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In this article is dealt with the ways of improving the diagnostic accuracy of braking systems of passenger cars, taking into account the operational factors. A diagnostic system that monitors the pneumatic processes and transmits the data in real time has been implemented. The method proposed has provided an increase of reliability from 83.1% to 87.6%.

Logistic regression has been a widely used prediction technique to analyze categorical variables. However, if the assumptions are violated the results may be biased. The study in this paper applied an analytical technique namely generalized ordered logit model. A case study of using urban light rail under pandemic conditions was applied for the analysis. The results suggested that logistic regression should not be applied before exploring the multicollinearity and applying the test of parallel lines. If the assumptions are violated, generalized ordered logit model should be considered. Regarding the predictive variables, sociodemographic, socioeconomic and travel pattern, related variables were found to have a statistically significant impact on the perception of safety and infrastructure of urban light rail. The outcomes of the study would provide a deeper understanding of developing regression models for categorical variables for future studies.

Widespread application of advanced transportation technologies in conditions of open-pit mining with the use of high-capacity belt conveyors is limited by the need for additional crushing of overburden rocks and minerals. Accordingly, the quality of crushing of rock mass, the output of oversize during drilling and blasting operations at quarries and open-pit operations significantly affect the possibility of using flow and cyclic-flow technologies with the use of conveyor transport. In this paper is presented a method of increasing the energy efficiency of the explosive pulse in drilling and blasting operations by means of developed gas pedal designs to improve the quality of crushing and conditions of conveyor delivery of rock mass.

In this study is presented an analytical mathematical model developed to determine the forces arising during the active penetration of machine working bodies into sticky rocks. The methodology is based on the method of element-by-element calculation of resistances, where the contact zone is divided into discrete prisms of material. As a result of the analysis, a final formula for the total penetration force is derived. This formula shows the dependence of the resistance force on the dimensions of the tool (thickness, depth, angle of sharpening) and the physical characteristics of the rock (internal friction, adhesion, stickiness). The model serves as a reliable engineering tool for the design and optimization of working bodies of earthmoving and mining equipment.

The purpose of this study was to determine the vibrations transmissibility characteristics of an air suspension system (ASS) with self-damping air bellows to assess the comfort and safety of the ride. The conceptual design of a pneumatic self-damping air bellow is presented, which involves forced airflow through a damping orifice between the air bellow and an auxiliary reservoir. Two dynamic models, classical and simple, of the analyzed air bellow were used for numerical modelling solutions. Vibrations transmissibility charts as a function of the frequency ratio and at different damping ratios were determined using the accepted excitation forces. The different vibrations transmissibility states and dynamic characteristics of the air bellow for the frequency ratios and individual damping (inherent, pneumatic self-damping, and hydraulic absorber) in the ASS range were examined.

In the development of Global Navigation Satellite System (GNSS) Positioning, Navigation, and Timing (PNT), short-lived, fast-growing ionospheric storms (lasting up to three days) were assumed to constitute a single, uniform class of space weather events. To challenge this premise, here is presented a circular analysis of single-frequency commercial-grade Global Positioning System (GPS) horizontal positioning errors in the mid-latitude region during four observed storms (one in 2015 and three in 2017), revealing significant heterogeneity. Maximum positioning errors reached 7.495 m in March 2015, but peaked at 4.261 m, 4.387 m, and 3.948 m during storms in May, early September, and late September 2017, respectively. By demonstrating that short-duration, fast-growing storms require subclassification, in this study is offered a new perspective on disturbances.

In this study are analysed the determinants of road traffic fatalities in the Visegrad Group countries during 2000-2024, using a balanced panel and fixed-effects models with Driscoll-Kraay standard errors. The results show that the higher motorization and a longer high-standard road network are associated with lower fatalities. By contrast, the GDP per capita and unemployment increase fatalities in the baseline model, although these effects are sensitive to alternative specifications. Public expenditure on road infrastructure has no robust immediate effect, with only limited evidence of delayed benefits. Overall, the findings suggest that the road safety depends not only on economic growth, but on the quality and structure of infrastructure development, as well.

In this article is addressed the optimization problem of assigning aircraft to parking stands on the apron of international regional airports. The goal was to position an aircraft on the airport apron in a way that complies with operational, capacity, and safety constraints while optimizing the value of the selected optimization criterion. In contrast to other commonly published approaches, problem considered here focuses on minimizing passenger transport between the parking stands and the terminal via airport buses. To solve this problem, a linear integer programming model is formulated and solved using the Xpress-IVE optimization software. The model’s functionality is tested using real operational data from Ostrava International Regional Airport.

A machine learning framework for predicting the traffic accident severity under class imbalance conditions is predented in Amman, Jordan. The methodology began with a preprocessing pipeline consisting of IQR-based (Interquartile range) outlier removal, label encoding, feature scaling, and Synthetic Minority Over-sampling Technique (SMOTE). Sixteen model configurations were considered, comprising four ensemble learning algorithms (XGBoost, LightGBM, Random Forest, CatBoost) under oversampling, with Optuna-based Bayesian hyperparameter optimisation. The result indicated that the class balancing using SMOTE had a greater influence on the predictive performance than hyperparameter optimisation, specifically for CatBoost model. Feature importance showed that vehicles involved, collision type, and speed are the strongest predictors of accident severity.

In this paper is presented a cloud-based framework for automated acquisition and visualization of Orbiting Carbon Observatory-2 (OCO-2) satellite CO₂ data. The system employs an ETL pipeline with OPeNDAP protocol for selective data retrieval, reducing network overhead while processing L2 Standard and L2 Lite FP products. Built on Amazon Web Services (AWS) infrastructure, using Python (Pandas, Dash, Plotly) and Docker orchestration, the modular architecture implements dependency injection for runtime flexibility. The deployed system achieves daily automated ingestion with 2.25 km × 1.29 km spatial resolution, enabling the real-time monitoring through interactive web visualization. The system is designed as a foundation for future analytical research, providing ready integration points for machine learning models to perform advanced CO₂ pattern recognition and predictive analysis.

The sustainability of international transport remains a critical topic of concern in both theory and practice. Ideally, scientific literature should align with practical needs, but such concurrence is not always present. This disparity is also evident in the specific issue of consignment delivery, which is currently of a great practical importance but lacks sufficient coverage in scientific literature. This paper aims to analyse current trends in maritime transport and their relevance to achieving global sustainability in international transportation. Additionally, it seeks to compare these findings with the practical needs and requirements of the industry, in order to provide constructive recommendations for further research. To accomplish this objective, a bibliometric analysis was conducted using scientific databases, including Web of Science and/or SCOPUS.

In this study is proposed and evaluated an adaptive traffic signal control system designed to synchronize the road and railway signaling, minimize collision risks, and improve traffic flow. Results show that adaptive control reduced average queue length for over 46%, cut vehicle delay for 34%, lowered stop frequency for 74%, and decreased CO₂ emissions for nearly 46% compared to static control. Further analysis examined the effect of varying the distance between intersections and railway crossings, revealing significant safety and efficiency gains when the separation exceeded 80 m. The findings demonstrate that intelligent, sensor driven traffic management can substantially enhance both safety and throughput in these complex transport nodes, while delivering environmental benefits.

Road traffic remains a major contributor to carbon dioxide emissions, making innovative energy solutions essential. Electric vehicles (EVs) offer a promising alternative, however, current lithium-ion batteries face limitations in power output, energy density, and cost. To address these challenges, hybrid energy storage systems (HESS) combine batteries for energy storage with supercapacitors for rapid power delivery. In this study was explored an optimization tool for EV operation using HESS configurations and evaluates performance through MATLAB Simulink simulations across various driving cycles. The results highlight trade-offs between the performance, weight, and cost, which vary by vehicle class. While HESS improves energy efficiency and extends battery life, its complexity and expense limit feasibility for medium and high-class vehicles. Lower-class vehicles benefit most from this approach. Ultimately, tailored HESS designs adapted to specific driving conditions can enable more sustainable and efficient electric vehicles.

Parametric transition curves designed to guarantee a smooth transition from tangent (straight) tracks to circular segments in the horizontal-plane projection of a railway track alignment. A rigorous theoretical framework was developed to express the functional dependence of curvature, deflection angle, and Cartesian coordinates on the curve's arc length. To validate the theoretical derivations, a detailed computational experiment was performed, fully confirming their correctness and accuracy. Furthermore, a methodology for constructing coordinate tables as a function of arc length - highly valuable for practical railway design and field layout - is provided. A robust mathematical apparatus for the curvature-based design of railway transition curves is established. The results demonstrate that the coordinates of the circular arc center were optimized and refined to the required level of precision.

The risk assessment of the area, with emphasis on the transport infrastructure, is dealt with in this paper. Disruption of some elements of transport infrastructure can lead to major negative impacts on the functioning of society, economies or states. The article therefore starts with presentation of the characteristics and importance of the road transport infrastructure with regard to its vulnerability. The core of the paper is the identification of vulnerable elements of road transport infrastructure and their parts and the subsequent vulnerability assessment of the selected element of the road transport infrastructure in the selected area. Therefore, the aim of the research, presented in this paper, was to propose a method for identifying and assessing the vulnerability of road transport infrastructure elements using the latest approaches in the field of vulnerability assessment. The proposed vulnerability assessment procedure is applied in the conditions of the city of Rajec in Slovakia.

The spatiotemporal redistribution of traffic flows under alternating blocking of channels at a signalized four-leg intersection is investigated using the case of Augustusplatz in Leipzig, Germany. Observations were conducted over three days, with flows recorded in 48 half-hour intervals per day across four directions and four categories of vehicles. For stochastic modelling, the negative binomial distribution, Taylor’s dispersion index (VMR), Shannon entropy, and an approximation based on M/G/1 queueing theory were applied. A mathematically grounded framework for the real-time network control is proposed, highlighting the necessity of adaptive signal timing adjustments to accommodate stochastic fluctuations and spatial overcompensation effects during node closures.

Internal combustion engines, which operate in various load and speed conditions, are significant sources of environmental pollution that affect a vehicle's movement in traffic. Automotive engines typically operate in unsteady-state modes, transitioning cyclically from one operating mode to another during vehicle operation. The potential of using biogas as an additive to compressed natural gas for automotive engines was explored within this research. The results of experimental studies on the fuel efficiency and environmental performance of a vehicle with a petrol engine, converted to run on a mixture of compressed natural gas and biogas, are presented. A comparative analysis was conducted on the fuel and economic performance, as well as environmental indicators of A-92 petrol, compressed natural gas, and a mixture of compressed natural gas and biogas in the European driving cycle modes.

The presented research is aimed at assessment of issues relating to strength of a universal container of the standard size of 1CC while it is transported on the sea by a railway ferry. Further it is considered that the container is located on a flat wagon at which, it is fixed to the upper deck of a railway ferry. Three load scenarios were considered in the research. Each of these scenarios are characterized by loaded conditions defined in the study. The structure of the investigated container was modelled in a commercial simulation software. The dynamic loads acting to the container structure for all three considered schemes, were carried out using mathematical modelling. The finite element method was applied to the numerical analyses of strength of the container structure. It was revealed by means of simulation computations, that the maximal stress in the container structure was of 102.4 MPa within the permissible limits and the maximal displacements of 4.5 mm were achieved.

Bio Fuels are considered as good alternatives for conventional fossil fuels. By the year 2020, in the GCC region these fuels are able to meet around 0.5 - 1 % of total transportation fuel demand. This industry grew at rate of 3.4 % over the period of 2015-2020 with a strong projected growth in the Kingdom of Saudi Arabia (KSA). Bio fuels are used to operate automotive for mining and construction industries. Critical barriers in foreign investments pose a major challenge for growth of this sector in the GCC region.

Transport is a phenomenon currently used in almost every sector. That is why attention is to be paid to transport safety, which should not only be addressed in relation to situation in cities or urban areas, but it is also necessary to deal with transport safety in larger enterprises where motor traffic encounters non-motorized traffic. The authors elaborated a similar research study. The introductory two sections analyze the current situation in terms of identifying bottlenecks of the traffic organization on the industrial site and possible separation of motor from non-motorized traffic to ensure safe access to workplaces and improve safety of transport on the site. In the most important part of the study, the obtained results are presented, wherein the "load" of the individual entry and exit points is specified. Thereafter, based on the acquired data, particular solutions related to transport safety with appropriate discussion are proposed.

The optimization of gear pairs in a two-stage planetary gearbox was performed using the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). A total of 18 combinations of input parameters were analyzed, varying: gear width (20, 22, 24 mm), module (2.25, 2.5, 2.75 mm) and material (16MnCr5, 34CrNiMo6). Safety factor from pitting (Sh) and safety factor from tooth fracture (Sf) were numerically obtained and those two parameters were chosen as criteria for optimization. TOPSIS identified alternative 1 (20 mm width, 2.25 mm module, 16MnCr5 material) as the optimal solution, demonstrating the highest safety factor values. Additionally, the optimization achieved satisfactory results regarding the mass of gear pairs. After optimization, the mass of gear pairs decreased by 20% compared to the pre-optimization version.

The development and simulation of a mathematical model for a hybrid powertrain vehicle, aiming to optimize its energy efficiency and dynamic performance is presented in this study. Implemented in MATLAB/Simulink, the model captures the dynamic interactions between the hybrid system's components, including the internal combustion engine, electric motor, and battery. By conducting a full factorial experiment, the specific power of the hybrid vehicle was analyzed, revealing the critical influence of factors such as driving speed, road gradient, and battery state of charge. The proposed model demonstrated a discrepancy of 4-11% between the simulated and experimental results, confirming its adequacy for forecasting energy consumption and operational range. These findings offer valuable insights for enhancing the hybrid vehicle performance and sustainability through precise energy management strategies.

In this study is examined the influence of traffic flow parameters on delay duration at signalized intersections of urban multi-lane streets. The findings show that traffic composition strongly affects delays at low volumes, while its influence decreases as total volume grows. These results highlight the need to account for traffic composition, not only volume, when optimizing the signal timing and managing flows. The novelty of the study lies in modelling delay as a joint function of traffic volume and traffic flow composition, where the share of passenger cars is varied independently, rather than through the generalized passenger car unit-based growth, enabling a more accurate assessment of delay formation under heterogeneous traffic conditions.

Rough roads negatively affect the ride quality and energy efficiency of autonomous vehicles (AVs) and demand adaptive speed control. To solve this, this research proposes a Deep Capsule Network integrated with Sparse Kernel K-means Clustering (DCapsNet + SK-K-means) to accurately reconstruct pavement conditions and adapt vehicle speed in real time. The Privacy-Preserving Federated Learning (PPFL) with Hyperledger Fabric blockchain allows federated learning to be trained in a secure and decentralized manner without the transfer of raw sensor data. With the BDD100K dataset, supervised and reinforcement learning are used. According to the obtained results of the experiment, there is a 10.45% increase in ride comfort, 28.23% in energy efficiency, and 98.28% in computational efficiency. The framework attains 93.73% security, 96.46% throughput and 0.83 s operation time at 250 vehicles/km.

Household car ownership has become a crucial issue in Indonesia due to rapid urbanization and economic growth, which have led to increased demand for personal vehicles. This surge in vehicles contributes to traffic congestion, pollution, and strains on urban infrastructure. This study aimed to investigate private vehicle ownership in relation to household characteristics and mobility attributes in developing country settings. The methodology used is the multinomial logit model (MNL) to analyze ownership patterns. The empirical results showed the significant impact of the income variable on vehicle ownership. Ownership of multiple private vehicles was more prevalent among individuals with a driver's license, males, and those who traveled longer distances. These outcomes could be invaluable for policymakers focused on reducing auto dependency and enhancing the efficiency of urban transportation systems.

The purchasing behavior of the population affects both passenger and freight traffic in cities. On the contrary, indicators of purchasing behavior are influenced by the characteristics of an individual, as well as external factors. The purpose of the conducted research was to analyze the population's purchasing behavior under martial law conditions. Data was collected by surveying residents of Ukraine's rear regions. Multinomial models of the frequency of purchases and transportation choice during shopping were formed. Martial law conditions and changes in the population size in the rear regions, change the general trends in purchasing behavior. The most visible trends are: a significant share of purchases made online, the popularity of shopping close to home, and the tangible impact of owning a car on the frequency and mode of shopping trips. The results obtained may be helpful in predicting consumer behavior in crisis scenarios.

Biomass combustion is a widely used renewable option for a small-scale heat and power, but incomplete burnout and pollutant formation remain challenges in boilers without optimized air staging. In this study, is investigated how controlled transport of air into the flame zone, implemented with an auxiliary tertiary system, affects performance and emissions in a bottom-fed pellet boiler. Tests were performed at constant fuel feed and primary/secondary airflow, with tertiary air varied between 0 and 15.8 m3/h. An airflow of about 8.9 m3/h proved optimal, giving the highest thermal output, a more uniform temperature distribution, and a nearly twentyfold reduction in CO emissions normalized to 10% O2. NOx rose only moderately (by approximately 60 mg/m3). The findings show that targeted air transport and staging into the flame zone can substantially improve combustion completeness and boiler efficiency.

The research presented in this article is aimed to show the prospective direction of increasing the efficiency of cleaning dusty air flows from light impurities and dust on mobile grain separators by using a rotary cyclone with a multi-disc after cleaner. An increase in the efficiency of the process of cleaning the dusty air flow in dust collectors is provided by an additional effect on dispersed particles for their intensive redistribution in the working areas. The developed rotary cyclone has two working zones: the main zone and the post-cleaning zone. The rotary cyclone consists of a bladed impeller, a main cylindrical channel, a sedimentation chamber and an after-cleaner. The overall air flow purification coefficient of the rotary cyclone varies between 87.5 to 92.5 %.

The development of a country's economy largely depends on the pace and efficiency of construction work, which, in turn, is determined by the extent to which innovative technologies and techniques are used. This work is devoted to justification of the basic parameters and the development of a new working body for a machine for cutting joints in road surfaces. A design with cycloidal motion is proposed, which intensifies the destruction process due to the vibrational impact of the cutters on the material being processed. The use of such a working body provides a vibrational effect, increases the cutting speed, and reduces the energy consumption of the process. As a result of intensifying the interaction between the working body and the material, it was possible to reduce the energy consumption of cutting by 1.13 times, and increase productivity by 1.18 times compared to analogues.

The dependence has been obtained that links the degree of coagulation of soot particles, the parameters of the ultrasonic equipment, the geometric dimensions of the ultrasonic muffler, the frequency characteristics of ultrasound, and the parameters of the engine operating mode. In the paper is presented solving of a problem of determining the number of particles in 1 cm³ of exhaust gas depending on the smoke index. An example of calculating the required ultrasound power for a full-size ultrasonic vehicle muffler bench has been given.