Rail Operations Research Articles

Optimize train capacity allocation for the high-speed railway mixed transportation of passenger and freight

The collaborative transportation strategy of passengers and freights can improve the efficiency and revenue of the high-speed railway (HSR) system. This paper focuses on the train capacity allocation problem for the mixed transportation pattern of passenger and freight in HSR systems, in which rail operators introduce revenue management to determine the optimal train capacity allocation plan for each train service. We first propose a general train capacity allocation model which addresses passenger priority and freight loading/unloading capacity, and then the deterministic and stochastic demand scenarios are considered respectively. With the deterministic demand, the train capacity allocation model is linear programming with the objective of maximizing the revenue of the HSR system. While a non-linear programming model is built for the stochastic demand to maximize the expected revenue. For solving the problem with stochastic demand, the non-linear programming model is transformed into a mixed integer linear programming model, which can be easily solved by the existing solver to obtain the optimal solution. Two different-sized numerical experiments are conducted to demonstrate the efficiency and effectiveness of the proposed methods.

A game-theoretic approach to an oligopolistic transportation market: Coopetition between incumbent systems subject to the entrance threat of an HSR service

• Competition and coopetition of airline, intercity bus, and entrant HSR operators. • The main driver for the operators’ pricing competition is identified. • Non-pricing strategies may be necessary for the incumbent operators’ survival. • Short-term government policies may not guarantee the passengers’ full satisfaction. We investigate pricing competition between passenger transportation modes in a transportation market by using a game-theoretic approach. Airplane and intercity bus operators are considered as incumbent; while a High-Speed Rail (HSR) operator decides on whether or not to enter the market. If the incumbent operators evaluate the entrance threat of HSR as serious, they have two alternatives: a barrier pricing strategy (BPS) to deter its entrance, and an accommodation pricing strategy (APS). Their interaction involves two competitive and cooperative aspects, called the coopetition interaction. Moreover, we extend the analysis to a real-world situation in which a government, as a social welfare maximizer, intends to certify and support one operator out of two candidate HSR operators. Our analyses reveal that: (a) the passengers’ heterogeneity (with respect to their perceptions on the operators’ quality of services) is the main driver for pricing competition between the three operators. (b) Under certain conditions, implementing a BPS is not only precluded for the incumbent operators, but also their pricing strategies cannot even guarantee their survival in the market. To address this issue, we suggest the incumbent operators adopt non-pricing strategies. Nevertheless, an incumbent operator may freely ride on the other ones’ non-pricing strategy. (c) Under a short-term (long-term) planning horizon, the government should specifically concentrate on compensating for the HSR operating cost (procurement cost of rolling stock). (d) In contrast to the short run, government expenses and the HSR’s profit exploitation provide a strong foundation for the passengers’ full satisfaction in the long run.

Data-Driven Analysis of Short-Distance Freight Rail Transportation Potential: A Case Study of Log Movements in the U.S. Lake Superior Region

As freight rail transportation in the U.S.A. increasingly concentrates on high-volume and longer distance train movements, shippers in rural areas with fragmented freight volumes, lighter line densities, and shorter distances have struggled to maintain the rail share of their shipments. The forest products industry in the mostly rural Lake Superior region is no exception and has seen a transition toward truck transportation for its main raw material, logs. The forest industry has attributed the phenomenon to reduced rail access and increased rail rates, and asked us to use their log shipment and rail operations network data to explore if (1) improved access through shared sidings, re-opened sidings, or both, and (2) rail rate reductions would encourage a modal shift from trucks back to rail. We developed four integer/mixed-integer programming models and several scenarios to research the problem. We concentrated on (1) allowing log consolidation from multiple companies at rail sidings and (2) rail rate reductions with and without volume thresholds. Our results showed that additional flexibility through shared rail sidings, re-opening of unused/closed sidings, or both, has minimal impact on increasing the rail modal share. Rail rate discounts with or without minimum volume thresholds were able to encourage a modal shift, but growing volume through rate reductions may not be attractive from the rail service provider perspective. While the results were not encouraging, our models offer the industry a data-based approach for further investigations, such as the impacts of potential shifts to a shortline cost model, or targeted analysis of specific mills that showed greater promise for a modal shift.

Real-time rescheduling approach of train operation for high-speed railways using problem-specific knowledge under a station blockage

This study considers the train timetable as the problem object to investigate the station blockage caused by emergencies. Based on the evolutionary algorithm framework, a real-time rescheduling approach using problem-specific knowledge is proposed. This approach ensures the safety and efficiency of high-speed rail operations and the satisfaction and comfort of passengers by minimizing the total train delay. First, a permutation encoding method is developed to reduce invalid searches in the search space based on the rescheduling strategy of reordering train departure sequences. Next, according to the train operation tracking mode, called tracking interval control, a heuristic decoding method is designed to eliminate all constraints of train operation to improve efficiency. Finally, the dispatcher's experience in adjusting the train timetable is used as the problem-specific knowledge to initialize the initial population of evolutionary computing. A heuristic population initialization method based on problem-specific knowledge is employed to speed up the algorithm convergence in the early stage and improve solution equality. Furthermore, the Beijing–Tianjin high-speed railway line is used as an example. Nine typical scenarios with different blockage durations of 20–150 min under the station blockage are installed at the Beijing South station. The strengthened elitist genetic algorithm (SEGA) and differential evolution (DE) are selected to perform the simulation using different combinations of the real-integer or permutation encoding and random or heuristic population initialization, respectively. The simulation results indicate that, compared with the real-integer encoding that cannot obtain feasible solutions, the two evolutionary algorithms can provide the rescheduling solution with a smaller total train delay in an average time of 9 s after using the permutation encoding. Besides, the results of the two evolutionary algorithms improved by the heuristic population initialization can quickly converge to a quasi-optimal solution. Finally, the SEGA in the permutation encoding with the heuristic population initialization is chosen as the optimal improved evolutionary algorithm. This improved evolutionary algorithm can provide quasi-optimal solutions in 20 s in the seven scenarios where the CPLEX cannot provide optimal solutions in 10 min.

Analisis Persebaran Tingkat Kebisingan Kereta Api di Rel Double Track Winongo Kota Madiun

Noise is an annoying sound when listened to for a long time. The standard for noise level in housing is based on KepMenLH No. 48 of 1996 worth 55 dB(A). Double track rails lead to increased rail operations and noise in the surrounding environment. This research was conducted to analyze the environmental noise level due to the train crossing the double track rail at Graha Kirana Winongo Housing, Madiun City by using a Sound Level Meter (SLM) device. Measurements were made at two points, namely at a distance of 7.5 meters and 21 meters. The results of the study the average value of environmental noise due to trains at a distance of 7.5 meters is 80 dB(A) and a distance of 21 meters is 75 dB(A). This value exceeds the standard noise level of 55 dB(A). Researchers provide mitigation in the form of suggestions for housing residents to build noise barriers or plant trees with dense leaves, and if residents are going to build new housing, it is recommended to be at a distance of 75 to 80 meters from the train tracks because the noise value at that distance is approximately 55 dB (A).

Influence of the Rail Program on Bus Transit in Los Angeles

In November 1980, voters in Los Angeles County, California, approved Proposition A, which stipulated a one-time, three-year rollback of bus fares to 50¢. Afterwards, at least 35 percent of the revenues had to be used for rail construction and operation (with a stated emphasis on construction). The program moved forward as called for, and by the early 1990s the Blue Line to Long Beach was in operation. The subway and an additional light rail line would both open by 1995.In the early 1990s, however, opponents of rail began a campaign to discredit the program using premature, distorted, and sometimes simply false information about rail s effectiveness. Embarrassed by construction problems and confused by internal issues, the Metropolitan Transit Authority (MTA) found it difficult to defend the new rail system. In 1994, a suit was filed by the Bus Riders Union, a small group of bus riders. In 1996, even though most of the basic assertions of the suit were proven to have been either premature or false, the MTA agreed to a settlement it is now trying to live up to.In truth, the MTA fully supported the bus system well after falling ridership would have called for service cutbacks. The number of buses in service stayed high, the bus-miles of service dropped far less than ridership, and the number of empty bus seats actually rose. The bus system lacked for neither operating funds nor subsidies. Even the average fare paid by the transit user (in constant 1999 dollars) changed very little since the early 1980s. Whatever the reasons for the slide in bus ridership, the rail system cannot be blamed.The new rail system continues to grow in importance. Less than 10 years after the Blue Line was inaugurated, the two light rail lines, the still incomplete subway, and the Los Angeles portion of the regional Metrolink commuter rail system together carry 11 percent of all MTA transit riders and 22 percent of its passenger-miles. Rail is also proving to be faster than the bus option even including a bus-to-rail transfer. And rail‘s operating cost effectiveness, already better than that of the bus, keeps improving.

Cooperative braking of urban rail vehicles with Koopman model predictive control

AbstractBraking control of urban rail vehicles with multiple carriages is critical to ensure the safe operation of urban rails. However, existing decentralized braking control methods lead to the inconsistent speed and excessive coupler force among carriages, which compromises the operation safety of urban rails. To address this issue, a cooperative braking strategy is proposed for urban rail vehicles based on Koopman model predictive control method. First, a cyber‐physical model is established, where the physical layer characterizes the dynamic model of multiple carriages using the Koopman operator. The cyber layer represents the communication topology of carriages with graph theory. Second, a cooperative braking controller is designed with the distributed model predictive control method. An optimisation problem is formulated to minimize the speed inconsistency and relative displacement difference among carriages. Third, extensive simulations under various scenarios, including normal and extreme operating conditions, are conducted to verify the effectiveness of the proposed method. Simulation results show that, compared with the classical decentralized method, the proposed braking method reduces the average relative displacement by 78% while reducing the speed error by 29%.

Making Regional Railroads More Attractive—Research Studies in Germany and Patronage Characteristics

This article summarizes current research on regional rail passenger service in Germany. The aim of the research was to help rail operators, municipalities along the rail lines, and transportation planners identify the most effective strategies for improving rail service and patronage. The article outlines study contents and purpose and then summarizes the most important study findings. It also presents action and research recommendations. In addition, current rail developments in Germany and methods for increasing patronage and reducing costs with special focus on the separation of infrastructure and operations are described. Finally, patronage data for different rail segments are compared to help determine whether improvement measures should be applied and what impacts they could have on patronage.

Forecasting Mobile Ticketing Adoption on Commuter Rail

Several commuter rail systems are beginning to accept mobile payments, in which tickets are purchased and validated on smartphones. Mobile payments may improve the rider experience while reducing costs and simplifying the fare collection process for rail operators. Before investing in this new ticketing technology, rail operators want to understand rider demand for mobile tickets. To assess the potential adoption of mobile payments, stated preference data from an onboard survey on two commuter rail lines (Worcester and Newburyport/Rockport) in the greater Boston area were analyzed. Binary logit was then used to forecast adoption on all commuter rail lines. Based on this model, 26 percent of commuter rail riders in Boston are very likely to adopt mobile ticketing.

Optimizing Skip-Stop Rail Transit Stopping Strategy using a Genetic Algorithm

With skip-stop rail transit operation, transit agencies can reduce their operating costs and fleet size and passengers can experience reduced in-transit travel times without extra track and technological improvement. However, since skip-stop operation does not serve all stations, passengers for certain origins-destinations could experience increased access time, waiting time, total travel time, and/or transfer. Only when the stopping and skipping stations are carefully coordinated can skip-stop service benefit passengers and transit agencies.This research developed a mathematical model using a Genetic Algorithm that coordinated the stopping and skipping stations for skip-stop rail operation. Using the flexibility of a Genetic Algorithm, this model included many realistic conditions, such as different access modes, different stopping scenarios, different collision constraints, and different objective functions. Passengers were put into three types and nine groups depending on their origin-destination pairs and the station and transfer choices. Four types of collision constraints were developed depending on the skip-stop strategy.For this research, Seoul Metro system Line No. 4 was used as an example. With skip-stop operation, total travel time became about 17–20 percent shorter than with original all-stop operation, depending on the stopping constraints. In-vehicle travel time became about 20–26 percent shorter due to skipping stations, although waiting, transfer, and additional access times increased by 24–38 percent.

Rail Operations Control Centres

The article presents an overview of common trends in the evolution of rail operations control as well as the factors stipulating the existing approaches to the design of Rail Operations Control Centres (ROCCs) around the world. Based on the comparative analysis of various ROCCs and traffic parameters, the authors propose some classification of global traffic control models. The article outlines further steps towards a more detailed analysis of ROCCs in terms of their effectiveness by introducing a number of additional criteria and performance indicators to be taken into account.

Evolution of Rail Operations Control Centres

The article gives an overview of the evolution trends and stages of rail operations control centres (ROCCs) and outlines their future development and challenges in the context of the digital transformation of railway transport. It addresses the key aspects of further evolution of ROCCs in terms of closer integration of various functional layers and systems, automation of control and supervision functionalities, application of new data processing methods based on artificial intelligence.

Take on Board

Reducing the energy and power consumption of onboard auxiliaries is a key priority for rail operators in meeting sustainability targets. Here, EHRT looks at some of the key technologies worth exploring

Railroad accident causal analysis with unstructured narratives using bidirectional encoder representations for transformers

Railroad safety is one critical concern for the railroad industry. Extracting useful information from railroad safety-related textual materials is one significant and essential task. To better understand the contributing factors to the railroad accidents, previous studies have primarily focused on the structured fields, while few of them have developed a thorough analysis of the narratives. In addition, due to the difficulty of understanding the terminologies in the accidents’ narratives, it is challenging to extensively use these narratives as a time-consuming and labor-intensive task. Therefore, this study proposed a novel deep learning approach to consistently leverage the values behind these railroad accident narratives. The proposed method modified the classical Bidirectional Encoder Representations for Transformers (BERT) with the connection of a Deep Neural Network (DNN). To validate the superiority of the proposed BERT-DNN, several additional text classification methods were employed in the real-world railroad accident database. Results demonstrate the proposed method in this study can assign congruous accident causes based on the railroad accidents’ narratives precisely and outperforms previous state-of-the-art text classification approaches. The analytical results, along with proposed methodological framework, can contribute to an in-deep understanding of accident causes for practitioners and academics, and ultimately enhance rail operation safety.

A Synthesis of Mobile Ticketing Applications Used by Commuter Railroads in the United States

Since 2012, many major commuter railroads have deployed mobile ticketing applications (or “apps”) that allow passengers to pay fares directly using their smartphones. In light of this rapid technological change, this research aims to provide a synthesis of the current state of mobile ticketing in the United States. The 14 largest commuter railroads that have launched mobile ticketing apps are compared in four different areas: (1) the ticket validation process; (2) ticket types offered in the mobile app; (3) additional features in the app; and (4) the process for transferring to other modes using the app. The results reveal that all mobile ticketing applications considered in this analysis utilize visual inspection for validation, and that most of them also use quick response (QR) barcodes to validate tickets. Additionally, many of the commuter rail operators examined offer the majority of the ticket types available via traditional fare media in their mobile ticketing apps. The third dimension revealed a large degree of variation in the availability of additional travel-related features, such as trip planners and schedules, in mobile ticketing apps. Last, only a handful of commuter rail operators have fully integrated transfer policies between commuter rail and other nearby transit modes using mobile ticketing, which is an area that warrants further study. These findings are important for other commuter rail and transit operators that are considering deployment of mobile ticketing systems.

The Rail Surface Defects Recognition via Operating Service Rail Vehicle Vibrations

Rail surface defects will not only bring wheel rail noise during train operation, but also cause corresponding accidents. Most of the existing detection methods are manual detection, which is time-consuming, laborious, inefficient, and subjective. With the development of technology, automatic detection replaces manual detection, which reduces manual labor, improves efficiency, and objectively evaluates the surface state of rails, which is in line with the purpose of modern intelligent production. The automatic detection of a single sensor is usually not enough to complete the recognition, but multiple sensors need to be additionally installed and refitted on the service vehicle, which creates difficulty for on-site test conditions. Therefore, in order to overcome these shortages and to adapt to the actual vibration characteristics of service vehicles, a rail surface defect recognition method based on optimized VMD gray image coding and DCNN is proposed in this paper. Firstly, the optimization method of VMD mode number based on the maximum envelope kurtosis is proposed. The VMD after parameter optimization is used to decompose the four-channel axle box vibration signal, and the component with the largest correlation coefficient between each order eigenmode component and the original signal is extracted. Secondly, the filtered IMF components are arranged in sequence and encoded into grayscale images. Finally, the DCNN structure is designed, and the training set is input into the network for training, and the test set verifies the effectiveness of the network and realizes the recognition of rail surface defects. The test accuracy of railway data set measured on the serviced vehicle is 99.75%, and the results show that this method can accurately identify the category of rail surface defects. After adding Gaussian noise to the original signal, the test accuracy reaches 99.20%, which proves that the method has good generalization ability and anti-noise performance. Additionally, this method can ensure the safe operation of vehicles without adding new equipment, which reduces operation costs and improves the intelligent operation and maintenance of rails.

Developing a Microservices Integration Layer for Next-Generation Rail Operations Centers

This experience report provides insights into architectural challenges, design decisions, and lessons learned developing a microservices-based integration layer for Rail Operations Centre (ROC) systems. The discussed project is part of a Hitachi Rail R&D initiative to develop a modern solution that standardizes the integration of Hitachi Rail signaling and traffic management applications. We describe the system architecture, discuss the microservice API considerations, and share the lessons learned and the experiences operating a simplified implementation of the integration layer microservice API in the autonomous freight train project AutoHaul.

Position‐track‐time three‐dimensional network model‐based improvement for high‐speed rail scheduling and operation

AbstractThe train timetable and station operation plan play a critical role in the high‐speed railway (HSR) planning and management. The existing hierarchical optimization methods for the planning process of the HSR would affect the efficiency of train schedules and are often difficult to achieve an optimized scheme. This paper proposes a position‐track‐time three‐dimensional network, which describes the process of train operations in sections and stations at a macroscopic scale, while the track infrastructure including the position of insulation joints in stations are modeled microscopically. The modeled train running times and dwell times are based on standard timetable design values given in full minutes by the China Railway Corporation, while the interlocking times and minimum headway times are not specified explicitly. The problem is formulated as a large‐scale 0–1 linear integer programming model, which is solved using an extended branch‐and‐price algorithm. The effectiveness and precision of the model are verified through a real‐world case study on the Beijing–Shanghai HSR line. The results indicate that the proposed model can effectively improve the line capacity by 17.2% while ensuring that there is no conflict between train operations in sections and stations.

Social distancing and revenue management—A post-pandemic adaptation for railways

The SARS-CoV-2 pandemic has had a significant impact on rail operations worldwide. Adopting control measures such as a 50% occupancy rate can contribute to a safer travel environment, though at the expense of operational efficiency. This paper addresses the issues of social distancing and revenue maximization for a train operating company in a post-pandemic world. Although the two objectives appear to be highly contradictory, we believe that judicious planning can optimize both to a great extent. Existing research on social distancing on public transport has only considered the risk of virus transmission during travel. This is the first attempt to recognize the risk of virus spread in different cities along with transmission risk as part of developing a social distancing plan. We study the problem of assigning seats to passenger groups on long-distance trains while ensuring social distancing within coaches. A novel seating assignment policy is proposed that takes into account several factors that govern the spread of virus. In an effort to reduce the spread of the virus and improve revenue simultaneously, a mixed-integer programming (MIP) model is proposed to assign seats to passengers. Several families of valid inequalities and preprocessing steps are proposed to strengthen the MIP formulation, which represents a substantial contribution to the literature on group seat assignment problem. The validity of the model and the effectiveness of the valid inequalities have been evaluated using real-life data from Indian Railways. The computational results demonstrate a significant reduction in the risk of contagion and an increase in seat utilization compared to the current approach employed by operators.

Getting freight trains back on track–How railway undertakings, infrastructure owners and regulators can navigate the main dilemmas in freight business to drive sustainable growth

Rail freight reportedly makes for an environmentally friendly means of transport. It also has significant potential for making a lucrative business, a stark contrast to rail passenger transport. Yet in Europe rail freight has long been displaced over its road equivalent and grown at rates inferior to overall land goods freight. Sustainable, profitable rail freight operations depend not only on goods volume, travel distance and pricing, but further on other key aspects permeating goods transportation by rail. Our research demonstrates that the choice for railway undertakings, infrastructure owners, and regulators alike, is in practice a complex one as depending on many, often competing factors. In fact, the key questions usually raised v.a.v. rail freight operations may be summed up to the following: (a) Mixed passenger and freight train operation or dedicated train corridors? (b) Conventional or heavy axle loads for freight trains? (c) Unitized wagonload or integrated trainload services? (d) Dangerous goods land shipping by rail or road? (e) Autonomous or manned freight train operation? Despite many individual contributions in the field, there is currently no single framework addressing the problem holistically. This paper breaks down what is seemingly a hard-to-balance decision-making process for rail freight players. It records and analyzes the forces and dynamics behind the dilemmas above and allows to: provide those partaking in the decision-making process with a robust framework identifying the key drivers behind sustainable rail freight growth; help them individually and collectively make more sound decisions regarding rail operations as a whole–including, in particular, strategic decisions regarding policy and/or investment; and, eventually, to enable them to craft and pursue viable, sustainable transport and business strategies. The research is underpinned by literature data review.