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.

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.

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.

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.

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.

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.

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.

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 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.

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.