending on timetable settings with respect to travelers’ desired departure times. The differences in on-board train flow estimates are more substantial in both cases of uniform and not uniform demand distribution.     

The variation in the value of travel-time savings and the dilemma of high-speed rail in China

This paper examines the variation in the value of travel-time savings (VTTS), a fundamental element determining the market demand for high-speed rail. Following a review of time allocation theories, a time allocation model for general travel behavior is proposed as a further elaboration of Evans’ (1972) activities analysis. There are relationships among activities that can be expressed using a linear inequality to show the constraints on the arrangement of activities. This model indicates that two or more activities can be simultaneously rearranged to improve time management, which may be a source of variation in VTTS. This time allocation model can explain why large-scale high-speed rail construction in China faces significant market risks and a high likelihood of economic loss. Data from a new ticket sales and booking system for railway passengers indicate that passengers prefer conventional overnight sleeper trains, rather than high-speed trains, for long-distance travel, which supports the analysis of the time allocation model.     

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.     

Total cost analysis: An alternative to benefit-cost analysis in evaluating transportation alternatives

This paper explains the theory in support of total cost analysis (TCA) to compare transportation system alternatives. The full costs of each alternative are first aggregated, including travel time costs and monetizable environmental and social costs. Many costs which are considered on the benefits side of the equation in benefit-cost analysis (BCA) as "cost savings" are brought over to the costs side. Total cost differences among alternatives are then traded off against their estimated non-monetized benefits or impacts, just as a consumer trades off product quality against cost before deciding which product he or she will buy. One advantage of TCA over traditional BCA is that the concept of "total cost" is more easily understood by the public and by political decision-makers than BCA concepts such as "net present worth", "benefit-cost ratio" and "internal rate of return". A second advantage is that there is no suggestion that all "benefits" have been considered; decision-makers are free to use their own value judgements to trade off total cost against non-monetizable social, environmental and economic impacts, just as they trade off quality and convenience against cost when purchasing goods and services in their roles as consumers. The TCA approach is demonstrated in this paper through a case study of two systemwide alternatives for the Baltimore, MD urban area.