Search Results (90)

In this paper, a route- and environment-aware rule-based energy management system (EMS) strategy for EVs equipped with HESSs consisting of a lithium-ion battery and a supercapacitor is proposed. The proposed rule-based EMS integrates driving mode classification, traffic conditions, road gradient, wind resistance, ambient temperature, and the supercapacitor (SOC) to determine the optimal power-sharing strategy between the battery and the supercapacitor under various driving conditions, including city, highway, and stop-and-go traffic. A mathematical model of the EV powertrain, battery, and supercapacitor is developed. The performance of the proposed rule-based EMS strategy is validated in MATLAB/SIMULINK under three representative driving cycles: the Urban Dynamometer Driving Schedule (UDDS), Artemis Motorway 130, and a Central Business District (CBD) driving cycle. It is shown that the proposed rule-based EMS strategy significantly reduces the battery current stress while increasing supercapacitor usage. Full article

The transport sector plays a significant role in air pollution, and real-world emissions measurements are becoming increasingly important. In this study, emissions from a turbocharged, direct-injection gasoline internal combustion engine (ICE) vehicle and a port fuel injection (PFI) hybrid electric vehicle (HEV) were compared using a portable emissions measurement system (PEMS) under real-world driving conditions. The CO₂, CO, NO_x, and PN emissions of the two vehicles were measured in urban, rural, and motorway sections. HEV CO₂ emissions were ~20% lower than ICE emissions in the entire Real Driving Emissions (RDE) cycle, while in urban operation, they were almost 50% lower. PN emissions were lower for HEV in rural and motorway sections than for ICE, but significant PN peaks occurred during the early urban phase, attributable to the slower engine warm-up of the HEV. Machine learning analysis (Random Forest and Extra Trees Regressor) indicated that coolant temperature was the dominant driver of HEV PN emissions. The results indicate that powertrain characteristics and thermal management strongly influence real-world driving emissions, highlighting their importance for the further development of hybrid vehicles. Full article

The aim of this study is to model traffic noise from the D-100 (a major national highway) and TEM (Trans-European Motorway), a major hub in Türkiye. This study models traffic noise from the D-100 and TEM using SoundPLAN software (NMPB-96 methodology) to identify legal levels and evaluate mitigation strategies. The model was verified locally with absolute errors of 1.3–1.7 dB(A). Impact analyses based on the L_den and Lnight (L_n) indicators have revealed that sensitive areas (e.g., dwellings, schools and hospitals) are exposed to noise levels that considerably exceed legal limits, primarily due to heavy vehicle traffic during the night-time hours. Two different noise mitigation scenarios were applied to the baseline model for addressing noise exposure. As a result, noise levels were reduced by approximately 4 dB(A). The number of residences exposed to excessive noise above 75 dB(A) decreased from 10,898 to 4451 (59%). A significant increase in acoustic comfort is achieved by reducing the number of dwellings in the 70–75 dB(A) contour range during night-time hours. The results indicate the need for integrated traffic management and infrastructure improvements for sustainable urban noise control. Full article

This study presents a replicable diagnostic framework for analysing latent safety vulnerability at complex junctions by integrating UAV-based observation, trajectory extraction, movement-level operational performance modelling, and regulatory benchmarking. Grounded in Vision Zero/Safe System principles, the approach is demonstrated at Junction 50 of the A-66 motorway in Mieres (Spain), a constrained urban interchange where motorway access/egress overlaps with local cross-town movements. Two one-hour UAV datasets were collected during peak periods and processed with GoodVision to extract trajectories, turning-movement counts, origin–destination patterns and recurrent irregular manoeuvres. These outputs were combined with SIDRA INTERSECTION indicators (e.g., LOS, delay and capacity utilisation) and assessed against the Spanish geometric design standard to identify design–operation misalignment, including a targeted 3D sight-distance check at the stop-controlled exit. The results show systematic behavioural adaptations at critical decision points, including informal side-by-side queuing at nominally single-lane exits and queue bypassing via adjacent auxiliary areas, co-occurring with capacity-strained movements (LOS E–F) and normative inconsistencies in lane type/length and channelisation. The framework translates high-resolution behavioural evidence into intervention-relevant outputs (critical movements, concentration zones and explicit design–behaviour mismatches) without relying on crash frequency as the primary signal, supporting proactive prioritisation in constrained legacy layouts. Full article

In this study, we present a machine-learning approach—a land use random forest (LURF) model—to produce daily PM₁₀ concentration maps at a 1 km resolution across the Campania region for the year 2022. The model combines daily measurements from 13 ARPA Campania monitoring stations with a wide set of spatial and atmospheric information. The predictors include population, land cover, road network, ERA5 meteorological data, satellite aerosol observations from MODIS, output from the CHIMERE chemistry transport model, and a flag identifying days affected by Saharan dust transport. The model is trained and validated using a station-based cross-validation scheme that accounts for spatial correlation between sites. Under this scheme, the LURF reproduces observed concentrations with substantially smaller errors than the raw CHIMERE output (RMSE of 11.0 vs. 23.6 $\mathsf{\mu }$g m⁻³). CHIMERE concentrations and ERA5 meteorology emerge as the most informative predictors, while the dust flag specifically improves the representation of episodic high-PM₁₀ events. The resulting 1-km maps reveal clear urban–rural contrasts. They identify pollution hotspots in the Naples metropolitan area and along major motorways that are not visible in coarser model outputs. Probabilistic exceedance maps further show that meeting the future 2030 EU limit value of 20 $\mathsf{\mu }$g m⁻³ will be challenging across much of the metropolitan area. Overall, the proposed framework provides a low-cost, practical tool for high-resolution PM₁₀ exposure assessment, supporting epidemiological studies, environmental justice analyses, and air quality management in regions with complex terrain and limited monitoring coverage. Full article

Although prior research focused on Baghdad has identified variability in fine particulate matter concentrations (PM_2.5) and their origins, there remains uncertainty in the identification of the relative importance of local and long-range PM_2.5 sources. This study analysed hourly air pollutant concentrations and meteorological data from three monitoring sites over the year 2019 in Baghdad, namely Al-Wazeriya (WZ), Al-Andalus Square (AS), and Al-Saiydiya (SA) sites, to determine the nature of PM_2.5 sources. Multi-stage statistical models were utilised to address inherent data limitations and varying sampling dates caused by limitations on power supplies to monitoring equipment, thus improving the identification of urban particulate sources. Bivariate polar plots, concentration ratios, and conditional bivariate probability function (CBPF) plots were used to identify local sources of PM_2.5. Potential Source Contribution Function (PSCF) and concentration weighted trajectory (CWT) methods were employed for distant and regional source apportionment. Domestic diesel generators are suggested to be the primary local source of PM_2.5 pollutants in Baghdad’s WZ area (categorised as residential with significant traffic volumes). Gasoline- and diesel-fueled motor vehicles significantly contribute to PM_2.5 concentrations in the AS and SA areas, which are commercial areas with the latter having close proximity to motorway sources. Additional impacts result from gas flaring and thermal power plants in these regions. Long-range PM_2.5 transport may be attributed to the combustion of low-quality heavy fuel oils from several potential sources, including Nahrawan brick factories, oil fields, and Al-Musayyab thermal power plants, primarily towards the northeast, east, and southeast of Baghdad. Transboundary contributions to PM_2.5 concentrations in Baghdad were also identified, from industrial sources in western Iran and eastern Syria, as well as dust particulates, and oil and gas production from southwestern Iran’s Khuzestan Province, Kuwait, and the Arabian Gulf. Low to medium wind speeds (1–4 ms⁻¹) were linked with the highest source contributions, suggesting local emission sources to be the most significant contributors to high PM_2.5 at the studied sample locations. Full article

This study quantifies the effect of air and fuel filter restriction on fuel consumption, regulated pollutants (CO and HC), and CO₂ greenhouse gas emissions under real driving conditions in a hilly high-altitude environment. Four filter configurations were evaluated: clean air filter–clean fuel filter (CAF–CFF, reference), dirty air filter–clean fuel filter (DAF–CFF), clean air filter–dirty fuel filter (CAF–DFF), and dirty air filter–dirty fuel filter (DAF–DFF). Each test was repeated three times over the same RDE route in Quito (≈2100–2900 m). Fuel consumption was estimated from ECU-based signals, and CO₂ emission factors and regulated pollutant (CO and HC) emission factors were computed from measured exhaust concentrations and distance normalization. Results were analyzed by RDE section (urban, rural, motorway) and expressed as percent changes relative to the reference configuration to directly isolate filter restriction effects. Relative to CAF–CFF, DAF–CFF produced the largest increase in average fuel consumption (+7.2%) and the largest urban CO₂ penalty (+22.7%), indicating a strong efficiency sensitivity to intake restriction under transient operation. CAF–DFF increased average fuel consumption by 6% and produced the strongest motorway penalties for CO (+77.3%) and HC (+44.4%), suggesting that fuel delivery restriction has a stronger influence on incomplete oxidation products under sustained higher load. The combined restriction (DAF–DFF) showed non-additive responses depending on the operating regime. Random Forest models were trained to estimate CO₂, CO, and HC, achieving R² values of 0.8571, 0.8229, and 0.7690, respectively, while multiple linear regression achieved an R² of 0.852 for fuel consumption. The proposed approach supports data-driven monitoring of filter restriction effects under real driving operation, while acknowledging that fuel consumption and CO₂ are obtained through different measurement and conversion paths and may not yield identical percent changes. Full article

Every year, road accidents cause significant human and social losses, posing one of the key challenges for public policy in Poland. The aim of this article is to quantitatively assess the relationship between selected infrastructural and economic conditions and the scale of road accidents in Poland in the period 2010–2024. The analysis was carried out using a log–linear regression model, which allows the results to be interpreted in terms of elasticity. The dependent variable was the total number of road accidents, while the set of explanatory variables included the density of paved roads, the length of expressways and motorways, urban population density, the level of private car ownership, and average gross wages. The results indicate that the development of road infrastructure and an increase in the population’s income contribute to reducing the number of accidents, while the growing number of passenger cars significantly increases the risk of accidents. The estimated model explains approximately 94% of the variation in accident counts (R² = 0.94). The elasticity of passenger car ownership is positive (β = 1.39), indicating increased accident exposure with rising motorization, while paved road density (β = −46.56) and expressways (β = −2.03) show negative elasticities. Average wages are also negatively associated with accidents (β = −4.64). These results quantify the proportional structure of long-term accident dynamics rather than merely confirming directional relationships. The analysis also revealed a negative correlation between urban population density and the number of accidents, which may indicate greater effectiveness of traffic management and control systems in urban areas. The results of the study provide empirical evidence relevant for the development of investment and regulatory strategies in the area of transport infrastructure and road safety. Full article

Road safety remains a critical concern in Poland, where infrastructure development, motorization, urban density, and public transport patterns all influence traffic accident occurrence. This study examines road accidents over the period 2010–2024, using official statistical data from the Polish Central Statistical Office (GUS) and national transport databases. The study examines how road infrastructure, vehicle ownership, population density, and public transport usage relate to traffic accidents in Poland between 2010 and 2024. A log-linear regression model was applied to estimate the elasticities of each factor, allowing interpretation of the expected percentage change in accidents associated with a 1% change in the explanatory variables. The results show that increased density of paved roads and higher urban population density are associated with higher accident numbers, while the expansion of expressways and motorways significantly is associated with lower accident numbers. Greater motorization also increases accident risk, whereas higher public transport usage has a modest mitigating effect. Bus and trolleybus operations slightly increase exposure, while tram mileage shows a negligible decrease in accidents. Results show that paved road density and urban density tend to increase accidents, while expressways reduce them. Policy implications include the importance of balancing infrastructure development with traffic management, promoting public transport, and addressing urban density to reduce accident risk. The study highlights the need for integrated approaches to improve road safety and provides a quantitative basis for evidence-informed transportation planning. Full article

Road transport systems are central to sustainable mobility and the energy transition because they account for a large share of final energy use and remain heavily dependent on fossil fuels. With more than 90% of transport energy still supplied by petroleum-based fuels, improving energy efficiency and reducing emissions in road networks has become a strategic priority. This review compares Australia, Hong Kong, and the United Kingdom to examine how road-design standards and emerging digital technologies can improve energy performance across planning, design, operations, and maintenance. Using Australia’s Austroads Guide to Road Design, Hong Kong’s Transport Planning and Design Manual (TPDM), and the UK’s Design Manual for Roads and Bridges (DMRB) as core reference frameworks, we apply a rubric-based document analysis that codes provisions by mechanism type (direct, indirect, or emergent), life-cycle stage, and energy relevance. The findings show that energy-relevant outcomes are embedded through different pathways: TPDM most strongly supports urban operational efficiency via coordinated/adaptive signal control and public-transport prioritization; DMRB emphasizes strategic-network flow stability and whole-life carbon governance through managed motorway operations and life-cycle assessment requirements; and Austroads provides context-sensitive, performance-based guidance that supports smoother operations and active travel, with implementation varying by jurisdiction. Building on these results, the paper proposes an AI-enabled benchmarking overlay that links manual provisions to comparable energy and carbon indicators to support cross-jurisdictional learning, investment prioritization, and future manual revisions toward safer, more efficient, and low-carbon road transport systems. Full article

The article presents the development and results of emission studies conducted in Poland in the context of global real-driving emissions research. Although the European Union has continuously tightened exhaust-emission standards, road transport remains one of the major sources of air pollution. Several research centers in Poland—including Rzeszów University of Technology, Poznan University of Technology, and the Motor Transport Institute—have been conducting on-road emission measurements for many years across a wide spectrum of vehicles: conventional, hybrid (including plug-in hybrids), and fully electric. The findings show that emissions under real-world driving conditions often differ from those obtained in homologation tests, particularly for nitrogen oxides and particulate matter. Ambient temperature, road gradient, and driving phases (urban, rural, motorway) were also identified as influential factors. Polish research centers have developed analytical tools enabling comparison between laboratory and on-road tests and allowing real-driving emissions to be estimated based on chassis-dynamometer data. Studies on plug-in hybrids highlighted that these vehicles remain environmentally beneficial only when regularly charged; otherwise, their emissions can increase sharply. Overall, the research confirms that on-road testing is essential for a reliable evaluation of vehicle performance, and the results can contribute to designing more eco-friendly technologies and improving future emission regulations. Full article

Road transport constitutes a crucial element of the European economy, but it also generates significant external costs. In the process of reducing the impact of road transport on the environment and society, numerous actions are being undertaken to implement the concept of sustainable transport development in the Member States of the European Union. A key measure in this area is the introduction of low- and zero-emission propulsion systems in vehicles intended for passenger and freight transport. This article focuses on electric vehicles powered by battery energy storage systems. An essential component of these efforts is the development of alternative fuels infrastructure, which is expected to enable the operation of such vehicles by providing access to battery charging facilities. The development of infrastructure in the form of electric vehicle charging stations, initially concentrated in urban areas, has been extended to the network of European roads. The driving force behind this expansion is the European Parliament and the Council of the EU, which, on the basis of the Alternative Fuels Infrastructure Regulation (AFIR), stimulate the development of alternative fuels infrastructure along the TEN-T network. The aim of the article is to present selected challenges related to the electrification of road transport infrastructure in the context of the sustainable transport development concept and the construction of alternative fuels infrastructure along the TEN-T network. The research focuses on forecasting the demand for alternative fuels infrastructure along the A1 and A2 motorways, which form part of the TEN-T network within the territory of Poland. The research process stems from the implementation of the AFIR in the EU Member States. Full article

The typical ranges available for electric vehicles (EVs) may be considered by users to be inadequate when compared to long, real-life trips, and charging operations may need to be planned along journeys. To evaluate the compatibility between vehicle features and charging options for realistic journeys performed by car, a simulation approach is proposed here, using travel data collected from real vehicles to obtain trip chains for multiple consecutive days. Car travel activities, including stops with the option of charging, were simulated by applying an agent-based approach. Charging operations can be integrated into trip chains for user activities, assuming that they remain unchanged in the event that vehicles switch to electric. The energy consumption of the analyzed trips, disaggregated by vehicle type, was estimated using the average travel speed, which is useful for capturing the main route features (ranging from urban to motorways). Data were recorded for approximately 25,000 vehicles in the Turin Metropolitan Area for six consecutive days. Market segmentation of the vehicles was introduced to take into consideration different energy consumption rates and charging times, given that the electric power, battery size, and consumption rate can be related to the vehicle category. Charging activities carried out using public infrastructure during idle time between consecutive trips, as well as those carried out at home or work, were identified in order to model different needs. Full article

Although particulate matter (PM) pollution from vehicles’ exhaust has decreased significantly over the years, the contribution from non-exhaust sources (brakes, tyres) has remained at the same levels. In the European Union (EU), Euro 7 regulation introduced PM limits for vehicles’ brake systems. Regenerative braking, i.e., recuperation of the deceleration kinetic and potential energy to the vehicle battery, is one of the strategies to reduce the brake emission levels and improve vehicle efficiency. According to the regulation, the shares of friction and regenerative braking can be determined with actual testing of the vehicle on a chassis dynamometer. In this study we tested the regenerative capabilities of a plug-in hybrid vehicle, both in the laboratory and on the road, under different protocols (including both smooth and aggressive braking) and covering a wide range of driving conditions (urban, rural, motorway) over 10,000 km of driving. Good agreement was obtained between laboratory and on-road tests, with the use of the friction brakes being on average 7% and 5.3%, respectively. However, at the same time it was demonstrated that the friction braking share can vary over a wide range (up to around 30%), depending on the driver’s behaviour. Full article

Forests are increasingly under pressure due to rapid population growth, unplanned urbanization, and the conversion of forest land for non-forestry uses. In Istanbul, large-scale infrastructure projects—including a major airport, motorways, and a bridge—constructed in forested northern regions have led to significant land use change, generating complex social and environmental impacts. This study examines how local populations perceive the social consequences of these projects. Data were collected through 995 questionnaires across 25 neighborhoods and semi-structured interviews with 18 neighborhood headmen and 5 representatives from NGOs and professional organizations. Exploratory factor analysis was used to categorize perceptions, and Mann–Whitney U tests assessed differences based on proximity to project sites and project type. The findings indicate that both proximity and project type play a key role: residents living closer to the projects—and particularly those living near the airport—report more negative impacts, including feelings of insecurity, increased accident risk, limited employment opportunities, loss of forest, agricultural, and pasture lands, heightened environmental, noise, and air pollution, as well as adverse effects on physical and mental health. Measuring and mitigating these impacts during and after the projects is essential. Properly conducted, audited, and effective social impact assessments are of vital importance for the local people living around the project. Full article