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.
Urban traffic flow simulation in various weather conditions using long short-term memory-based machine learning
This study proposes a weather-aware short-term urban traffic prediction framework that combines microscopic traffic simulation with Long Short-Term Memory (LSTM) based Machine Learning (ML) for forecasting vehicle flow at selected urban junctions. The research is motivated by the need to improve traffic-state prediction under varying environmental conditions, since weather disturbances such as rain, fog, and snow significantly affect driver-behaviour, vehicle speed, spacing, and intersection throughput. The simulation environment was developed in the Simulation of Urban Mobility (SUMO) platform using an urban road segment derived from geographic map data and traffic-flow information from the Vilnius city traffic database. 2 monitored junctions were selected as observation points, and traffic behaviour was simulated under 5 weather scenarios: normal conditions, light rain, heavy rain, fog, and snow. Weather-dependent driver parameters, including speed factor, reaction time, acceleration, deceleration, driver imperfection, and minimum gap, were incorporated into the simulation in order to reproduce realistic traffic dynamics. The generated simulation data, including vehicle count, speed, waiting time, temporal features, and encoded weather conditions, were used to train and evaluate multiple LSTM models through an AutoML-based tuning procedure. Among different configurations, the best-performing model consisted of 3 recurrent layers and achieved a validation RMSE of 0.1056 with a validation loss of 0.0652. The results show that the proposed framework is capable of reproducing the general temporal structure of urban traffic flow and preserving the relative ordering of traffic intensity across weather scenarios. Prediction quality was highest under normal conditions, with RMSE of approximately 0.21 veh/min, while the poorest accuracy was observed under snow conditions (about 2.5 veh/min). The model captured dominant traffic trends effectively, although it tended to smooth short-term local oscillations, especially under more unfavourable weather conditions. Overall, the study demonstrates that integrating SUMO-based simulation with LSTM forecasting provides an effective and flexible approach for short-term urban traffic prediction under varying meteorological conditions and may support future intelligent traffic management and weather-adaptive mobility applications.
Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. http://creativecommons.org/licenses/by/4.0
Modelling and optimizing flights diversion due to destination airport closure
With the fast development of civil aviation, large number of flights operate in major airports in rush hour. Extreme natural disasters, terrorism, and incidents may interrupt its normal operation, even lead temporary closure. Abrupt airport outage causes significant flights diverting to alternate airports. In this article, a centralized optimization method is proposed for the management and optimization of widespread flight diversion. Based on the idea of Collaborative Decision-Making (CDM), a linear programming model formulation is developed to assign flights, who are inbound to a temporary closed destination airport in an emergency, to divert to appropriate alternate airports. The objectives are minimizing total diverting time of flights as well as maximizing the expectation to alternate airports for airlines. Incorporating relevant real-world features, flights remaining flying time available and expectation of alternate airports are taken into account from airlines operation perspective. Airport alternate capacity, the category of aircraft could be accepted and the arriving flight slots assigned are considered for alternate airports. In addition, aircraft cruise speed, en-route wind, air traffic congestion and so on is considered. In the case study, it is found that under the given condition of 50 flights and 8 alternate airports, all flights can be accommodated within the remaining flying time, 33 (66%) flights are less 60 min and 48 (98%) flights are less than 120 min. The model solving time expenditure is less than one 2nd. It can meet the emergency condition and prevent a longer decision-making process. Comparing with the objective of the shortest diverting time as literature, the total diverting time is suboptimal but the formulation can get a better expectation of alternate airports for flights, which provides more flexibility of operations in airlines.
Factors influencing CO2 emissions in petrol passenger cars: evidence from Slovakia
The aim of this article is to identify the factors that influence the evolution of CO2 emissions in gasoline passenger cars. Specifically, the factors that can be obtained during emission measurements at technical inspection stations are analysed. This identification is used to determine the factors obtained by measurements at the technical inspection stations that should be used as a design element for the taxation of petrol road vehicles in order to reduce CO2 emissions. The underlying source was data recorded by the vehicle technical inspection stations in 2019 and worked with passenger petrol cars of category M1. In total, almost 460000 passenger cars were analysed. 12 factors were used for each car, from which 7 variables were identified through 2 methods (BMA and WALS) as likely to have a statistically significant effect on the magnitude of CO2 emissions. Subsequently, the effect of each factor was determined by OLS with robust Std. Err. Our results show that the maximum engine power and the latest emission standards can be used as design element for the taxation of gasoline road vehicles, as a positive relationship between the growth of this factor and the magnitude of CO2 emissions of gasoline vehicles has been demonstrated.
A data-driven picking strategy for micro fulfilment centers in quick commerce: the case of Korea
Quick Commerce (Q-Commerce) allows customers to receive their orders from near Micro Fulfilment Centers (MFCs) in a short time. However, the fulfilment centers are difficult to maintain responsive and reliable delivery services with traditional Single Order Picking (SOP) systems. Motivated by the above challenge, this study develops a hybrid picking method for an order fulfilment center of a Korean delivery company. The hybrid method considers certain rules for order batching to complement a SOP method. The order batching rules enable pickers to deal with 2 customer orders within a specific range of order lines. The order picking development are based on the results of a Warehouse Activity Profiling (WAP) analysis. This analysis shows possible approaches for the development of the hybrid method by considering arrival rates of customer orders and their variability in terms of item type and quantity. Afterwards, the hybrid method is validated with an agent-based simulation model using actual order information of the case study company. This study finds that the hybrid method shows consistent performance in terms of order picking and fulfilment times under wide ranges of order arrival rate and variability.
Improving the efficiency of using an electric scooter in urban electromobility
The popularity of electric scooters as an individual means of transport results from their availability in the urban sharing system, ease of movement in the city and reduction of driving time compared to other means of passenger transport. The user can choose from a whole range of vehicles with different driving range and equipment with elements increasing the functionality of using the scooter. The article presents a proposal for changes to the design of a typical electric scooter. The main objective of the work is the engineering design of suspension and braking systems, in particular the swing arm suspension of the front and rear wheels and an additional disc brake. Increasing the diameter of the wheels and equipping it with a front and rear suspension system allowed for the reduction of vibrations and shocks transferred to the vehicle when driving on uneven surfaces. The results of analytical calculations confirming the positive effects of the introduced modifications were included. Adding a disc brake allowed for shortening the braking distance from 13.7 to 8.9 m, which has a positive effect on driving safety. A Finite Element Method (FEM) strength analysis was also performed, the results of which confirm the correctness of the new design. The modernized design improved the ride comfort and safety of using the electric scooter. First published online 9 February 2026
Copyright (c) 2025 The Author(s). Published by Vilnius Gediminas Technical University. http://creativecommons.org/licenses/by/4.0
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
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