Railway Enterprises Research Articles

A Novel Hybrid Deep Learning Model for Complex Systems: A Case of Train Delay Prediction

Predicting the status of train delays, a complex and dynamic problem, is crucial for railway enterprises and passengers. This paper proposes a novel hybrid deep learning model composed of convolutional neural networks (CNN) and temporal convolutional networks (TCN), named the CNN + TCN model, for predicting train delays in railway systems. First, we construct 3D data containing the spatiotemporal characteristics of real-world train data. Then, the CNN + TCN model employs a 3D CNN component, which is fed into the constructed 3D data to mine the spatiotemporal characteristics, and a TCN component that captures the temporal characteristics in railway operation data. Furthermore, the characteristic variables corresponding to the two components are selected. Finally, the model is evaluated by leveraging data from two railway lines in the United Kingdom. Numerical results show that the CNN + TCN model has greater accuracy and convergence performance in train delay prediction.

Стратегирование коммерциализации инноваций в условиях отечественной экономики данных

Professor A.G. Aganbegyan defines a new transport and logistics infrastructure as a key factor of economic growth, welfare, and transformation of Russia’s socio-economic system. This new infrastructure should include two-way highways, high-speed railways, regional airports, and major logistics centers in key transport hubs. Unfortunately, such projects have a very long payback cycle that may last up to 20–25 years. Moreover, the investments may be as high as 3 trillion rubles annually. As a result, transport and logistics suppliers alone cannot support such a large-scale initiative. Domestic logistics is currently going through all the stages from 1PL to 5PL, which places very high requirements on the multimodality of transport and logistics in physical infrastructure, software, and hardware. These processes encourage research cooperation between industries aimed at developing novel interoperable R&D solutions. Russian transport and logistics infrastructure depends heavily on the railway industry: its main operational task is to maintain passenger and cargo traffic, as well as to provide safety. Under the current sanctions, Russian railroads face the challenge of developing and scaling advanced scientific and technical reserves. Technological independence relies on end-to-end production technologies, e.g., artificial intelligence algorithms, digital twins, etc., which impose requirements on data interoperability. This article describes the potential that domestic railway enterprises have for improving commercialization of innovations and technology transfer. The authors used the theory of strategy and the methodology of strategizing developed by Professor V.L. Kvint to design several recommendations on how railroad companies may increase their economic motivation to overcome various barriers.

Research on Green Finance Supporting Green and Sustainable Development of Railway Enterprises

In the process of rapid industrialization and urbanization in China, there is a strong demand for energy, while carbon emissions have not yet reached their peak. As an important market-incentivized environmental policy tool, green finance plays an increasingly important role in the process of carbon neutrality. The railway is the backbone of the transportation system, and a complete green finance application model has not yet been formed in its green development process. This article focuses on the impact of green finance on railway enterprises, analyzes the challenges and necessity faced by the development of green finance in railway. It also explores the green and sustainable development methods of railway enterprises, analyzes the application of green financial tools in enterprises, and proposes exploration and expansion suggestions from the development path and mechanism of green finance in railway enterprises. The study has shown that the main sources of green funds for railway construction come from green loans and green bonds. The construction of a green transformation plan takes green funds as an important innovative financing method. In the railway industry, enterprises innovate and develop financial service supply side reforms through green insurance and green leasing, and apply carbon trading and related financial derivatives to obtain green development benefits. Carrying out green finance in the railway industry can optimize financing structure, broaden financing channels, reduce the overall financing costs, and guide funds to clean, science and technology and other key areas, which is of great significance to support the high-quality development and green upgrading of the railway enterprises.

Optimization of ticket pricing for high-speed railway considering full competitive environment

The rapid development of high-speed railways (HSR) worldwide has provided a fast, convenient, safe, and comfortable mode of transportation. It is also an important public transportation tool for green travel, contributing to the reduction of carbon emissions. HSR has a strong competitive advantage in long-distance passenger transportation, but it faces significant competition from the aviation industry. Airlines attract passengers with discounted fares and differentiated pricing strategies, apart from shorter travel times. Therefore, it is necessary for railway enterprises to enhance their competitiveness through differentiated pricing methods for HSR. In this study, we focus on optimizing a long-distance origin-destination (OD) pair and creating a competitive market environment by considering all operating trains and flights for the selected OD pair. We aim to improve the realism of the study by considering passengers’ fully rational travel choice behavior. To reduce the complexity of variables, passengers are grouped based on their expected departure time and income level. A mixed integer linear programing model is developed to address the problem, aiming to minimize overall travel costs for passengers while ensuring that the income of the railway enterprise does not fall below a specified value. By setting this specific value, the maximum revenue of HSR train tickets can be obtained.

A Study on a Solution for Standardization Work for the Sustainable Development of Railway Enterprises

As one of the most widely used modes of transportation worldwide, the standardization work of railways is of great significance for improving operational efficiency, enhancing service quality, and promoting sustainable development. Through research on railway enterprises, this paper proposes a standardization work solution applicable to railway enterprises of different sizes, which includes six steps. It is found that railway enterprises of different sizes can use the solution proposed in this study to carry out standardization work, but the results of different railway enterprises using this solution to carry out standardization work may be different, and the results of different units using this solution to carry out standardization work within the same railway enterprises are not comparable. Railway enterprises should strengthen cooperation and learn from each other’s advanced experience. Furthermore, the solution in this study can serve as a reference for different railway enterprises to carry out standardization work and contribute to the sustainable development of railway enterprises.

Organization of marketing pricing at a railway enterprise that affects the innovation potential

Organization of marketing pricing at a railway enterprise that affects the innovation potential

Mission of Samara State Transport University

Samara State Transport University (SamGUPS) is the largest transport university in the Volga Federal District, training specialists for the country’s railway transport and for many other areas of the national economy.The institution was founded in 1973 as the Kuibyshev Institute of Railway Transport Engineers, primarily to meet the need for highly qualified engineering staff of the Kuibyshev Railway, one of the largest railway enterprises of the USSR.In 1991, in connection with the renaming of the city of Kuibyshev and the return of its historical name Samara, the university was renamed Samara Institute of Railway Transport Engineers (SamIIT).Over the past period the higher education institution has consistently raised its academic status — first to the Academy, becoming Samara State Transport Academy, and in 2007 — winning the right to be called Samara State Transport University.The article presents the main goals and objectives of the university and the achieved results of the university development, tells about the interaction of Samara State University of Railway Transport with related branch and engineering universities in our country and abroad, tells about the interaction with transport, construction and infrastructure enterprises in the cities of the region.

Development of the sound barriers for speeding up the Joetsu Shinkansen

Considering speed increase in the future, noise prevention is a major issue for railway enterprises. In this paper we present an example of noise control measures for speeding up the Joetsu Shinkansen. We develop a new sound absorption panel to be attached to the inside of viaduct sound barriers and to use that in optimized combination with edge-shaped device where acoustical devices are attached to the top of sound barriers.

Pricing Analysis for Railway Multi-Ride Tickets: An Optimization Approach for Uncertain Demand within an Agreed Time Limit

A multi-ride ticket with a certain period of validity and maximum number of uses has been introduced into railway transport. The key to pricing the railway multi-ride ticket is determining the uncertain demand within an agreed time limit. Unfortunately, limited studies have focused on this pricing issue. Therefore, we focused on railway multi-ride ticket pricing optimization in two different scenarios: a single train with multiple stops and multiple trains with multiple stops. First, the expected coefficient and incentive coefficient were introduced to describe the decision-making process for multi-ride tickets and simulate the change in passengers’ travel behavior after purchasing multi-ride tickets. Then, passenger demand functions based on a normal distribution were developed to establish the pricing models with maximized revenue. Finally, we adopted improved particle swarm optimization (PSO) to solve the models. Two numerical cases were used to verify the models separately for two application scenarios. The results revealed that the multi-ride ticket pricing problem is not a simple summation of pricing for one-time travel of passengers. In the situation of a single train with multiple stops, the expected coefficient is positively related to the total income, whereas the incentive coefficient has limited influence on the optimal price and total revenue. Furthermore, a multi-ride ticket should allow the passenger to take trains eight times at most in 8 days at the price of CNY 4922 (abbreviated as 4922 (8, 8)) rather than 3785 (8, 6). Railway enterprises should cautiously limit the scope of trains available for multi-ride tickets in the case of multiple trains with multiple stops.

Deep Learning Based Method for Early Warning of Price Risk in Railroad Bulk Freight Transport with Consideration of Time Series of Comprehensive Impact Index

The aim in this study is to enhance the price competitiveness of medium- and long-haul railroad bulk cargoes in the transportation market. Efficiently triggering an early warning for railroad bulk freight price risk is crucial. This paper discusses relevant factors affecting the pricing of railway freight from four aspects, namely the macroeconomy, the transportation market, the freight owner, and the railway enterprise. We construct a comprehensive index system for generating an early warning of railroad bulk freight prices. Utilizing a collected data set of 20 factor indicators that affected prices from 2015 to 2017, we calculate a comprehensive price risk warning index using the integrated entropy weight and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. We propose a risk warning level classification method based on the k-means clustering method to determine five levels of price risk warning. Subsequently, we establish comprehensive index prediction methods for issuing price risk warnings based on the back propagation (BP) neural network and the deep learning long short-term memory (LSTM) network. We verify that the prediction performance of the deep learning LSTM network is significantly better than that of the BP neural network by combining all coal freight data from the Shanghai Railway Bureau for the period 2015 to 2017 as a case study. The proposed method can predict the level of freight price risk more accurately in the next phase, based on the status of the factor indicators, and be used to assist railway departments in developing a more reasonable freight price adjustment strategy to scientifically mitigate freight price risk.

Pricing for Refund Service Fee of High-Speed Railway: An Optimization Approach with Uncertain Demand

Compared to single ticket purchase behavior, the impact of ticket cancellation behavior on revenue is full of complexity. Due to the cancelled tickets will be resold with uncertain demand, ticket cancellation behaviors and ticket purchase behaviors are intertwined and influenced, composed of a dynamic and complex system in the presale period. How to charge for ticket cancellation behavior in the name of refund service fee to reduce losses as much as possible is an urgent problem for high-speed railway enterprises. However, there has been little research on this issue. Therefore, a pricing optimization approach for refund service fee based on negative binomial distribution was proposed in this article. Firstly, we proved that the probability of passengers arriving based on the accumulated ticket sales obeyed the negative binomial distribution, which was used to fit the uncertainty demand of passengers. Then, we categorized the passengers to build an optimization model with the objective of maximizing compensation for losses caused by ticket cancellation. A case study was implemented to show that the proportion of refund service fee to ticket price is generally higher than 50%. The refund service fee remains monotonously nondecreasing as the departure date approaches. It also indicated that the current charging standard for refund service fees was too low to offset the losses. In addition, passenger preferences and passenger flow have significant impacts on the dynamic pricing strategy for refund service fees.

Pollution of the hydrosphere with petroleum products at railway transport facilities

On railway transport, a large amount of water is used for production needs, respectively, domestic wastewater contaminated with petroleum products is formed.For water purifi cation in modern conditions, oil traps or oil traps are used. They are designed for cleaning ground, thawed, rainwater, water from washing rolling stock, washing components and parts before repair in electroplating workshops or sites, when washing and refueling batteries, fi lter regeneration, when purging and washing steam boilers, washing inspection ditches and washing overalls.As a result of man-made disasters on railway transport, there may be pollution of water bodies, as a result of which there is a violation of the integrity of ecological systems and the death of living organisms.To eliminate the consequences of pollution of water bodies, JSC “Russian Railways” uses mechanical, chemical and biological methods of water purifi cation. Additionally, it is advisable to use modern types of sorbents. The choice of a method for cleaning reservoirs depends on many factors, the most important of which are the volume and scale of pollution.A number of bacterial preparations have been created in Russia that are successfully used to clean water bodies and shorelines from oil pollution.Voronezh State University, with the cooperation of VEGA-eco LLC, is developing a biological product of the genus Acinetobacter (B-2838, B-5064 and B-3780), which is capable of refi ning oil.The drug “Devoroil” is used to clean oil-contaminated sites at railway enterprises. It includes an association of cells of hydrocarbon-oxidizing microorganisms and additives that activate the process of biodegradation of oil. The working time of the drug “Devoroil” is 2-3 months.Today, there are 25 known species of bacteria and fungi that decompose hydrocarbons.These organisms work in a complex and participate in the biochemical carbon cycle in nature, being powerful tools in the fi eld of environmental microbiology.As a result of the development of scientifi c and technological progress, it becomes possible to create new technologies in the fi ght against man–made disasters.

Research on Choice Preference of Parallel Trains for High-Speed Rail Heterogeneous Passengers

The passenger capacity utilization of parallel trains on China’s high-speed railway (HSR) varies greatly, which seriously affects the revenue and passenger service quality of railroad companies. One of the key factors contributing to this issue is the uniformity of fares. To address this, China’s railway enterprises are implementing differential pricing reforms for parallel trains. This paper presents a two-step method that combines latent class analysis (LCA) and random parameter logit (RPL) models to estimate the preferences of diverse passengers for parallel trains and quantify them using willingness to pay. To illustrate this, we conducted revealed preference and stated preference questionnaire surveys at Nanning East Railway Station, China, focusing on the Nanning-Guangzhou HSR route. These surveys gathered data on passengers’ personal and travel attributes. LCA was carried out according to passenger attributes, and passengers were divided into three categories according to the goodness-of-fit measures. Through the questionnaire data, the travel time and departure time period of each category of the passenger were converted into costs, and the absolute value of each influencing factor of passengers for parallel trains was obtained. Considering the limited rational choice behavior of passengers, the perceived value of each influencing factor of passengers on parallel trains was calculated through prospect theory. Finally, an RPL model for parallel train choice of heterogeneous passengers was constructed, and the parameters of each category of the passenger were estimated based on the absolute value and perceived value of the influencing factors.

Can firm R&D benefit from digital technologies? Evidence from Chinese high-speed rail industry

PurposeAs an emerging socio-technical paradigm, high-speed railways profoundly change individuals' lifestyle and allow for the shift toward a green transportation. Digital technologies open an opportunity window for the development of enterprises. This study aims to clarify the impact of firm digitalization on the innovation efficiency of the Chinese high-speed rail industry. In addition, human capital is the important non-physical capital of enterprises. The authors also elucidate the moderating role of human capital on the above relationship.Design/methodology/approachBased on the data of Chinese high-speed railway listed companies from 2015 to 2021, this study explores the impact of digital transformation on the innovation efficiency, and further clarifies the boundary role of human capital with two-way fixed effect regression models.FindingsThe empirical results indicate that digital transformation has a positive impact on the innovation efficiency of the Chinese high-speed railway enterprises. Furthermore, human capital significantly enhances the above relationship. In addition, digital transformation fosters the innovation efficiency of small- and medium-sized enterprises and private-owned enterprises, but the correlation coefficients between digital transformation and the innovation efficiency of large enterprises and state-owned enterprises are not significant.Originality/valueThis is one of the earliest studies to explore how digital technologies shape R&D activities. From the perspective of relative efficiency, this study evaluates the effectiveness of digital transformation and provides empirical evidence for the formulation and implementation of corporate digital strategies. Moreover, this study links human capital with digital transformation and identifies condition factors that affect the effectiveness of digital transformation, thereby supplementing existing knowledge.

Railways of India. An important stage of modernization is completed – unification of track width

India, the Republic of India is a country of one of the world’s oldest civilizations, the largest state in the world by population — 1.42 billion people (end of 2022), occupying an area of over 3 million square kilometers. India, which has accelerated the pace of its socio-economic development in recent decades, is playing an increasingly important role in the international arena every year, including as one of the BRICS organizers. The state railways of India are managed by the Ministry of Railways of India represented by Indian Railways (99 % of the country’s railway network) and are, despite the dominance of motor transport, remain one of the main modes of transport. During the year, the railways of India transport more than 8 billion passengers (2nd place in the world after Japan), the staff of the railways of India will amount to 1.2 million people (the 7th employer in the world). Railway transport in India is developing intensively, in recent years, work has been intensified on the organization of high–speed traffi c on a number of lines of existing railways, the fi rst high-speed railway line Mumbai — Ahmedabad is being built with a normal gauge of 1435 mm with a length of 508 km, designed for a maximum train speed of 350 km/h. The authors of the article have repeatedly visited India, visited various railway enterprises, railway educational institutions — universities and institutes, met with industry leaders at the Ministry of Railways of India, traveled along the country’s railways along a number of routes with a total length of about six thousand km.

Influence of financing water protection measures in the field of transport on water quality of water bodies

Transport is a major water consumer and source of environmental pollution, including water resources. In order to preserve and improve water quality in water bodies at industrial and transport enterprises, including railway enterprises, water protection measures entailing permanent signifi cant funding are required. The study is aimed to develop a methodology for determining dependence of water quality of the water body on the real financing of water protection measures; theoretical justifi cation of the choice of water quality of the water body from the quality of wastewater (WW) of water users, discharging them into the water body and amount of financing of water protection measures. The solution of the task of determining the best water quality in a water body under limited fi nancing of water protection measures and rational distribution of fi nancial resources between water users, including transport infrastructure objects, is proposed. Financing of water protection measures in Russia is less than abroad and has been decreasing over the last three decades. The limits for pollutant concentrations in pollutant discharges into water bodies and water disposal systems in Russia are often set very strict, sometimes more stringent than those for drinking water, which leads to unjustifi ed spending of investment costs. It is pointed out that at present in Russia market relations in the field of nature and, in particular, water use have not been formed. The basic diffi culties at realization of these relations in our country are designated. When using the proposed methodology, the rational quality of water resources of water users by limiting pollutants and the rational distribution of funds for water protection measures among water users within the limited amount of financing are determined. The extent to which water quality in a water body changes is also determined. The possibility of practical application of the proposed methodology is considered.

A System Optimization Approach for Trains’ Operation Plan with a Time Flexible Pricing Strategy for High-Speed Rail Corridors

Optimizing the train plan for high-speed rail systems should consider both the passengers’ demands and enterprise’s benefits. The choice of the departure time period is the most important factor affecting the passenger demand distribution. In this paper, the optimization problem of a train operation plan based on time period preference is studied for a high-speed rail corridor. First, according to the travel process of the passengers, the extended service network for a high-speed rail system is established. The main factors that influence the passengers’ travel choices are analyzed, and the departure time period preference, stop time and flexible pricing strategy based on the time period preference are put forward. The generalized travel cost function, including the convenience, ticket fare and stop time costs, is constructed, and a two-level programming model is established based on the function. The upper-level planning model is formulated as a mixed 0–1 programming problem that aims at maximizing the revenue of the railway enterprise. It is mainly constrained by passenger travel demand and solved by improved genetic algorithms. The lower-level model is a user equilibrium (UE) model. The Frank–Wolfe algorithm is used to allocate multiple groups of OD (origin and destination) passenger flows to each train so that the generalized travel expenses of all the passengers with the same OD are minimized and equal. Finally, the train operation plan is solved based on the Lan-xi (Lanzhou–Xi’an) high-speed rail data, and the validity of both the model and algorithm is verified.

Modeling and Heuristically Solving Group Train Operation Scheduling for Heavy-Haul Railway Transportation

In light of the improvements to the capacity and timeliness of heavy-haul railway transportation that can be organized through group trains originating at a technical station, we address a group train operation scheduling problem with freight demand importance via a newly proposed mixed integer programming model and a simulated annealing algorithm. The optimization objective of the mixed integer programming model is to minimize the weighted sum of the transportation cost and the total cargo travel time under the condition of matching freight supply and demand within the optimization period. The main constraints are extracted from the supply and demand relations, the cargo delivery time commitment, the maintenance time, and the number of locomotives. A simulated annealing algorithm was constructed to generate the grouping scheme, the stopping scheme and the running schedule of group trains. A numerical experiment based on a real heavy-haul railway configuration was employed to verify the efficacy of the proposed model and heuristics algorithm. The results show that the proposed methodology can achieve high-quality solutions. The case results reveal that the freight volume increased by 2.03%, the departure cost decreased by CNY 337,000, the transportation cost which results from the difference in the supply and demand matching increased by CNY 27,764, and the total cargo travel time decreased by 40.9%, indicating that group train operation can create benefits for both railway enterprises and customers.

Being good or being known: International reputation of high-speed railway enterprises

Being good or being known: International reputation of high-speed railway enterprises

Performance analysis of protective functions of forest plantations of the Lviv railway line (Ukraine)

To reduce the harmful impact of railway transport on the environment and ensure environmental safety, railway enterprises develop and implement a wide range of environmentally effective measures annually. First, it concerns the protection of the territories adjacent to the railroad tracks from various types of pollution. These forest plantations are created for the protection of the railroad track from adverse climatic factors, as well as for the reduction of the railway's impact on the surrounding territories - to reduce the various types of pollution, and to protect from adverse aerodynamic effects. In order to investigate the protective properties of forest plantations, we presented their detailed characteristics on the section of the Lviv-Sambir railway line. This is the busiest railway line in terms of the number of trains, which connects the eastern industrial regions of Ukraine with the western part of the European Union. It transports the largest volumes of cargo, including hazardous ones. The effect of afforestation on reducing the heavy metals content in the soil of the impact area of the railway was determined experimentally. In all samples, the concentrations of heavy metals in the soil do not exceed the maximum permissible concentration standards: Cu-100, Zn-100, Pb-30, Cd-3.0 mg/kg3. However, there is a decrease in the heavy metals' content with the distance from the track. Differences in ingredient pollution depending on the placement of plantations were established. Thus, the concentration of heavy metals is higher on average from 2.6% to 29.9% in the areas on the windward side compared to the areas on the opposite leeward side. Therefore, forest vegetation intensively retains heavy metals and performs the function of a filter for the natural environment. Research has established a reduction in the parametric impact of railway transport. The level of protective plantings' effect on noise reduction along railway lines was determined. The highest noise levels of electric trains were determined at 95-94 dBA near the track, at a distance of 50-100 m the noise level remained high at 90-82 dBA, and at a distance of 150-200 m the noise ranged from 86 to 65 dBA; the highest noise levels of passenger trains were determined near the track of 92-91 dBA; freight trains ‒ near the track 93-92 dBA. The dependence of the noise level on the structure and condition of the plantations was determined. Thus, it can be stated that the existing forest plantations perform their phytomelioration functions and reduce the negative ingredient and parametric impact of railway transport. In order to protect the territories adjacent to the railway from pollution successfully, it is necessary to monitor transport sections constantly to ensure the sustainable development of the railway industry.