Transportation and Information Technologies in Russia

Technological model for organizing efficient maintenance of signaling and interlocking devices on low‑intensity railway sections

2026-03-17T04:37:26+07:00

Background. The relevance of the study is due to the need to optimize operating costs for the maintenance of signaling and interlocking devices on low-intensity railway sections. Such sections, characterized by freight intensity of less than 15 million tkm/km per year, constitute a significant part of the network of the Russian Federation. However, traditional scheduled preventive maintenance systems, designed for intensively operated lines, lead to unjustifiably high unit costs, a mismatch between the frequency of maintenance and the actual aging rate of equipment, and an excessive number of personnel trips. Current trends require a transition to condition-based maintenance using predictive analytics methods. The lack of comprehensive technological models adapted to the conditions of low-intensity sections determines the need to develop a scientifically based approach that ensures a balance between economic efficiency and the required level of traffic safety.

Purpose. Development of a technological model for organizing efficient maintenance of signaling and interlocking devices on low-intensity railway sections, based on the principles of failure prediction and rational resource allocation, allowing to reduce operating costs while maintaining or improving reliability and traffic safety.

Materials and methods. The research is based on a statistical analysis of 2,348 records of failures of signaling and interlocking devices on low-intensity sections for the period 2020–2023, classified by device types and nature of malfunctions. To describe the patterns of failure occurrence, a modified Weibull distribution was applied, taking into account seasonal fluctuations and operation intensity. Nonlinear and dynamic optimization methods were used to determine rational maintenance intervals. A simulation model of the maintenance system was developed, and 2,000 runs were performed for various scenarios (confidence probability 95%). Economic efficiency was assessed using discounted cash flow methods (NPV, IRR, payback period). The initial data for the calculations correspond to a typical low-intensity section 50 km long with a specific list of devices and work costs.

Results. The proposed technological model, including a differentiated approach to maintenance by criticality classes and an algorithm for optimizing maintenance intervals, allows to increase the average maintenance interval by 57.8% (from 90 to 142 days), reduce the number of unscheduled failures by 38.9%, and decrease the average recovery time by 45.2% (according to calculation results). The system availability factor can increase from 0.980 to 0.991, which corresponds to a reduction in downtime by 55%. Annual operating costs can be reduced by 20.5% (2.7 million rubles for a 50 km section) with an estimated payback period for capital investments of 1.6 years. The developed models and recommendations can be replicated on other low-intensity railway sections.

EDN: EJPKFZ

Social aspects of assessing the effectiveness of gross‑contract transportation for commuter bus routes in urban agglomerations

2026-03-17T04:37:26+07:00

Background. This article examines the social transition to gross-contract transportation for commuter bus routes in large metropolitan areas such as Krasnodar. It is shown that the key factors for commuter passengers include inconvenience, regularity, and accessibility of transport during peak hours. Based on the calculations for route 186b (Lazurny settlement – city center), a detailed passenger flow analysis was conducted, identifying its high unevenness (coefficient 2.75), and calculating key performance indicators.

It was established that random issues such as schedule failures and insufficient comfort can be addressed through the use of a gross contract, which sets strict requirements for rolling stock and service frequency.
The objective of this study is to assess social effectiveness and justify the transition to gross contracts using suburban bus routes in Krasnodar's metropolitan areas as an example. The study aims to identify key social requirements for passengers and evaluate gross models of transport service quality.

Methodology. Systems analysis, naturalistic research and instrumental methods, analytical and computational methods, and questionnaires were used.

Results. High social innovation and passenger flow dynamics typical for a suburban-urban route were identified. Significant unevenness in load across routes and times of day was revealed, confirmed by a high unevenness coefficient (2.75). Current capacity utilization rates (coefficient ~0.41) were found to indicate potential for optimizing rolling stock distribution. Key issues were confirmed through questionnaires: comfort and schedule delays, which can be regulated under a gross contract.

Practical implications. The study's results can be used to support transport management in commercial agglomerations to justify the transition of suburban and standard routes to gross contracts. A study of electronic tools for improving quality of life, reducing social isolation, improving the environment, and managing population mobility through transport service reform.

EDN: GFCYHT

Automation of operations with brake shoes to improve the quality of station work

2026-03-17T04:37:26+07:00

Background. The article substantiates the need to improve the operation of railway stations in order to increase the efficiency of cargo delivery using rail transport. It explores possible ways to improve the existing racks used to store brake shoes within the railway station, which used to secure railway rolling stock on the station's tracks. The article analyzes the system of accounting and storage of brake shoes. The current conditions highlight the need to find effective solutions for the existing technology of storing brake shoes, which has several drawbacks. The article analyzes the safety of train traffic and shunting operations. It describes the main operations performed when working with racks and brake shoes. The article also provides a detailed description of the proposed technology for upgrading racks, which will help ensure that railway rolling stock is properly secured on the railway station tracks, reduce the number of unauthorized departures of rolling stock, "brake-on" movements, and subsequent derailments, as well as the theft of brake shoes.

Purpose. Automation of operations with brake shoes to improve the quality of the station's work.

Methodology. The paper analyzes technological operations with brake shoes, develops an automated rack design, and conducts a SWOT analysis of the project.

Results. An upgraded rack design for storing brake shoes has been developed, equipped with an RFID reader, an electromagnetic lock, and end sensors that indicate the presence or absence of a shoe in the rack. A remote monitoring system has been proposed, allowing for real-time monitoring of the shoe's condition.

Practical implications. Train and maneuvering operations at railway stations.

EDN: DSIJNQ

Car engine diagnostics using a vacuum gauge

2026-03-17T04:37:26+07:00

Background. Various methods are widely used in diagnosing the technical condition of automotive engines, but most require highly skilled personnel and sophisticated equipment. Vacuum diagnostics, based on measuring the vacuum in the intake manifold, is an accessible and effective way to assess the condition of the engine and auxiliary systems.

Purpose. To explore the potential of using a mechanical vacuum gauge to diagnose the technical condition of the cylinder-piston group, valve timing systems, valves, and other engine components of various designs.

Materials and methods. A mechanical pointer vacuum gauge was used in this study to measure the vacuum at various points in the vacuum systems of gasoline and diesel engines. The dynamics of the instrument readings were analyzed, faults were modeled, and a comparative analysis was conducted with compression diagnostics, computer diagnostics, and oscillographic methods.

Results. The method demonstrated high information yield for identifying air leaks, valve malfunctions, valve timing issues, ignition problems, and other faults. Practical recommendations for interpreting vacuum gauge readings and a table of reference vacuum values for various engine types are provided.

EDN: QNHITF

Study of the impact of integrating the Watt linkage as a stabilizer in an agricultural tractor‑vehicle

2026-03-17T04:37:26+07:00

Background. The article is devoted to the study of the dynamics of the Watt mechanism as a suspension stabilization device for a wheeled vehicle based on an experimental model of a passenger mobile small-sized vehicle NAMI-2339. The key problem in the design of independent suspensions is the minimization of undesirable parasitic movements of the wheel in the horizontal plane (track change, convergence, longitudinal displacement) during its vertical course. As an alternative, a kinematic scheme based on the Watt parallelogram mechanism (known as a mechanism for reproducing approximately rectilinear motion) is proposed.

Purpose. To obtain results under the influence of emerging forces and efforts as a result of suspension operation.

Methodology. Studies of the movement of the Watt mechanism were conducted in the SolidWorks Motion environment.

Results. The dependences of the displacement of the center of mass of the main elements of the mechanism and their numerical parameters under the influence of applied forces are obtained.

Practical implications. The results can be used in the development and production of wheeled vehicles.

EDN: AICXYP

Development of an algorithm for a decision support system for planning and managing container transportation in a multimodal communication

2026-03-17T04:37:26+07:00

Background. The article provides an overview of the current state of the railway container transportation market, analyzes statistical data on the dynamics of the railway container transportation market by type of transportation and individual transport and logistics companies. An overview of the work aimed at improving the organization of transportation of container products by rail has been made. The review of digital systems currently used on the network of Russian Railways and transport and logistics companies in the implementation of container transportation is carried out, their functionality and capabilities are considered. The key tasks aimed at ensuring the reliability of container product delivery have been identified. A decision support system is proposed that operates based on an assessment of the workload of transport and terminal infrastructures and allows choosing the optimal route for container delivery. Conclusions are drawn about the prospect of implementing the system algorithm as a software product as a digital service suitable for use in transport and logistics companies.

Purpose. Development of an algorithm for a decision support system for planning and managing container transportation in multimodal transport.

Methodology. The article uses an analysis of the current situation in the field of container transportation, mathematical modeling of the objective function of container traffic management, and an algorithm for a decision support system in delivery management.

Results. The analysis of container transportation statistics has been performed, and an algorithm for a decision support system for container traffic management has been developed.

Practical implications. It is advisable to apply the obtained results in the system of automobile and railway container transportation, in the work of forwarding, operator and transport and logistics companies.

EDN: DWQXTH

Fuzzy system for determining an objective solution for the transportation of petroleum products

2026-03-17T04:37:26+07:00

Background. The article discusses the issue of determining the rational option for delivering cargo M_T from point A⁰ to point B⁰ with maximum satisfaction of the k_j system of criteria. Essentially, the members of the expert council are asked to find a single measure on the set M_j, i.e., to assign a weight value λ_j to each M_j of a single selected «standard» proposed by the decision-making system. The calculated M_ji correspond to Ц_ji with an accuracy of less than 0.1%. This significantly simplifies the task of the expert council and increases the objectivity of the k_j assessments, increases the validity and objectivity of choosing the most rational cargo delivery option.

In the field of the expert council, an intuitive approach is adopted, while using the proposed mathematical apparatus, a quantitative approach is adopted.

Purpose. To develop and test a mathematical model based on fuzzy sets that allows formalizing the decision-making process when selecting a delivery route for petroleum products.

Materials and methods. The theoretical and methodological basis of the study was the system analysis and modeling, fuzzy set theory, statistical analysis and correlation-regression analysis, as well as scientific and engineering works for various types of expert assessments, used to determine the values of criteria when comparing the considered options for the delivery of petroleum products.

Result. The mathematical apparatus is aimed at multi-criteria analysis with a mathematical solution of the problem and is a tool for selecting the best schemes, including hypothetical (planned) ones, in particular, using logistics facilities by mode of transport, according to the selected logistics polygons with competing routes and varying modes of transport.

EDN: QDMXJM

Research on the architecture of a low-code platform for hybrid intelligence with the implementation of the Kanban method for decision support in transportation management

2026-03-17T04:37:26+07:00

Background. The article examines the problem of insufficient functionality of existing low-code platforms in terms of decision support for freight transportation management. It is shown that the growth in freight traffic volume in the Russian Federation (by 5.5% in 2024), coupled with an increase in the share of short-haul routes and an acute personnel shortage (a deficit of about 1 million specialists), creates a need for new approaches to the automation of dispatching management. It has been established that modern low-code platforms are primarily focused on accounting and registration functions and do not integrate optimization algorithms with visualization tools, while Kanban boards, used in isolation, do not provide a closed-loop learning system based on expert decisions.

Purpose. Development and research of the architecture of a low-code platform with hybrid intelligence that integrates Kanban boards for visualizing transportation statuses and supporting dispatcher decision-making.

Materials and methods. The study employed a systems analysis approach to identify functional gaps in existing solutions. The architecture was designed using a modular approach and the BPMN 2.0 business process modeling notation. A case study method involving a regional transport company was used to verify the proposed solutions.

Results. This article proposes a three-layer architecture that includes a low-code configuration layer (a Kanban board with WIP limits, a visual route editor), a hybrid intelligence layer (an ML optimization module, an LLM explanation generation module, a decision orchestrator, a simulation modeling module), and a data and integration layer.

EDN: LNOOIG

Predictive maintenance of electric drives based on IIoT and Random Forest

2026-03-17T04:37:26+07:00

Background. With the growing fleet of electric vehicles and increasing demands for their reliability, the task of transitioning from scheduled maintenance to predictive maintenance based on actual component condition becomes urgent. The electric powertrain is a critical component whose failure leads to significant economic losses and reduced safety. The use of Industrial Internet of Things (IIoT) technologies enables continuous real-time monitoring of electric drive parameters, while machine learning methods allow early detection of failure precursors.

Purpose. Development and experimental validation of a method for predictive maintenance of automotive electric drives based on IIoT data and the Random Forest algorithm, ensuring timely detection of developing defects.

Materials and methods. The study is based on data obtained during 24 months of operation of a fleet of 32 commercial electric vehicles equipped with an additional IIoT platform featuring high-frequency vibration, temperature, and current sensors. Digital filtering, spectral, and wavelet analysis methods were applied to extract diagnostic features. The Random Forest algorithm with hyperparameter optimization using GridSearchCV was used for electric drive state classification. Performance evaluation was conducted on a stratified test set using precision, recall, F1-score, and ROC-AUC metrics.

Results. The developed Random Forest model demonstrated high effectiveness in detecting pre-failure conditions: the F1-score for the "developing defect" class was 0.876 with a recall of 0.861. Comparative analysis showed the advantage of Random Forest over XGBoost, SVM, and 1D CNN in terms of accuracy, interpretability, and noise robustness. The model was found to statistically significantly better detect bearing defects compared to interturn short circuits, which is consistent with the physics of the processes. Feature importance analysis was performed, identifying key indicators of electric drive component degradation.

EDN: OCSHYU