Short-line railroad managers discuss their industry

In the United States, the 1980 Staggers Rail Act created a positive regulatory environment for the creation of new short-line railroads. At present there are about 450 of these railroads that have less than 250 miles of trackage. This study asked managers/owners of these railroads two basic questions. First, what do you believe is the single most important trend that is currently taking place in your industry. The most frequently noted trend was the frustration of working with the larger Class 1 railroads. Five additional trends were also identified by the respondents. The second question asked the respondents if they thought the short-line sector of the rail industry will become more or less important in the next ten years and why. About 70% of the owner/managers believed their industry would become more important in the next decade. The most commonly expressed reason for this position is that the Class 1 railroads will increasingly specialize in mainline service only. Three other rationales were also enumerated. For the managers that thought their industry would become less important, the most noted reason was their trackage would not safely transport the newer very heavy bulk commodity freight cars.     

Transporting export-bound grain by rail: Rail rates in the Post-Staggers Rail Act Period

A spatial analysis involving four origin states (Illinois, Iowa, Minnesota and Nebraska) and two destinations (Gulf of Mexico and Pacific Northwest) is conducted in order to determine if pricing practices by the same or different railroads in different regions are consistent. A system of structural equations is estimated and dynamic regression tests are conducted because of the dynamic nature of interregional trade and arbitrage activities. The results indicate that the railroad industry is noncompetitive and that rail rates converge at a different speed to their desired levels in different regions. This may be partly due to the increased concentration in the railroad industry that took place during last twenty years.     

Large-scale network distribution of pooled empty freight cars over time,with limited substitution and equitable benefits

A set of models and procedures is described for finding the optimal distribution of empty freight cars owned by the railroads participating in a pooling agreement. A distinction is drawn between a system focus, in which the emphasis is on minimizing total cost, and a company focus, in which the benefits of the agreement to the individual railroads are emphasized. Limited car substitution is accounted for by combining interchange costs with distribution costs, and incorporating interchange possibilities and prohibitions into the network structure. Temporal variations in car supply and demand levels are also taken into account. A large-scale network algorithm is used in conjunction with decomposition to obtain solutions which show for a given time horizon how much equity can be achieved in the balance of savings among the railroads involved and at what cost. Results using actual operating data are reported.     

Closed form models to assess railroad technology investments

ABSTRACT

Class I railroads in North America collectively invested USUS$11.2 billion to comply with a U.S. federal mandate to deploy positive train control as a form of train protection system. This amount dwarfs the potential savings from accidents the technology could prevent. Therefore, railroads must seek additional benefits. This research contributes simple closed-form models to inform strategies that can leverage the technology deployment by estimating the annual additional net benefits, internal rate of return, and benefit-cost ratio needed for a desired payback period.     

A method to measure the eco-efficiency of diesel locomotive

Brazilian railroads transport over 490 million tons a year using diesel-electric locomotives. These locomotives emit several pollutants into the atmosphere and because of that, the railroads seek to reduce emissions and achieve global emission standards. Thus, it is important to analyze the environmental impact of the use of diesel and alternative fuels to reach environmental standards. This paper makes use of a method based upon the World Business Council for Sustainable Development (WBCSD) metrics to evaluate the locomotives’ eco-efficiency. The method was applied to Estrada de Ferro Vitória a Minas (EFVM). Different scenarios representing the exchange of fuel sources and technologies were developed, tested and analyzed. The impacts were evaluated by seven eco-efficiency performance indicators and compared with United States Environmental Protection Agency (EPA) standards. The results offered cost savings and emissions reduction opportunities.     

Individual freight effects,capacity utilization,and Amtrak service quality

This paper offers a new perspective on the post-deregulation rail industry. We hypothesize that a link exists between individual freight effects and Amtrak service quality. Specifically, we investigate the relationship between freight control of the infrastructure on which Amtrak trains operate and Amtrak train delays. Our sample consists of 1117 directional station-pairs for fiscal years 2002 through 2007 on 28 Amtrak non-Northeast Corridor passenger routes. We found that freight effects have a significant impact on Amtrak train delays after controlling for other important delay determinants such as the capacity utilization rate. The impact is higher on long-distance routes. We also observed significant differences between the effects of different freight railroads. For example, Amtrak operations on infrastructure controlled by several Class I railroads experienced significantly larger delays than baseline operations, while Amtrak train delays on Burlington Northern and Santa Fe’s tracks actually fell below baseline levels.     

Development of a differential route share model for railroad freight traffic

This paper summarizes work undertaken towards development and calibration of a model to predict the distribution of rail freight traffic among competing routes. The model is designed for use in analyzing the traffic effects of changes in the level-of-service on selected rail lines. The model predicts route shares based on the overall network configuration of each railroad participating in a given market. The model selects feasible routes, discards those routes which appear to be too circuitous or costly, and then assigns traffic to the remaining routes in accordance with several network characteristics. It is designed to be sensitive to level-of-service changes, and to simulate the response of shippers and railroads to a competitive environment. A multiple route-finding algorithm was used to find possible routes based on the number of railroads operating at the originating and terminating end of a market. Multiple routes were determined and matched with observed traffic flows from the ICC One-Percent Waybill Sample. Physical network characteristics for each route, including distance, junction frequency, and “impedance,” were calculated from the network model and were correlated with the traffic share observed on each route in the market. A two-stage model was developed to find feasible routes from the set of possible routes and to allocate traffic to feasible routes based on levels-of-service. The model was calibrated on 9,793 routes from 1,199 markets with twenty or more carloads from the 1977 One-Percent Carload Waybill Sample. Model calibration supported the hypothesis that network route characteristics did indeed influence shipper choice of route, and that a normative model could be used to assess relative attractiveness of routes under various railroad corporate ownership restructuring scenarios.     

Improving the performance of rail yards through dynamic reassignments of empty cars

This paper considers the problem of reducing the time that empty cars spend in classification yards of rail systems operating under real-time information and automated schedule-adjustment technologies. The proposed methodology performs dynamic reassignments of empty cars through a fast and efficient solution procedure based on the assignment algorithm. The procedure has been tested on real-life data from one of the major railroads in North America. Computational results show that the procedure runs fast and yields savings in the time that the empty cars spend in the yard.     

The impact of U.S. rail regulatory reform on railroad management and organizational structure

The management structure of U.S. railroads has been historically characterized as static and bureaucratic. Many writers have attributed this to years of restrictive government regulation. This paper tests the hypothesis that observable characteristics and organizational structure of railroad management have changed in conjunction with recent regulatory reform. Management characteristics are analyzed in both 1977 and 1983. Major findings are that managers in 1983 are significantly younger and better educated with fewer years of company and industry service. Railroad organizational structures are also reviewed before and after deregulation to assess whether management structures are becoming leaner and less mechanistic.     

The states and passenger rail service

In recent years, a number of states have acted to expand the passenger rail services provided to their citizens by subsidizing Amtrak. Subsidizing states tend to be relatively metropolitan, with large tourist industries, large populations, relatively liberal electorates (for 1980 subsidy decisions), and a history of efforts to protect the environment. Multivariate analysis indicates that population, electoral liberalism, and environmental concern play key roles in shaping subsidy decisions, although electoral liberalism has little influence on 1985 subsidies.     

A cost and expected consequence approach to planning and managing railroad transportation of hazardous materials

Although hazardous materials (hazmat) account for around 140 million tons of all railroad freight traffic in the US, it has not received much attention from academic researchers. This is surprising especially when one considers the volume of hazmat moved by railroads in both North America and Europe. In this paper we develop a bi-objective optimization model, where cost is determined based on the characteristics of railroad industry and the determination of transport risk incorporates the dynamics of railroad accident. The optimization model and the solution framework is used to solve a realistic-size problem instance based in south-east US, which is then analyzed to gain managerial insights. In addition, a risk-cost frontier depicting non-dominated solutions is developed, followed by conclusion.     

Determinants of Efficiency at Major Brazilian Port Terminals

This paper reports on the use of different approaches for measuring the efficiency of major Brazilian port terminals. Two of the most important approaches, DEA (Data Envelopment Analysis) and SFA (Stochastic Frontier Analysis), were performed on data collected from 25 terminals. The findings indicate that the majority of Brazilian terminals are running short on capacity due to the export boom that has occurred over the past few years and due to the lack of investment in capacity expansion. Furthermore, efficiency measurements derived from a reduced model with only one input and one output were explained based on variables such as type of cargo handled (container or bulk), connectivity of the terminal to railroads, and control (state or private) of the terminal. Implications and directions for future research are explored.     

Competition and Ownership in Land Passenger Transport: The Sixth International Conference,Cape Town,South Africa,September 1999 - Part 1

The ability of conventional South African travel analysis practices to analyse adequately the travel needs of the poor is examined. The origins and nature of conventional practices are described, and it is observed that typically their scope has been limited to motorized modes, commutes and peaks. The paper reports on the findings of an activity diary survey administered in Cape Town that extended the conventional scope of analysis. An activity‐based survey method was selected because it typically yields higher rates of trip recall than other methods and is therefore relatively well suited to investigating travel behaviour in its fuller complexity. Selected findings of the survey are presented to demonstrate that travel occurring by non‐motorized modes, for non‐work purposes and during off‐peak periods, is considerable. It is argued that the conventional limitation in analytical scope can create serious misconceptions of the true nature of travel behaviour, particularly of low‐income households. By restricting the focus of analysis to motorized, work and peak period trip‐making, there is a risk of a routine bias being introduced in the way the urban passenger transport problem is understood, and in the nature of the interventions that are implemented as a result.     

An aggregate capacity estimation model for the evaluation of railroad passing constructions

The Netherlands Railways operates a double tracked intensively used network of railroads. To expand the transportation capacity, each year a number of infrastructure expansions are considered. The evaluation of these expansions is traditionally done by establishing a set of detailed timetables that serve the forecasted transportation demand and that can be executed with the proposed infrastructure expansion. However, the development of a detailed timetable is a very time consuming process, and therefore leaves little opportunity for comparing many alternatives. In this paper, we present and test an aggregate model that can be used to single out the most promising investment alternatives in the railroad infrastructure, specifically passing constructions. The aggregate model provides the user with insight into the ranking of the various alternatives and additionally gives a relative insight into the theoretical capacity of the proposed infrastructure change.     

Optimal fueling strategies for locomotive fleets in railroad networks

Railroad companies spend billions of dollars each year to purchase fuel for thousands of locomotives across the railroad network. Each fuel station charges a site-dependent fuel price, and the railroad companies must pay an additional flat contracting fee in order to use it. This paper presents a linear mixed-integer mathematical model that integrates not only fuel station location decisions but also locomotive fueling schedule decisions. The proposed model helps railroads decide which fuel stations to contract, and how each locomotive should purchase fuel along its predetermined shipment path, such that no locomotive runs out of fuel while the summation of fuel purchasing costs, shipment delay costs (due to fueling), and contracting charges is minimized. A Lagrangian relaxation framework is proposed to decompose the problem into fueling schedule and facility location selection sub-problems. A network shortest path formulation of the fueling schedule sub-problem is developed to obtain an exact optimal solution to the fueling schedule sub-problem. The proposed framework is applied to a large-scale empirical case and is shown to effectively reduce system costs.     

Adaptive traffic parameter prediction: Effect of number of states and transferability of models

Traffic parameters can show shifts due to factors such as weather, accidents, and driving characteristics. This study develops a model for predicting traffic speeds under these abrupt changes within regime switching framework. The proposed approach utilizes Hidden Markov, Expectation Maximization, Recursive Least Squares Filtering, and ARIMA methods for an adaptive forecasting method. The method is compared with naive and mean updating linear and nonlinear time series models. The model is fitted and tested extensively using 1993 I-880 loop data from California and January 2014 INRIX data from Virginia. Analysis for number of states, impact of number of states on forecasting, prediction scope, and transferability of the model to different locations are investigated. A 5-state model is found to be providing best results. Developed model is tested for 1-step to 45-step forecasts. The accuracy of predictions are improved until 15-step over nonadaptive and mean adaptive models. Except 1-step predictions, the model is found to be transferable to different locations. Even if the developed model is not retrained on different datasets, it is able to provide better or close results with nonadaptive and adaptive models that are retrained on the corresponding dataset.     

The relationship between property values and railroad proximity: a study based on hedonic prices and real estate brokers' appraisals

We study the relationship between the price of residential property value and proximity to railroads in Oslo, by two different methods, namely a) through a hedonic price study where the statistical relationship between property prices and railroad proximity is estimated, and b) through a multi-attribute utility investigation of real estate agents' evaluation of such a relationship. We find in both cases that there are strong effects of proximity to railroad lines on property prices, at distances less than 100 meters from the lines. In the statistical study log-linear relationships fit the data best, and our estimates indicate that a doubling of the distance from the railroad line, within a 100 meter bound, increases the property price by about 10%. With real estate agents only a linear relationship is probed. This yields an increase in the price of an average relevant housing unit by about 182,000 NOK, due to a increase in the distance to a railroad track from 20 to 100 meters. The equivalent figure from the statistical study is in the range 120–150,000 NOK. The two figures are thus of the same magnitude.     

Data-driven optimization of railway maintenance for track geometry

Railway big data technologies are transforming the existing track inspection and maintenance policy deployed for railroads in North America. This paper develops a data-driven condition-based policy for the inspection and maintenance of track geometry. Both preventive maintenance and spot corrective maintenance are taken into account in the investigation of a 33-month inspection dataset that contains a variety of geometry measurements for every foot of track. First, this study separates the data based on the time interval of the inspection run, calculates the aggregate track quality index (TQI) for each track section, and predicts the track spot geo-defect occurrence probability using random forests. Then, a Markov chain is built to model aggregated track deterioration, and the spot geo-defects are modeled by a Bernoulli process. Finally, a Markov decision process (MDP) is developed for track maintenance decision making, and it is optimized by using a value iteration algorithm. Compared with the existing maintenance policy using Markov chain Monte Carlo (MCMC) simulation, the maintenance policy developed in this paper results in an approximately 10% savings in the total maintenance costs for every 1 mile of track.     

On the existence of stationary states in general road networks

Our daily driving experience and empirical observations suggest that traffic patterns in a road network are relatively stationary during peak periods. In numerous transportation network studies, there has been an implicit conjecture that stationary states exist in a network when origin demands, route choice proportions, and destination supplies are constant. In this study, we first rigorously formulate the conjecture within the framework of a network kinematic wave theory with an invariant junction model. After defining stationary states, we derive a system of algebraic equations in 3-tuples of stationary link flow-rates, demands, and supplies. We then introduce a new definition of junction critical demand levels based on effective demands and supplies. With a map in critical demand levels, we show that its fixed points and, therefore, stationary states exist with the help of Brouwer’s fixed point theorem. For two simple road networks, we show that the map is well-defined and can be used to solve stationary states with a brute-force method. Finally we summarize the study and present some future extensions and applications.