The journal TRANSPORT publishes articles in the fields of: transport policy; fundamentals of the transport system; technology for carrying passengers and freight using road, railway, inland waterways, sea and air transport; technology for multimodal transportation and logistics; loading technology; roads, railways; airports, ports; traffic safety and environment protection; design, manufacture and exploitation of motor vehicles; pipeline transport; transport energetics; fuels, lubricants and maintenance materials; teamwork of customs and transport; transport information technologies; transport economics and management; transport standards; transport educology and history, etc. More information ...
Copyright © 2021 The Author(s). Published by Vilnius Gediminas Technical University. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Novel hybrid model for addressing uncertainty of the road safety composite indicator: integration of DEA and weighted GRA
Creating a composite indicator is a popular concept in evaluating and comparing road safety of territories. While many other approaches are used, most current interest is on Data Envelopment Analysis (DEA) for measuring the relative performance in efficiency terms. Usefulness of DEA, which measure performance in efficiency terms, has already been proven. However, the indicators commonly used to construct a road safety composite index are not always precise and accurate (particularly safety performance indicators), and the results obtained from this type of data does not seem to be solid. So, the main aim of this paper is to represent the novel methodology to effectively evaluate the state of road safety and create a reliable composite index of the selected entities when imprecise data are involved and, to produce reliable composite index under uncertain environment. DEA, the weighting method Fan–Ma, and the Grey Relational Analysis (GRA) were integrated into hybrid methodology to obtain a more realistic and relevant picture of road safety. Applying this hybrid methodology, peculiarity of DEA is retained, scores are further differentiated, and entities are ranked and classified according to the road safety level. A case study was conducted to evaluate and rank municipalities, determine road safety classes and benchmark the territories under study. Results were verified indicating the robustness and effectiveness of the proposed methodology and its superiority to basic DEA as regards the territory ranking. First published online 3 February 2026
Copyright (c) 2025 The Author(s). Published by Vilnius Gediminas Technical University. http://creativecommons.org/licenses/by/4.0
Location of urban logistics distribution centers considering cargo transportation services of a public transportation system
Urban logistics distribution accounts for a large proportion of CO2 emissions generated by urban transportation. Reducing CO2 emissions in the process of logistics distribution is one of the urgent urban problems to be solved. This article investigates the location of urban logistics distribution centers considering cargo transportation services of a public transportation system. Considering one or several bus lines for representing a public transportation system, several collaborative distribution scenarios are studied, and 2 mixed integer linear programming models are established to explore the impact of the public transportation system on the location of distribution centers in urban logistics. Numerical experiments show the influence of different bus lines on the location of distribution centers, collaborative distribution and truck carbon emissions in Dalian (China). In any case, the possibility of establishing distribution centers in blocks 5 and 42 of Dalian is very high. When bus lines are used, the highest bus line utilization can reach 47.83%, and the CO2 emission can be reduced by up to 36.3%. In terms of different bus lines, line 2002 is more suitable to participate in the collaborative distribution in Dalian compared with other bus lines. First published online 2 February 2026
Extended security control and delay propagation in air cargo transport operations: implications for supply chain continuity
Prior research on security controls in air cargo terminals has primarily focused on protecting passengers, crews, and airport infrastructure, while largely overlooking the maintenance of supply chain continuity. The present study addresses this gap by analysing how the configuration, spatial placement, and scheduling of screening procedures affect the stability of cargo flows, as well as the incidence and propagation of delays in air freight operations. Evidence was collected at 2 terminals – a regional facility in southern Poland and a large international terminal in southern Europe, which enabled a comparative assessment that accounts for organisational and structural differences. The analysis mapped screening procedures onto the operational timeline of cargo-handling. Standard screening consisted of radiographic inspection of palletised consignments using an X-ray system. A negative result triggered an extended screening path comprising, in sequence, canine inspection, chemical screening using reactive swabs, and manual inspection of the load unit after opening by a qualified specialist. The total delay was computed as the sum of the times associated with the additional screening steps and the waiting time for the substitute uplift. Findings for 2022–2024 indicate pronounced differences between terminals in both the scale and effectiveness of controls. At the regional terminal, 3…6% of shipments were routed to extended screening, the average duration of additional actions was 1…2 h, and the final delay was 14…20 h. At the international terminal, the corresponding values were 12…15%, 5…7 h, and 84…95 h. The most significant delays were generated by procedures requiring external specialists, such as crate-opening technicians, and by the organisation of replacement transport. Where specialist support was provided periodically, the waiting time for inspection could reach up to 7 days, whereas smaller facilities operated with near-immediate response times. Based on these results, several operational improvements are indicated. Recommended actions include maintaining specialists on-call, issuing immediate notifications of adverse X-ray outcomes to planning teams, and selectively automating repetitive steps. Implementing these measures is expected to reduce inspection-related delays, improve on-time delivery performance, and enhance the resilience of air cargo supply chains. First published online 23 January 2026
Logistics operations management in the Industry 4.0 era: a case study for transition of an automotive company′s operations to fourth-party logistics structure
In recent years, the understanding of minimum inventory and customer satisfaction in the flow of goods and services from manufacturers to end-users is of great importance among the factors that make businesses more interested in outsourcing logistics activities. Additionally, technological transformation and customer requests for complicated technology and services caused the appearance of new circumstances, which is progressively altering the industry. In this regard, choosing, managing and coordinating between multiple vendors become very difficult and time consuming so, companies outsource more functions while supply chain operations getting more complex. Companies generally preferred 3PL providers for their logistics functions including packaging design and management of company-owned assets. On the other hand, with technological transformation in logistic sector, businesses are looking to outsource 4PL more than ever. 4PL system transitions are difficult processes since it requires comprehensive system integration and should be well understood by the company′s supply chain team. Today, although the importance of 4PL systems is more understood and this structure is becoming more widespread, many companies still face similar adaptation problems. From this point of view, it is believed that this study creates important insights into the business world. In this study, the transition process of an automotive company is examined which successfully completed after a 5-month project period. As a detailed case study, the Transportation Management Module (TTM) is selected since the whole transition process was very comprehensive and included many dimensions. Study revealed that adaptation of the new system, developed by the partnership of the automotive company and 4PL company, provided several benefits. In this sense, with the transition of Transportation Management (TM), TTM is reduced by 2 days, almost 10% savings are reported in the whole company and only in the Turkey branch, 243311 € cost saving is achieved in the 1st year. The study proves that focusing on the core business via outsourcing supply chain activities not only increases efficiency in the selected automotive company but also increases supply chain quality as well. First published online 22 January 2026
Multi-bus-line joint operation strategy of optimizing bus speed and intersection signal priority to minimize passengers waiting time
The rapid increase in the number of vehicles reduces the efficiency of transportation networks in modern big cities. Thus, minimizing passengers waiting time by bus has become an inevitable approach. Through intelligent bus systems and Dedicated Bus Lanes (DBLs), jointly optimizing bus speed and intersection signal priority has become a feasible research objective for multi-bus-lines. Moreover, the length of Beijing (China) DBLs will be 1020 km in 2022. Considering the requirements of the Beijing Bus Group, a problem model is formulated, including multi-bus-lines, time-varying passenger flow, bus-speed-control only on DBLs, and intersection signal control. In this study, the real-time framework of the multi-bus-line joint operation strategy with the Transformable Salp Swarm Algorithm (TSSA) is proposed. Moreover, the small optimization interval effectively reduces the impact of bus-speed-control inaccuracy and the errors between the joint optimization scheme and actual operation states. In the real-time framework, only the speed of the bus traveling on DBLs could be guided in the form of real-number speed, and this bus-speed scheme is safe. Additionally, the strategy could compensate for the travel time in the non-priority direction after buses pass through intersections, and this is effective to avoid traffic congestion. As the online optimization algorithm, TSSA simulates the grouping activity of salp swarms. Based on actual data from Beijing Bus Group, 6 test problems are constructed, and the joint operation strategy outperforms others. First published online 20 January 2026
Modelling solutions for cost optimization in multimodal transports considering the operational risk variables
The general risk assessment usually has the potential of setting a viable ground for pursuing a complex mathematical model based on an objective function, defined by several variables and constraints, which can be further applied for the specific analysis of multimodal transport. In order to assess the operational risks in multimodal transports, the authors have formulated an objective function with the aim of minimizes the sum of total cost of transportation on route components depending on the risk variables, respectively for road, maritime and railway subsystems of multimodal transport, in different combinatorial perspectives. The main objective of this study is to provide a method to value the overall risk assessment based on the defined objective function, considering both the variables that may influence the cost effectiveness and the relevant probabilities for each route component of multimodal transport. In this perspective, the authors have sought to provide practical solutions for decision-making process in multimodal routing, to optimize the costs on different routes and to contribute for decision-making process in routing and transports mode selection. The main contribution is residing from the novelty of decision-making process approach, considering the risk variables in different combination, facile to be applied professional in multimodal transportation in routing process, when risks are to be considered as significant for process reliability. First published online 19 January 2026
Co-governance of online car-hailing operation based on passenger feedback
The illegal operation of online car drivers is a recurring issue that has garnered significant societal attention. The literature has investigated this problem primarily from the perspectives of the government, platforms, and drivers, while the mechanisms for co-governance among different stakeholders in addressing illegal online car-hailing operations have received limited focus. Additionally, the role of passengers in the online car-hailing process has not been sufficiently explored, leading to a lack of systematic research conclusions and inherent limitations. To analyse the evolutionary equilibrium strategies of participants under various scenarios and their influencing factors, a tripartite evolutionary game model involving passengers, drivers, and online car-hailing platforms was constructed. The decision-making behaviours of these stakeholders were examined through numerical simulation. The results indicate that by strengthening investigations and addressing illegal behaviours, online car-hailing platforms can significantly reduce the likelihood of drivers′ illegal operations. Furthermore, increasing the amount of guarantee deposits can increase drivers′ respect for regulations. Additionally, improving passenger satisfaction can be achieved by increasing compensation for participation in co-governance and increasing promotional rewards from platforms, thereby enhancing service quality. Strengthened supervision strategies not only boost platforms′ social reputation and management efficiency but also create positive incentives for strict supervision through penalty income. This study provides a theoretical foundation for optimizing the supervision of the online car-hailing industry, emphasizing the critical roles of strict supervision, positive incentives, and public participation in elevating service standards. The findings enrich the theoretical understanding of online car-hailing market supervision and offer innovative co-governance strategies aimed at fostering the healthy development of the online car-hailing market.
Assessing sustainability in BRI railway projects with a novel integrated fuzzy methodology
China′s Belt and Road Initiative (BRI) and South–South cooperation have received universal concern over sovereignty and debt issue, despite their goal to promote development. In Africa, the rapid expansion of Chinese-funded railway projects has overtaken the development of systematic methods for evaluating sustainability, producing a serious gap in decision-making. To address this challenge, this study proposes an integrated methodological approach, i.e., Delphi, PIvot Pairwise RElative Criteria Importance Assessment (PIPRECIA), Logarithmic Percentage Change-Driven Objective Weighting (LOPCOW), and Evaluation Based on Distance from Average Solution (EDAS) methods within the p, q Rung Orthopair Fuzzy Sets (p, q ROFSs) to assess sustainability performance under high uncertainty. The findings indicate that trade facilitation, job creation, debt sustainability, accessibility and connectivity, and safety and security are the most significant criteria for sustainability. Among the projects assessed, the Nairobi – Mombasa Standard Gauge Railway (SGR) project exhibits greatest sustainability performance, followed by the Addis Ababa – Djibouti railway while others indicated weakened outcomes because of restricted freight integration. These findings recommend that future projects should prioritize powerful trade and freight connections, guarantee employment creation and skills transfer, and implementing financing models that safeguard debt sustainability. In doing so, policymakers, managers, and planners can reinforce regional integration, improve the long-term socio-economic advantages, and obtain the operational and financial viability of extensive railway investments in Africa.
p, q rung orthopair fuzzy sets (p, q ROFSs)
Tourists′ local buses ridership and pandemic resilience: a smart card data analysis in Southern Catalonia
The COVID-19 pandemic′s harmful effects have varied across economic sectors and been particularly adverse for the transport and tourism sectors. This article analyses the pandemic′s impact on tourists′ use of public transport since 2020, including its patterns of change and general decline, using data from more than 40000 smart card holders considered to be summertime users during the peak tourist season in Camp de Tarragona (Catalonia, Spain). 3 model-based clustering analyses of pre-pandemic data from 2019 were performed and used to classify data generated since the pandemic began in 2020. The 1st model included variables of each smart card′s volume of activity, the 2nd model analysed the concentration or spatial dispersion of validated uses of each card, and the 3rd model examined the temporal dimension of the use of smart cards depending on the defined objective. Among the major findings, the number of journeys plunged by 92% in summer 2020 – that is, by far more than throughout the year (64%), which suggests a higher loss of travellers linked with tourism activities (e.g., tourists, 2nd-residence owners, and workers in the tourism sector). Regarding the spatial dimension, patterns with minor reductions related to trips taken within cities (45%) or between major cities (78%). By contrast, travellers with sprawled patterns fell the use by 93%. Last, profiles obtained from variables of a temporary nature presented similar percentages of losses; the most significant losses were for use distributed throughout the day (91.81%) and throughout the night (90.12%). This article provides valuable insights into the pandemic′s varied effects on the use of public transport during peak season at a tourist destination, insights that could inform policies and actions to ensure a more robust response to future crises.
An evaluation study on immigrants′ transport system adaptation behaviour: Turkey example
Global migration patterns have led to significant population shifts, particularly in regions such as Turkey, which has experienced a substantial influx of immigrants due to political crises, economic instability, and armed conflicts. This study examines the adaptation behaviour of immigrants to Turkey′s transport system, identifying key challenges, expectations, and integration patterns. Using survey data from immigrants in Turkey, the study explores the role of demographic factors, prior transport experiences, and socio-economic conditions in shaping mobility choices. The findings indicate that while many aspects of Turkey′s transport system are familiar to immigrants, significant barriers such as high travel costs, unclear traffic signage, and language-related difficulties hinder complete adaptation. Younger, higher-educated immigrants and those from culturally similar backgrounds demonstrate a faster integration process, whereas older immigrants and those with limited educational backgrounds face more significant obstacles. Statistical analyses, including multiple linear regression and decision tree classifier, reveal that age is the most significant predictor of long-term transport adaptation. Additionally, the study highlights that as the duration of stay increases, immigrants exhibit a higher reliance on public transportation, with ownership of private vehicles gradually rising among long-term residents. The research underscores the need for policy interventions, such as reducing transport costs, improving multilingual signage, and offering integration programs to enhance immigrant mobility. These insights provide valuable guidance for policymakers, urban planners, and transport authorities striving to develop more inclusive and efficient transport systems.
The approach to optimization of the structure of the repair process of aviation radio equipment
The Operation System (OS) of Aviation Radio Equipment (ARE) includes such elements as equipment, organizational structure, processes, documentation, personnel, measuring equipment, consumables and information resources, and others. When considering the problems of primary design and modernization of OSs, a large number of problems arise that can be solved with the help of intelligent decision support systems. During the operation of ARE, significant material resources are consumed, the amount of which is usually random. Therefore, during design, one of the main tasks is to ensure the minimum costs. This article considers the task of cost optimization within the organizational structure of the repair process. At the same time, the article provides analytical equations that allow to calculate and estimate operational costs for a given organizational structure, tariffs for repair and delivery of equipment components, and failure flow parameters. Attention is also paid to the task of rationalizing the organizational structure of the repair process, taking into account the efficiency of the decision-making procedures depending on the failure type (simple or complex). In addition, the article considers an example of several scenarios for the possible placement of repair enterprises in the airports of Ukraine during the post-war reconstruction period.
Accessibility of public transport for people with disabilities: a systematic literature review
The use of public transport is a facilitator for the development of people′s abilities and a channel for their participation in society. Mobility limitations are a cause of social exclusion and people with disabilities is one of the groups most likely to suffer from it. Problems using public transportation are among the main causes for this exclusion. The aim of this research is to conduct a systematic review of the published literature on to public transport accessibility for people with disabilities. We have found articles published in peer-reviewed scientific journals between 2010 and 2022, searching in Web of Science Core Collection (WoS) and Scopus databases implementing the Systematic Literature Review (SLR) methodology and applying Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. Of the 2224 documents found during the initial search, we selected 65 articles according to the criteria used, more than 60% of them published in the last 4 years. Despite the growing literature on public transport and disability, there is still little research into this area, with the urban bus being the most studied mode of transport; and physical disability the most analysed in the articles identified.
The impact of basic traffic flow characteristics on traffic accident occurrence on 2-lane rural roads in Serbia
Basic traffic flow characteristics, such as volume and speed, represent the key criteria for estimating the level of service and traffic safety. Numerous studies have been conducted with the aim of determining the impact of the basic traffic flow characteristics on traffic accident occurrence. However, the mutual impact of traffic volume and speed characteristics has not been examined to a sufficient degree. Therefore, the authors of the article analysed the mutual impact of average annual daily traffic (AADT), share of heavy vehicles in the traffic flow (%HV) and speed parameters (such as speed variance $\left( \sigma^2_{s} \right)$, average travel speed (ATS), speed limit credibility and percentage of exceeding the speed limit (%ESL) on traffic accident occurrence on Class I 2-lane rural roads in the Serbia. The article analysed spatial distribution and traffic accidents′ severity on homogeneous segments equipped with automatic traffic counters, which provided data on speeds and other traffic flow characteristics during a 5-year period. The application of generalised linear models led to the development of 3 negative binomial models with an natural logarithm (ln) link function for the (1) total number of traffic accidents (ACT), (2) property damage only accidents (ACPDO) and (3) injury and fatality accidents (ACI&F). The obtained results show that 3 variables are statistically significant in all 3 final models: (1) AADT, (2) $\sigma^2_{s}$ and (3) difference between the free-flow speed and speed limit $\left( \small\Delta S_{ff - {lim}} \right)$. All variables included in the final models are positively associated with the dependent variable. In other words, the rise of the values of AADT, $\sigma^2_{s}$ and $\small\Delta S_{ff - {lim}}$ variables increases the expected number of traffic accidents. The variable related to the %HV is statistically significant in the models related to the ACT and traffic accidents with injuries and fatalities, and it is positively associated with the expected traffic accident number.
A case study of the use of statistical processing of the armature rotation irregularities for the diagnostics of locomotive traction electric motors
Locomotive Traction Electric Motors (TEMs) generate power to rotate the wheelsets of diesel or electric locomotives, electric or diesel multiple units. TEMs are the most critical parts of traction rolling stock on which exploitation costs, reliability and train traffic safety depend. The purpose of the article is to evaluate the possibility of diagnostics the technical condition of the TEM using the rotation irregularities of the armature shaft in the electric motor as a diagnostic parameter. The article analyses the main causes of TEM failures and methods for diagnosing electric motors in operation. The expediency of using the rotation irregularities of the armature shaft in the electric motor as a diagnostic parameter is substantiated. The structural flowchart of the device for measuring the rotation irregularities of the armature is presented. Diagnosing the mechanical part of an electric motor is chosen as an implementation example. The authors confirmed the connection between the technical condition of the electric motor and the statistical indicators calculated for the signal of the rotation irregularities of the armature shaft.
Real-time information-based combined control method for bus delay
As environmental pollution and energy consumption become increasingly serious concerns, more cities are opting for electric buses over traditional fuel buses. However, the stability and reliability of electric buses during operation are challenged by the unpredictability of traffic flow and passenger demand. Factors such as traffic congestion, weather conditions, and fluctuations in passenger numbers can compromise the punctuality of electric bus services, often resulting in delays. To address these challenges, a real-time dual-objective bus control model for mixed traffic scenarios has been proposed. This model aims to minimize both passenger time costs and company operational costs. Factors such as intersections and traffic flow are also considered. A combined control strategy, including speed control and a backup bus replacement strategy, has been proposed. Speed control is specifically aimed at managing intersection delays, allowing buses to adjust their speeds to pass through intersections optimally between queue dissipation and the end of the green-light period. The backup bus replacement strategy, on the other hand, is implemented at bus terminals, where a backup bus replaces a delayed one to maintain the schedule. A heuristic algorithm based on Particle Swarm Optimization (PSO) is incorporated into the model, enhancing its effectiveness by iteratively updating the positions and velocities of particles in the search space. Harbin City Road 96 was selected as a case study for model validation. In the off-peak case scenario, schedule deviation was reduced by 89% through the implementation of the proposed speed control strategy. Additionally, passenger waiting time was reduced by 8%, and passenger travel time was reduced by 14%. In the peak case scenario, the proposed control strategy effectively eliminated bus departure delays originating within the bus system. These results demonstrate the potential of the proposed model to significantly enhance the reliability and stability of public transportation systems, thereby improving the overall quality of public transport services.
Viability of automation, robotization and intelligent systems in the last-mile delivery: a roadmap for future research
Cutting-edge technologies in automation, robotization and intelligent systems are emerging in last-mile delivery. However, lacking knowledge on viability is limiting the application and transformation in the final stage of logistics chains. The aim of this article is to identify viable automation, robotization and intelligent solutions and discuss their association for last-mile delivery optimization. This article therefore presents a systematic review of automation, robotization and intelligent solutions, followed by empirical data collected from a workshop with practitioners and representatives of logistic companies, seeking to identify associated opportunities and challenges. The analysis resulted in 3 clusters of innovative solutions discerned upon functional characteristics. Furthermore, the acquired empirical data enabled co-relation from theory and practice to both ensuing opportunities and challenges. By analysing the input by practitioners in the field, we propose internal development and spillover effects as deriving opportunities, technical requirements, and societal concerns as emanating challenges. Based on the diversity of opportunities and challenges associated to each solution, this study proposes a roadmap for future research.
Forecasting short-term passenger flow on a bus route: a splitting–integrating method based on passenger travel behavior
Short-term passenger flow forecasting is the key to implement real-time dynamic dispatching of buses, which can meet the travel time requirement of passengers with different attributes. In practice, it is difficult to obtain passenger attribute information due to the restriction of bus information systems or other conditions. This article proposes a new perspective on identifying passenger attribute information, that is, the correlation between the bus card number and the travel time is used to analyse passenger travel behaviour. Then using the travel frequency as the splitting boundary, the passenger set is split into different types of subsets, which are predicted by different methods. The total forecast values are obtained by integration, so as to explore the effectiveness of the passenger attribute identification and splitting–integrating method. The result shows that: (1) compared with the forecasting method without considering the passenger travel behaviour, the performance of splitting–integrating method is better, and the passenger attribute identification method is effective; (2) the value of the splitting boundary will affect the size and consistency of the subset, and the optimal value can be sought according to forecast results; (3) different types of subsets should be treated by different forecasting models and combination paths.
Reducing CO2 emissions by improving road design: a driving simulator study
In the last decade, the causes of Greenhouse Gas (GHG) emissions were widely studied, to delete or, at least, mitigate them. In the road context, as reasonable, greater importance was assigned to the vehicles, since huge traffic flows, including high percentages of trucks, determine negative impacts on the environment. On the contrary, the role of the road infrastructure has always been considered marginal. It was thought as a functional element on which the traffic flows move, without evaluating the role of its geometrical characteristics on exhaust gas emissions. The proposed research aims to verify whether some road features, related to its horizontal geometry, influence the carbon dioxide production of vehicles or, on the contrary, if it is not sensitive to the different geometrical compositions. A driving simulator gives the opportunity to calculate the emissions from fuel consumption data, in turn, calculated through the engine mapping of an ordinary vehicle. The proposed procedure may be easily applied to any road context and may represent a further checking element for the infrastructure efficiency, in terms of environmental impacts. The results, derived from a test phase in a simulated environment and obtained using 3 different one-way ANOVAs, allowed the authors to define some interesting conclusions. The trend of the carbon dioxide function depends on curve radius and lengths and on tangent length; therefore, an opportune alignment design can effectively contribute to control emission values. The experiments confirmed that designing a consistent road is fundamental, but this cannot be deduced by traditional literature models.
Well-to-wheel analysis of the emissions from the electric buses used in Poland and Czechia
Road transport is one of the major sources of pollution. To solve this problem, alternative fuels with a lower environmental impact are sought. Therefore, it is important to determine the impact of the life cycle of transport fuels in order to assess, which of them are more environment-friendly by taking into account the emissions generated during fuel production and vehicle operation. Electric Vehicles (EVs) are becoming increasingly popular. This article discusses a life cycle approach to the assessment of transport fuels intended for electric buses. It presents a comparative Well-To-Wheel (WTW) analysis of the emissions from the buses used in Poland and Czechia by analysing their life cycle, with particular consideration of the production of the electricity required to charge electric batteries. Furthermore, a comparative analysis of an electric bus and a conventional diesel bus has been performed. The results of the analysis are expressed as Greenhouse Gas (CHG) emission ratios across the life cycle of the buses operated in Poland and Czechia.
Risk analysis of road traffic accidents in Ukraine
This article presents a comprehensive investigation into the causes of road transport accidents in Ukraine, focusing on the application of risk analysis to minimize economic and human losses. The study begins with a detailed examination of the current road safety scenario in Ukraine, highlighting the alarming statistics of road accidents and their consequences. The central aim is to develop effective strategies for controlling and managing the causes of road accidents. The research identifies the primary factors contributing to road accidents, such as exceeding safe speed limits, driving under the influence of alcohol, etc. A risk management system is proposed, encompassing the creation of a structured risk management framework, development of methodologies, and implementation of information and analytical systems. The article emphasizes the importance of continuous risk monitoring and assessment, including risk identification, analysis, and management. Statistical observations and analysis play a crucial role in diagnosing risks, which are then used to devise risk minimization measures and improve road safety. The study concludes with recommendations for risk-based decision-making and the implementation of targeted interventions to reduce road accidents and associated risks in Ukraine. First published online 11 February 2025
Copyright (c) 2024 The Author(s). Published by Vilnius Gediminas Technical University. http://creativecommons.org/licenses/by/4.0
Multidimensional cost analysis of Europe–Asia container transport routes
In this article, we propose a 3-dimensional framework for evaluating the costs of transporting goods between Europe and Asia, including direct transport, time, and Environmental Costs (ECs). We estimate the costs of alternative container transport routes, including direct sea transport via the Suez Canal Route (SCR) and the Northern Sea Route (NSR); direct rail connections via the Trans-Siberian Rail (TSR) and the Belt and Road Initiative (BRI), and intermodal transport options consisting of rail and sea transport legs. When considering environmental and Inventory Carrying Costs (ICs), the NSR is viable at least seasonally, whereas rail and intermodal alternatives remain more expensive. The results provide a robust estimate of the potential of alternative transport routes and modes. The inclusion of ECs in our analysis provides valuable new information to stakeholders on how to achieve the ambitious environmental goals while also considering the economic viability of different route options in Europe–Asia container trade.
The operational resilience evaluation method as a tool for decision-making during traffic disruptions in the railway system
Basically, node connections and arc capacity issues are taken into account for resilience evaluation. Then, resilience investigation is mainly limited to catastrophic events with focus on the system layer. Nevertheless, from the operation point of view it is not enough to keep the correct node connection of the system but also to keep the appropriate process schedules. Thus, it is important to go beside the classical network (system) resilience and to develop the concept of operational resilience. In the typical resilience analysis, the main function necessary for resilience evaluation is the performance or functionality in time. Normally it is defined by one criterion, for example available railway lines, or number of trains, or hardly ever also punctuality. Therefore, the 1st aim of this article is to propose a multi properties functionality function, that takes into account operation process parameters like punctuality, delay probability, number of launched trains, and correctly assigned resources. 2nd, the article shows a tree stage fuzzy model to calculate the performance function using the incoherent process parameters. The multidimensional character of the functionality function is well covered by the proposed 3 stage fuzzy model. It makes it possible to put together different measures, and to calculate in an effective way the synthetic functionality/performance value. The model is in detail described as well as its developed including theoretical works, operational data analysis, as well as the experience of experts. The model description is followed by a railway case study, where scenarios elaborated by Experts are evaluated and compared, looking for the best one in terms of resilience. A resilient solution will be that one with the smallest performance/functionality loss in time. Basing on the case it can be concluded that the method is a step forward in resilience research. It has also a high practical potential due to simplification of very complex prediction issues. For example, possible further lack of crews or vehicles is represented as negative influence on the functionality function, without the need to make in short decision time complicated and not maybe incomplete.
Designing a sustainable closed-loop supply chain using robust possibilistic-stochastic programming in pentagonal fuzzy numbers
The lack of information and hybrid uncertainties in Supply Chain (SC) parameters affect managerial decisions. It is inevitable to consider random uncertainty based on fuzzy scenarios and cognitive uncertainty to model a Sustainable Closed-Loop SC (SCLSC) problem. Using Pentagonal Fuzzy Numbers (PFNs) has higher comprehensiveness and accuracy than triangular and trapezoidal fuzzy numbers due to taking into account higher uncertainty, less lack of information, and taking into account maximum subjectivity Decision-Makers (DMs). There is a gap in the literature regarding the use of PFNs in SCLSC problems. This research presents a new model using PFNs to solve deficiencies in stochastic-possibilistic programming. Developing a Robust Stochastic-Possibilistic (RSP) based on PFNs under fuzzy scenarios, presenting measures of necessity, possibility, and credibility for making decisions founded on different levels of DMs’ risk, and proposing global solutions through providing linear programming models are the main innovations and contributions of the present research. An actual case study evaluates the presented approach to reduce the cost and carbon pollution in the stone paper SC. In the suggested method, trade-offs could be formed between the mean of objective functions and risk by modifying the robustness coefficients. According to the proposed approach, an optimal value of confidence is specified. Additionally, robustness deviations are controlled in the model, which results in more accurate and reliable results. Numerical simulations confirmed the efficacy of the robust approach proposed. First published online 7 February 2025
A multi-objective fuzzy optimization model for multi-type aircraft flight scheduling problem
This study proposes a multi-objective optimization model for an Aircraft Flight Scheduling Problem (AFSP) for assigning a set of aircraft located at different airports to conduct all flight trips. The proposed model features each flight trip with its own special aircraft type and fuzzy flight time. Moreover, a flight trip with a small aircraft being covered by a larger one is fully accounted for in the model. The model can effectively reduce the number of aircraft and achieve the minimum total idle time for adjacent flight trips covered by an aircraft. A novel heuristic algorithm based on the Non-dominated Sorting Genetic Algorithm (NSGA-II) is further designed to yield meta-optimal solutions efficiently for such a Non-deterministic Polynomial (NP) problem. Finally, a real airline scheduling example in China is conducted using CPLEX and the proposed heuristic algorithm to evaluate the difference between the proposed and traditional models. The results show that the given scheduling problem effectively enhances the operational efficiency of the aircraft fleet. First published online 28 January 2025
Computer-aided simulation of unmanned aerial vehicle composite structure dynamics
The dynamic response of an aerial vehicle structure is a key parameter that must be determined before further aeroelastic phenomena can be analysed in the aerospace sector. Natural frequencies, mode shapes, and damping can be measured or predicted through experimental, operational, or computational studies. To reduce the costs and complexity of experimental investigations, there is a demand for numerical models that accurately represent the structure′s dynamic behaviour. This article focuses on modelling composite structures, which are increasingly utilised in the aerospace industry and whose dynamic properties are heavily influenced by fibre directionality. ANSYS software and the ACP module were employed to develop a numerical model of a wet Epoxy Carbon UD (230 GPa) composite commonly used in Unmanned Aerial Vehicle (UAV) components. Ten layers of 0.1 mm thick carbon fibre were incorporated into the model to create a 1 mm thick composite plate, with fibres oriented at 0°, 30°, 45°, and 90° relative to the horizontal direction of the plate. The simulations demonstrated that careful consideration and modelling of the material significantly impact the values of natural frequencies and, more importantly, the mode shapes. First published online 28 January 2025
Railway transport system modelling approach for robustness analysis
The article presents an approach to train traffic modelling that allows for the analysis of how railway networks respond to various disturbances, including increased traffic and disturbance events. It discusses different methods of reconfiguration actions in key points of the railway network, which helps reduce delay propagation in the transport system. The 1st part covers building simulation models, which include defining infrastructure, setting train routes, configuring rolling stock, and disturbance scenarios, enabling the analysis of various disruptive events. The simulations allow for testing disturbance scenarios with minimal downtime risk without interfering with the real-world environment. The study results identified key system parameters generating the largest delays, such as platform availability, signaling, and the number of block sections. Probability density distributions for event intervals and durations were analyzed. The Kolmogorov–Smirnov test was used to confirm the fit of empirical distributions with theoretical ones, which were then implemented in the model of railway line No 271, running from Wrocław to Żmigród (Poland). As part of the reconfiguration of this railway line, new platforms were added, the time required for route setting was reduced, and the number of block sections was increased. These actions significantly reduced average delays, improved line capacity, and enhanced the robustness of the railway transport system against disturbances. The reconfiguration effectively reduced delays in areas causing significant time exceedances above 359 s, which was recognized in the Polish railway network as critical. First published online 3 January 2025
Spatial partition for heterogeneous city networks composed of factors that influence the distribution of the macroscopic fundamental diagram
Using a Macroscopic Fundamental Diagram (MFD) to implement partition control is effective in improving mobility in heterogeneous city networks. As one of the most complex issues in partition control, accurate sub-region partition is critical for control effectiveness. Current partition methods focus on the link density and precondition of existing MFD and disregard the factors that influence MFD distribution. To overcome this drawback, this study uses the characteristic value of the link and the intersection connected to the link as the analysis object and proposes an MFD sub-region partitioning method for large-scale networks. Firstly, the influences of road state parameters on MFD distribution are classified into traffic flow parameters, network physical properties, network operation mechanisms and emergencies. Simulation experiments are conducted to determine the degree to which these classifications affect MFD distribution. Secondly, a partition method combined with the link density and influence parameters of MFD is developed. The method is used for a preliminarily division of a road network through Minimum Spanning Tree (MST) and depth partition by the Normalised Cut (Ncut) algorithm. Finally, a case study is conducted in an actual city centre network, and results show that the developed method is superior to the single method based simply on link density.
Copyright (c) 2023 The Author(s). Published by Vilnius Gediminas Technical University. http://creativecommons.org/licenses/by/4.0
Starting driving style recognition of electric city bus based on deep learning and CAN data
Drivers with aggressive driving style driving electric city buses with rapid response and high acceleration performance characteristics are more prone to have traffic accidents in the starting stage. It is of great importance to accurately identify the drivers with aggressive driving style for preventing traffic accidents of city buses. In this article, a starting driving style recognition method of electric city bus is firstly proposed based on deep learning with in-vehicle Controller Area Network (CAN) bus data. The proposed model can automatically extract the deep spatiotemporal features of multi-channel time series data and achieve end-to-end data processing with higher accuracy and generalization ability. The sample data set of driving style is established by pre-processing the collected in-vehicle CAN bus data including the status of driving and vehicle motion, the data pre-processing method includes data cleaning, normalization and sample segmentation. Data set is labelled with subjective evaluation method. The starting driving style recognition method based on Convolutional Neural Network (CNN) model is constructed. Multiple sets of convolutional layers and pooling layers are used to automatically extract the spatiotemporal characteristics of starting driving style hidden in the data such as velocity and pedal position etc. The fully connected neural network and incentive function Softmax are applied to establish the relationship mapping between driving data characteristics and the starting driving styles, which are categorized as cautious, normal and aggressive. The results show that the proposed model can accurately recognize the starting driving style of electric city bus drivers with an accuracy of 98.3%. In addition, the impact of different model structures on model performance such as accuracy and F1 scores was discussed, and the performance of the proposed model was also compared with Support Vector Machine (SVM) and random forest model. The method can be used to accurately identify drivers with aggressive starting driving style and provide references for driver’s safety education, so as to prevent accidents at the starting stage of electric city bus and reduce crash accidents.
Funiculars in Lithuania: from the fruit basket to Gediminas Hill
Technological advances in transport of the 20th century include aeroplanes, human spaceflight and Moon landings, submarines, and magnetic levitation trains. In the fast-paced world of technology, the achievements of previous centuries are often forgotten. One of the examples of human ingenuity is the funicular railway. Its technology has hardly changed over the years. Using a simple pulley system, passengers and freight are still lifted steep slopes with minimal energy consumption. This demonstrates the lasting value of simple solutions and engineering intelligence. The article discusses the world’s funiculars and their design characteristics. A correlation analysis for the number of funiculars per country (N) and the country mountainousness index (M) has been carried out. 3 types of regression models have been developed and their determination and correlation coefficients have been calculated. The highest correlation coefficient values are for quadratic and linear mathematical models. The critical values of the correlation coefficients were calculated and compared with the correlation coefficients obtained from the study. For all 36 countries, the correlation coefficient for N and M variables is above the critical value only when a quadratic regression model is used. The correlation coefficients for all models are above the critical value for the 15 economically advanced and tourism-developing countries. The study shows that the number of cable cars in economically developed countries is more strongly correlated with the degree of mountainousness of the country in question.
Multi-criteria decision-making for solving transport sustainability issues: an overview
With the recognition of the impact of the transport sector on climate change and human health, decision-makers are under the pressure to shape the transport sector in a more sustainable way, considering more sustainable options and technologies. Besides that, it is also important to ensure such aspects as affordability, security, reliability and convenience of transport services and the effective functioning of the whole system. Therefore, transport-related policy actions require not only an economic point of view, but also environmental and social actions. The article aims to overview the application of Multi-Criteria Decision-Making (MCDM) techniques for solving sustainability issues in the transport sector and to provide the main insights for methods and sustainability criteria selection. The Search, Appraisal, Synthesis and Analysis (SALSA) framework and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement were applied as the basis for the research. The detailed content analysis of studies is arranged according to the application areas and the methods applied. In order to increase the applicability of the performed analysis and to simplify the decision-making for further studies, the thematic areas for criteria selection are proposed, the most popular MCDM techniques alongside their advantages and disadvantages are briefly discussed.