Alica Kalašová

Passenger car unit (PCU) values are an essential input for traffic capacity assessment (TCA) of intersections, as they allow different vehicle categories to be converted into a common unit. In the Slovak Republic, current technical guidelines use fixed equivalency factors for specific intersection types. However, international research shows that PCU values depend on local traffic conditions, vehicle composition, road geometry, and vehicle interactions. Incorrectly selected factors may therefore lead to inaccurate capacity calculations and misleading conclusions regarding intersection performance. This study analyses PCU values for different vehicle categories, with a focus on heavy vehicles (HV) at roundabouts and turbo roundabouts (TR). Traffic surveys were conducted at selected intersections near industrial areas, where a higher proportion of freight traffic was expected. Manual and semi-automatic turning-movement counts were combined with high-resolution video recordings and automatic traffic counters (ATC) to obtain data on traffic volumes, vehicle composition, travel times, speeds, vehicle lengths, and time headways. The results indicate that the behavior of trucks and HV combinations may differ from the assumptions reflected in static equivalency factors. In several cases, the measured travel times and time headways did not reach the values implied by the prescribed PCU coefficients. Based on these findings, a methodology for dynamically determining PCU values was proposed. The methodology is based on the time headway principle and uses commonly available measurement devices. The proposed approach enables PCU values to be determined for either a simplified two-category vehicle classification or a more detailed classification. It may serve as an alternative to static tabulated values, particularly under non-standard traffic composition, a high proportion of HV, or specific geometric conditions of intersections.

This study examines the potential effect of hypothetical Urban Air Mobility (UAM) demand redistribution on congestion and signalized intersection performance in the urban environment of Topoľčany, Slovakia. Based on a calibrated microsimulation model, scenarios involving the redistribution of a portion of ground traffic demand away from the road network were analyzed at 30% and 50% during the morning peak period. The evaluation focused primarily on travel times and intersection load. The results indicate that a moderate reduction in ground traffic demand leads to a significant reduction in travel times and traffic intensity. The most substantial improvement was observed in the 30% redistribution scenario. In comparison, a further increase to 50% did not yield proportional benefits, suggesting a nonlinear threshold effect in the transport system’s performance. It should be emphasized that the UAM scenarios in this study do not represent a full operational simulation of Urban Air Mobility, including aerial corridors, vertiports, waiting times, intermodal transfers, or airspace capacity. Instead, they represent demand redistribution scenarios used to evaluate the response of the existing signalized road network to reduced ground traffic demand. The study identifies limitations arising from simplified model assumptions and the absence of broader environmental, operational, and social considerations. Nevertheless, the findings show that even a moderate reduction in road traffic demand, potentially associated with future multimodal mobility concepts, can contribute to improved traffic efficiency in congested urban networks.

Vehicle restrictions on urban expressways are widely used to relieve traffic congestion and reduce traffic emissions. However, the effects of such restrictions should be assessed over the wider urban road network rather than on expressways alone, and over both short-run and longer-run periods. This study empirically investigates the impacts of vehicle restriction policies on network-level emissions in Shanghai. The network-level vehicle emissions are dynamically estimated using a carbon-emissions macroscopic fundamental diagram (CE-MFD) model based on taxi trajectory data and loop detector data. The effects are then identified using a spatial difference-in-differences (SDID) framework, while geographically weighted regression (GWR) is used to examine spatial heterogeneity in the associated factors. The results show that extending the restriction periods reduced carbon emissions across the urban road network by 9.96% after one month and by 17.93% after one year. The effects are spatially heterogeneous and are associated with population, road-network characteristics, parking supply, and ramp configuration. These findings suggest that the sustainability impacts depend not only on the restrictions themselves, but also on traffic redistribution and local network conditions. Findings provide empirical evidence for designing sustainability-oriented traffic strategies, underscoring the importance of evaluating emissions outcomes across the urban road network over both short-run and longer-run horizons.

This paper evaluates the operational and safety performance of a conventional single-lane roundabout (SLR) and a turbo roundabout (TR) using a mixed-methods approach. Field traffic counts and turning-movement matrices were collected at the studied intersection in Pezinok (Slovakia). The article describes capacity calculations according to national guidelines (TP 100 and TP 102) and the development of a calibrated and validated microsimulation model. Alternative designs—the existing SLR and a proposed TR conversion—were compared under observed morning and afternoon peak-hour conditions. Performance was assessed using standard operational indicators (delay, queue length, degree of saturation) and qualitative consideration of conflict points and weaving behavior. Simulation results for the case study indicate that the TR design reduced average delays and queue lengths and removed internal weaving compared with the SLR for the tested traffic distributions. However, the observed benefits are conditional: they depend on traffic volumes and turning-movement patterns, and may be reduced under very high total flows or when pedestrian and cyclist impacts are significant. Implications for applicability and limitations of TRs are discussed.

Accurate traffic modeling is essential for effective urban mobility planning within Smart Cities. Conventional capacity assessment methods assume rule-based driver behavior and therefore neglect psychological priority, an informal interaction in which drivers negotiate right-of-way contrary to traffic regulations. This study investigates how the absence of this behavioral factor affects the accuracy of delay and capacity evaluation at unsignalized intersections. A 12 h field observation was conducted at an intersection in Prešov, Slovakia, and 28 driver interactions were analyzed using linear regression modeling. The derived model (R² = 0.83, p < 0.05) demonstrates that incorporating psychological priority significantly improves the agreement between calculated and observed waiting times. Unrealistic results occurring under oversaturated conditions in standard methodologies were eliminated. The findings confirm that behavioral variability has a measurable impact on traffic performance and should be reflected in analytical and simulation models. Integrating these behavioral parameters into Smart City traffic modeling contributes to more realistic and human-centered decision-making in intersection design and capacity management, supporting the development of safer and more efficient urban mobility systems.

This study investigates the accuracy of traffic flow and speed measurements using two radar-based devices, Sierzega and SDR, against manual video-based traffic counts. The measurements were conducted over a 12-h period on a congested urban road section characterized by variable traffic conditions and frequent vehicle stops. The results revealed that the SDR device generally provided lower deviations compared to manual counting, especially in measuring traffic flow. In contrast, the Sierzega device demonstrated greater and more inconsistent deviations, particularly in vehicle categorization and traffic density estimation. The observed discrepancies were primarily attributed to vehicle stopping and queuing, influencing length estimation and classification errors. Despite these limitations, SDR provided sufficient accuracy for practical applications, such as monitoring traffic trends or supporting long-term traffic planning in urban environments.

Countries in the EU, as part of the Paris Agreement, committed to achieving EU climate neutrality by 2050. To meet this goal, the EU aims to reduce its net greenhouse gas emissions across the entire economy by at least 55 % by 2030 compared to 1990 levels, continuing the reduction of emissions until 2050. The transport sector, responsible for a quarter of EU greenhouse gas emissions, must transform, requiring a 90 % reduction in greenhouse gas emissions by 2050. It is crucial to enhance the efficiency of both personal and freight transport in the EU and reduce dependence on fossil fuels. Our paper presents the cost calculation results of using electric vehicles with a total weight of up to 3.5 tons in the courier services sector, compared to conventional vehicles. Based on our analysis, electric vehicle usage is effective and environmentally beneficial. However, BEVs (battery electric vehicles) have higher acquisition costs than ICEVs (internal combustion engine vehicles). This paper analyses the vehicle fleet of a significant courier company. Thanks to their data, it was possible to provide a closer look at the economic efficiency of BEV in courier services.

This paper examines how the unidirectional alignment of a selected street affects traffic load at nearby signal-controlled intersections. Using the Aimsun 8 simulation model, the intersections in the city of Topoľčany were evaluated. A simulation model was created based on a traffic survey conducted by video detection at selected signal-controlled intersections. Both the negative and positive impacts of this modification were analyzed. This study shows a significant deterioration in the traffic situation. This paper further investigates the improvement achieved through corrective measures such as implementing an actuated control plan, modifying signal plans, and coordinating traffic flows. The results show the effectiveness of these measures in reducing congestion and improving traffic flow. They also serve as a foundation for optimizing traffic systems and implementing measures to improve urban mobility.

This study focuses on optimizing traffic flow at uncontrolled intersections by comparing the effectiveness of different intersection types: roundabouts, signal-controlled intersections, and turbo-roundabouts. The purpose is to determine which type offers the best solution for enhancing traffic efficiency, reducing delays, and improving safety. The research employs simulation-based modeling to analyze traffic performance under varying traffic conditions. Critical parameters such as vehicle flow rate, average delay time, and capacity are used to assess the performance of each intersection type. The results indicate that turbo-roundabouts outperform conventional roundabouts and signal-controlled intersections in terms of both capacity and reduction in delays. The findings suggest that implementing turbo-roundabouts at high-traffic intersections can significantly improve traffic flow and reduce congestion. However, the effectiveness of each solution is context-dependent, with signal-controlled intersections still being advantageous under specific conditions, particularly in highly urbanized areas. This study provides valuable insights for transportation planners and engineers, highlighting the importance of intersection design in traffic optimization.