Estimating the marginal cost of railway track renewals using corner solution models

Economic theory advocates marginal cost pricing for efficient utilisation of transport infrastructure. A growing body of literature has emerged on the issue of rail marginal infrastructure wear and tear costs, but the majority of the work is focused on costs for infrastructure maintenance. Railway track renewals are a substantial part of an infrastructure manager’s budget, but in disaggregated statistical analyses they cause problems for traditional regression models since there is a piling up of values of the dependent variable at zero. Previous econometric work has sought to circumvent the problem by aggregation in some way. In this paper we instead apply corner solution models to disaggregate (track-section) data, including the zero observations. We derive track renewal cost elasticities with respect to traffic volumes and in turn marginal renewal costs using Swedish railway renewal data over the period 1999–2009. This paper is the first attempt in the literature to apply corner solution models, and in particular the two-part model, to disaggregate renewal cost data in railways. It is also the first paper that we are aware of to report usage elasticities specifically for renewal costs and therefore adds important new evidence to the previous literature where there is a paucity of studies on renewals and considerable uncertainty over the effects of rail traffic on renewal costs. In the Swedish context, we find that the inclusion of marginal track renewal costs in the track access pricing regime, which currently only reflects marginal maintenance costs, would add substantially to the existing track access charge. EU legislation requires that access charges reflect the ‘costs directly incurred as a result of operating the train service’, which should include a marginal renewal cost component. This change would also increase the cost recovery ratio of the Swedish infrastructure manager, thus meeting a policy objective of the national government.     

An econometric analysis of motorway renewal costs in Germany

The analysis of motorway renewal costs presented in this paper was driven by two research questions: First, to analyse the economic process of motorway renewal work and to identify whether there exist economies of scale; and second to identify the influence of traffic volume on renewal costs and to derive an estimate of marginal infrastructure costs as part of optimal road user charges. The analysis is based on cross-sectional data for motorway renewal costs and traffic volume in Germany during the period 1980–1999. Two translog models were estimated, each of them including the factor input prices for labour, material and capital, and a set of regional dummy variables as well as dummy variables for the type of material used for renewal. The first model includes in addition to these variables the sqm of renewed road as explanatory variable. The second model was constructed to analyse the relationship between traffic volume and renewal costs and contains the average annual daily traffic volume of trucks and passenger cars as independent variables. Two main results were derived from the models: First, motorway renewal work is characterised by substantial economies of scale. Second, the relationship between renewal costs and traffic volume is expressed by a cost elasticity, i.e., the ratio between marginal and average costs, which ranges from 0.05 up to 1.17 with a digressive increase of marginal costs.     

Marginal costs of freeway traffic congestion with on-road pollution exposure externality

The health cost of on-road air pollution exposure is a component of traffic marginal costs that has not previously been assessed. The main objective of this paper is to introduce on-road pollution exposure as an externality of traffic, particularly important during traffic congestion when on-road pollution exposure is highest. Marginal private and external cost equations are developed that include on-road pollution exposure in addition to time, fuel, and pollution emissions components. The marginal external cost of on-road exposure includes terms for the marginal vehicle’s emissions, the increased emissions from all vehicles caused by additional congestion from the marginal vehicle, and the additional exposure duration for all travelers caused by additional congestion from the marginal vehicle. A sensitivity analysis shows that on-road pollution exposure can be a large portion (18%) of marginal social costs of traffic flow near freeway capacity, ranging from 4% to 38% with different exposure parameters. In an optimal pricing scenario, excluding the on-road exposure externality can lead to 6% residual welfare loss because of sub-optimal tolls. While regional pollution generates greater costs in uncongested conditions, on-road exposure comes to dominate health costs on congested freeways because of increased duration and intensity of exposure. The estimated marginal cost and benefit curves indicate a theoretical preference for price controls to address the externality problem. The inclusion of on-road exposure costs reduces the magnitudes of projects required to cover implementation costs for intelligent transportation system (ITS) improvements; the net benefits of road-pricing ITS systems are increased more than the net benefits of ITS traffic flow improvements. When considering distinct vehicle classes, inclusion of on-road exposure costs greatly increases heavy-duty vehicle marginal costs because of their higher emissions rates and greater roadway capacity utilization. Lastly, there are large uncertainties associated with the parameters utilized in the estimation of health outcomes that are a function of travel pollution intensity and duration. More research is needed to develop on-road exposure modeling tools that link repeated short-duration exposure and health outcomes.     

Railway traffic disturbance management—An experimental analysis of disturbance complexity,management objectives and limitations in planning horizon

With the increasing traffic volumes in European railway networks and reports on capacity deficiencies that cause reliability problems, the need for efficient disturbance management becomes evident. This paper presents a heuristic approach for railway traffic re-scheduling during disturbances and a performance evaluation for various disturbance settings using data for a large part of the Swedish railway network that currently experiences capacity deficiencies. The significance of applying certain re-scheduling objectives and their correlation with performance measures are also investigated. The analysis shows e.g. that a minimisation of accumulated delays has a tendency to delay more trains than a minimisation of total final delay or total delay costs. An experimental study of how the choice of planning horizon in the re-scheduling process affects the network on longer-term is finally presented. The results indicate that solutions which are good on longer-term can be achieved despite the use of a limited planning horizon. A 60 min long planning horizon was sufficient for the scenarios in the experiments.     

A proposal for cost-related and market-oriented train running charges

This paper examines some key aspects of a charging system for promoting railway transport, including charges reflecting a clear relationship with costs (transparency) and charges reflecting the quality of the infrastructure manager's service. Train running charges recover track-related costs and can help to develop a charging system that meets these requirements. To orient train running charges to the market, a method for processing track maintenance and renewal costs is proposed whereby the quality of the service provided by an infrastructure is measured according to its utility to the railway undertaking. To achieve transparency, a single indicator is used for cost planning and the subsequent levying of costs on railway undertakings. The paper includes an example of how proposed train running charges would be calculated according to data from 14 European countries. The example shows that short-distance trains generate the lowest maintenance and renewal costs, followed by long-distance trains and freight trains.     

Optimal tolls for multi-class traffic: Analytical formulations and policy implications

This paper puts together an analytical formulation to compute optimal tolls for multi-class traffic. The formulation is comprised of two major modules. The first one is an optimization component aimed at computing optimal tolls assuming a Stackelberg game in which the toll agency sets the tolls, and the equilibrating traffic plays the role of the followers. The optimization component is supported by a set of cost models that estimate the externalities as a function of a multivariate vector of traffic flows. These models were estimated using Taylor series expansions of the output obtained from traffic simulations of a hypothetical test case. Of importance to the paper is the total travel time function estimated using this approach that expresses total travel time as a multivariate function of the traffic volumes. The formulation presented in the paper is then applied to a variety of scenarios to gain insight into the optimality of current toll policies. The optimal tolls are computed for two different cases: independent tolls, and tolls proportional to passenger car equivalencies (PCE).The numerical results clearly show that setting tolls proportional to PCEs leads to lower values of welfare that are on average 15% lower than when using independent tolls, though, in some cases the total welfare could be up to 33% lower. This is a consequence of two factors. First, the case of independent tolls has more degrees of freedom than the case of tolls proportional to PCEs. Second, tolls proportional to PCEs do not account for externalities other than congestion, which is likely to lead to lower welfare values.The analytical formulations and numerical results indicate that, because the total travel time is a non-linear function of the traffic volumes, the marginal social costs and thus the optimal congestion tolls also depend on the traffic volumes for each vehicle class. As a result of this, for the relatively low volumes of truck traffic observed in real life, the optimal congestion tolls for trucks could indeed be either lower or about the same as for passenger cars. This stand in sharp contrast with what is implied in the use of PCEs, i.e., that the contribution to congestion are constant. This latter assumption leads to optimal truck congestion tolls that are always proportional to the PCE values.The comparison of the toll ratios (truck tolls divided by passenger car tolls) for both observed and optimal conditions suggests that the tolls for small trucks are about the right level, maybe a slightly lower than optimal. However, the analysis of the toll ratio for large trucks seems to indicate a significant overcharge. The estimates show that the average observed toll ratio for large trucks is even higher than the maximum optimal toll ratio found in the numerical experiments. This suggests that the tolls for large trucks are set on the basis of revenue generation principles while the passenger car tolls are being set based on a mild form of welfare maximization. This leads to a suboptimal cross-subsidization of passenger car traffic in detriment of an important sector of the economy.     

Can high speed rail offset its embedded emissions?

This paper analyzes the climate implications of investments in high speed railway lines given uncertainty in future transport demand, technology and power production. To capture the uncertainty of estimated parameters, distributions for the annual traffic emissions reduction required to compensate for the embedded emissions from the construction of infrastructure are calculated using Monte Carlo simulation. In order to balance the annualized emissions from the railway construction, traffic volumes of more than 10 million annual one-way trips are usually required. Most of the traffic diverted from other modes must come from aviation and the project cannot involve the extensive use of tunnels.     

A new Swedish railroad policy: Separation of infrastructure and traffic production

In 1988 the Swedish nationalized railway company was separated into two separate entities, the Swedish State Railways in charge of running rail transport and the National Rail Administration, responsible for investment in and maintenance of rail infrastructure. This paper describes institutional aspects of this new railway policy. It also specifies methodological and practical problems in the computation of social marginal costs for using rail as well as road infrastructure. It is furthermore made likely that present fuel charges on road vehicles, but not the new rail use charges, are insufficient to cover costs for infrastructure use.     

Measuring marginal congestion costs of urban transportation: Do networks matter?

In determining the marginal cost of congestion, economists have traditionally relied upon directly measuring traffic congestion on network links, disregarding any “network effects,” since the latter are difficult to estimate. While for simple networks the comparison of the network-based congestion costs with the link-based ones can be done within a theoretical framework, it is important to know whether such network effects in real large-scale networks are quantitatively significant.In this paper we use a strategic transportation planning model (START) to compare marginal congestion costs computed link-by-link with measures taking into account network effects. We find that while in aggregate network effects are not significant, congestion measured on a single link is a poor predictor of total congestion costs imposed by travel on that link. Also, we analyze the congestion proliferation effect on the network to see how congestion is distributed within an urban area.     

A carbon footprint analysis of railway sleepers in the United Kingdom

This paper provides an assessment of the lifecycle Greenhouse Gas (GHG) emissions associated with the four most common sleeper (railroad tie or cross-tie in North America) types present in the UK rail network. It estimates the embodied material, process and transport emissions linked with the lifecycle activities of construction, relay/renewal and end-of-life of these variants at low and high traffic tonnage. The analysis suggests that at low traffic loads, the softwood sleepers perform the best over the whole simulated-period. At high traffic loads, the concrete sleepers outperform all other variants in terms of lifecycle CO₂e emissions, followed by hardwood, softwood and steel. Regardless of the scenario examined, the steel sleepers perform the worst due to the carbon intensive nature of their manufacturing process. This performance gap is amplified at high traffic loads, as their service life is excessively compromised. The analysis reveals that the end-of-life pathway of timber is a critical determinant of its footprint. Results suggest that the impact of disposing of these sleepers results in their footprint being magnified. Nevertheless, if a minimum of 50% follows the combustion pathway with subsequent heat recuperation, then a GHG reduction potential of between 11% and 18% of their footprint is feasible. From a whole-lifecycle cost lens, for higher tonnage routes, the choice of concrete sleepers results in considerable financial savings. If the infrastructure manager was to install sleepers with stiff under sleeper pads (USPs), it may achieve additional economic and GHG savings, with potential for increasing the latter using recycled carbon-neutral USPs.     

A marginal utility day-to-day traffic evolution model based on one-step strategic thinking

Most deterministic day-to-day traffic evolution models, either in continuous-time or discrete-time space, have been formulated based on a fundamental assumption on driver route choice rationality where a driver seeks to maximize her/his marginal benefit defined as the difference between the perceived route costs. The notion of rationality entails the exploration of the marginal decision rule from economic theory, which states that a rational individual evaluates his/her marginal utility, defined as the difference between the marginal benefit and the marginal cost, of each incremental decision. Seeking to analyze the marginal decision rule in the modeling of deterministic day-to-day traffic evolution, this paper proposes a modeling framework which introduces a term to capture the marginal cost to the driver induced by route switching. The proposed framework enables to capture both benefit and cost associated with route changes. The marginal cost is then formulated upon the assumption that drivers are able to predict other drivers’ responses to the current traffic conditions, which is adopted based on the notion of strategic thinking of rational players developed in behavior game theory. The marginal cost based on 1-step strategic thinking also describes the “shadow price” of shifting routes, which helps to explain the behavioral tendency of the driver perceiving the cost-sensitivity to link/route flows. After developing a formulation of the marginal utility day-to-day model, its theoretical properties are analyzed, including the invariance property, asymptotic stability, and relationship with the rational behavioral adjustment process.     

A latent variable representation of count data models to accommodate spatial and temporal dependence: Application to predicting crash frequency at intersections

This paper proposes a reformulation of count models as a special case of generalized ordered-response models in which a single latent continuous variable is partitioned into mutually exclusive intervals. Using this equivalent latent variable-based generalized ordered response framework for count data models, we are then able to gainfully and efficiently introduce temporal and spatial dependencies through the latent continuous variables. Our formulation also allows handling excess zeros in correlated count data, a phenomenon that is commonly found in practice. A composite marginal likelihood inference approach is used to estimate model parameters. The modeling framework is applied to predict crash frequency at urban intersections in Arlington, Texas. The sample is drawn from the Texas Department of Transportation (TxDOT) crash incident files between 2003 and 2009, resulting in 1190 intersection-year observations. The results reveal the presence of intersection-specific time-invariant unobserved components influencing crash propensity and a spatial lag structure to characterize spatial dependence. Roadway configuration, approach roadway functional types, traffic control type, total daily entering traffic volumes and the split of volumes between approaches are all important variables in determining crash frequency at intersections.     

Environmental benefits from better freight transport management: freight traffic in a VAR model

Most macro empirical studies on the price elasticity in the freight transport sector focus on the demand for transport. However, most of the external costs from the freight transport sector are more closely linked with the traffic volumes. In the paper an explicit distinction between traffic and transport demand is made by regarding traffic as an input in the shippers’ production of transport services, while transport demand is derived from firms’ production of output. An empirical analysis based on aggregate time series is carried out in a VAR model, where the stationary long run relationships are estimated using the so-called ‘Johansen Procedure’. The estimated price elasticity with respect to traffic (−0.81) is considerably higher than the elasticity with respect to transport (−0.47).     

Alternative methods for estimating full marginal costs of highway transportation

This paper presents various methods of estimating the full marginal cost (FMC) of highway passenger transportation. First, the computation of FMC is performed using the marginal cost functions, most of which were developed by Ozbay et al. [Ozbay, K., Bartin, B., Berechman, J., 2001. Estimation and evaluation of full marginal costs of highway transportation in New Jersey. Journal of Transportation and Statistics 4 (1)]. FMC is defined and calculated as “total cost per trip” as explained in this paper. However, in multiple origin-destination and multiple route highway networks, the practical application of the network-wide FMC concept is complicated. These issues are addressed in detail in this paper. Therefore, in the second method, a multiple route based FMC approach is proposed for a given origin-destination pair in the network. It is observed that the marginal values of different paths vary as much as 28%. Third, a comparison of FMC estimation results of two distinct measurement tools is presented. The FMC estimation is performed between a selected OD pair using the static transportation planning software output (TransCAD). The same analysis is repeated using the stochastic traffic simulation software output (PARAMICS). The differences in FMC values estimated by static transportation planning software and microscopic traffic simulation software are discussed.     

Dynamic user equilibrium with side constraints for a traffic network: Theoretical development and numerical solution algorithm

This paper investigates a traffic volume control scheme for a dynamic traffic network model which aims to ensure that traffic volumes on specified links do not exceed preferred levels. The problem is formulated as a dynamic user equilibrium problem with side constraints (DUE-SC) in which the side constraints represent the restrictions on the traffic volumes. Travelers choose their departure times and routes to minimize their generalized travel costs, which include early/late arrival penalties. An infinite-dimensional variational inequality (VI) is formulated to model the DUE-SC. Based on this VI formulation, we establish an existence result for the DUE-SC by showing that the VI admits at least one solution. To analyze the necessary condition for the DUE-SC, we restate the VI as an equivalent optimal control problem. The Lagrange multipliers associated with the side constraints as derived from the optimality condition of the DUE-SC provide the traffic volume control scheme. The control scheme can be interpreted as additional travel delays (either tolls or access delays) imposed upon drivers for using the controlled links. This additional delay term derived from the Lagrange multiplier is compared with its counterpart in a static user equilibrium assignment model. If the side constraint is chosen as the storage capacity of a link, the additional delay can be viewed as the effort needed to prevent the link from spillback. Under this circumstance, it is found that the flow is incompressible when the link traffic volume is equal to its storage capacity. An algorithm based on Euler’s discretization scheme and nonlinear programming is proposed to solve the DUE-SC. Numerical examples are presented to illustrate the mechanism of the proposed traffic volume control scheme.     

Marginal cost congestion pricing based on the network fundamental diagram

Congestion pricing schemes have been traditionally derived based on analytical representations of travel demand and traffic flows, such as in bottleneck models. A major limitation of these models, especially when applied to urban networks, is the inconsistency with traffic dynamics and related phenomena such as hysteresis and the capacity drop. In this study we propose a new method to derive time-varying tolling schemes using the concept of the Network Fundamental Diagram (NFD). The adopted method is based on marginal cost pricing, while it also enables to account realistically for the dynamics of large and heterogeneous traffic networks. We derive two alternative cordon tolls using network-aggregated traffic flow conditions: a step toll that neglects the spatial distribution of traffic by simply associating the marginal costs of any decrease in production within the NFD to the surplus of traffic; and a step toll that explicitly accounts for how network performance is also influenced by the spatial variance in a 3D-NFD. This pricing framework is implemented in the agent-based simulation model MATSim and applied to a case study of the city of Zurich. The tolling schemes are compared with a uniform toll, and they highlight how the inhomogeneous distribution of traffic may compromise the effectiveness of cordon tolls.     

Transport policy prioritisation for Dublin

Internalisation of the external costs of transport is currently the subject of much debate. Estimation of costs such as those of pollution and congestion is a primary element in any strategy involving policies for use in the internalisation of these costs. The objective of the TRENEN II STRAN project, funded by the EU, was to develop a methodology for estimation of the marginal external costs of transport. The model developed during the project was used in a series of case studies. One of the case studies, that conducted for Dublin, is reported in this paper. A brief summary of the TRENEN approach is presented followed by the results for Dublin produced from policies such as Do Nothing, Uniform pricing (internalising external costs by means of fuel taxation), Congestion Pricing (cordon pricing) and a first-best policy, the Full Optimum where one assumes that the policy maker has perfect pricing instruments available. As one would expect, the model shows that the greatest reduction in traffic level and external costs would occur if it were possible to introduce a highly differentiated and sophisticated pricing system. Increased taxation on fuel is not an efficient policy as it does not address the marginal external costs of congestion in a way that time-differentiated road-use pricing would. The results from testing of the different measures are interesting particularly those relating to parking and the way in which residents within the CBD and commuters to the CBD are dealt with. This revised version was published online in June 2006 with corrections to the Cover Date.     

Determinants of air cargo traffic in California

Studies on the economic impacts of air cargo traffic have been gaining traction in recent years. The slowed growth of air cargo traffic at California’s airports, however, has raised pressing questions about the determinants of air cargo traffic. Specifically, it would be useful to know how California’s air cargo traffic is affected by urban economic characteristics. Accordingly, this study estimates the socioeconomic determinants of air cargo traffic across cities in California. We construct a 7-year panel (2003–2009) using quarterly employment, wage, population, and traffic data for metro areas in the state. Our results reveal that the concentrations of both service and manufacturing employment impact the volume of outbound air cargo. Total air cargo traffic is found to grow faster than population, while the corresponding domestic traffic grows less than proportionally to city size. Wages play a significant role in determining both total and domestic air cargo movement. We provide point estimates for traffic diversion between cities, showing that 80% of air cargo traffic is diverted away from a small city located within 100 miles of a large one. Using socioeconomic and demographic forecasts prepared for California’s Department of Transportation, we also forecast metro-level total and domestic air cargo tonnage for the years 2010–2040. Our forecasts for this period indicate that California’s total (domestic) air cargo traffic will increase at an average rate of 5.9% (4.4%) per year.     

An assessment of cost management regimes in British rail infrastructure provision

Over the last decade, British railway engineering efficiency has come under close scrutiny, with general perceptions of massive maintenance cost escalations and a general lack of control over these costs. This is exemplified by headline figures such as Roger Ford??s perceptions of a 50% rise in maintenance costs since privatisation (Mod Railw 638:8, 2001), or the more recent figure of a doubling in all rail costs since privatisation presented by Shaoul (Public Money Manag 26:151?C158, 2006). Little, however, has appeared in the academic literature on the subject. This paper considers these issues through an examination of British railway infrastructure costs over the period 1980?C2009, which has seen three different infrastructure management regimes in place??the nationalised BR (1980?C1994), the privatised Railtrack (1995?C2001) and the not for dividend Network Rail (2002?C2010). Infrastructure costs are examined in total for all operating costs (including maintenance but excluding renewals and depreciation), and under two sub categories, signalling and management costs. The results show that in the case of total operating costs, by the end of the period (up to 2010) these had returned to pre-privatisation levels. The results also show that costs increased significantly following privatisation due to imperfect competition in sub contractor markets, but large declines in the last 6?years have eradicated most of these costs increases, although still do not match the best achieved under full public sector management. Management costs associated with the infrastructure on the other hand have increased significantly.     

An improved car‐following model for railway traffic

In this paper, we propose an improved traffic model for simulating train movement in railway traffic. The proposed model is based on optimal velocity car‐following model. In order to test the proposed model, we use it to simulate the train movement with fixed‐block system. In simulations, we analyze and discuss the space–time diagram of railway traffic flow and the trajectories of train movement. Simulation results demonstrate that the proposed model can be successfully used for simulating the train movement in railway traffic. From the space–time diagram, we find some complex phenomena of train flow, which are observed in real railway traffic, such as train delays. By analyzing the trajectories of train movement, some dynamic characteristics of trains can be reproduced. Copyright © 2011 John Wiley & Sons, Ltd.