Search Results (456)

Traffic congestion in large-scale road networks significantly impacts urban sustainability. Traditional traffic signal control methods lack adaptability to dynamic traffic conditions. Recently, deep reinforcement learning (DRL) has emerged as a promising solution for optimizing signal control. This study proposes a Multi-Agent Deep Reinforcement Learning (MADRL) framework for large-scale traffic signal control. The framework employs spatio-temporal attention networks to extract relevant traffic patterns and a hierarchical reinforcement learning strategy for coordinated multi-agent optimization. The problem is formulated as a Markov Decision Process (MDP) with a novel reward function that balances vehicle waiting time, throughput, and fairness. We validate our approach on simulated large-scale traffic scenarios using SUMO (Simulation of Urban Mobility). Experimental results demonstrate that our framework reduces vehicle waiting time by 25% compared to baseline methods while maintaining scalability across different road network sizes. The proposed spatio-temporal multi-agent reinforcement learning framework effectively optimizes large-scale traffic signal control, providing a scalable and efficient solution for smart urban transportation. Full article

Traditional Pavement Condition Index (PCI) assessments are highly resource-intensive, demanding substantial time and labor while generating significant carbon emissions through extensive field operations. To address these sustainability challenges, this research presents an innovative methodology utilizing Gene Expression Programming (GEP) to determine PCI values based on International Roughness Index (IRI) measurements from Iraqi road networks, offering an environmentally conscious and resource-efficient approach to pavement management. The study incorporated 401 samples of IRI and PCI data through comprehensive visual inspection procedures. The developed GEP model exhibited exceptional predictive performance, with coefficient of determination (R²) values achieving 0.821 for training, 0.858 for validation, and 0.8233 overall, successfully accounting for approximately 82–85% of PCI variance. Prediction accuracy remained robust with Mean Absolute Error (MAE) values of 12–13 units and Root Mean Square Error (RMSE) values of 11.209 and 11.00 for training and validation sets, respectively. The lower validation RMSE suggests effective generalization without overfitting. Strong correlations between predicted and measured values exceeded 0.90, with acceptable relative absolute error values ranging from 0.403 to 0.387, confirming model effectiveness. Comparative analysis reveals GEP outperforms alternative regression methods in generalization capacity, particularly in real-world applications. This sustainable methodology represents a cost-effective alternative to conventional PCI evaluation, significantly reducing environmental impact through decreased field operations, lower fuel consumption, and minimized traffic disruption. By streamlining pavement management while maintaining assessment reliability and accuracy, this approach supports environmentally responsible transportation systems and aligns contemporary sustainability goals in infrastructure management. Full article

This study examines the safety and cost-effectiveness of implementing shoulder rumble strips (SRS) and road lighting on Saudi Arabian freeways, providing insights into their roles in fostering sustainable transport systems. By leveraging the Highway Safety Manual (HSM) framework, this research develops localized Crash Modification Factors (CMFs) for these interventions, ensuring evidence-based and context-specific evaluations. Data were collected for two periods—pre-pandemic (2017–2019) and post-pandemic (2021–2022). For each period, we obtained traffic crash records from the Saudi Highway Patrol database, traffic volume data from the Ministry of Transport and Logistic Services’ automated count stations, and roadway characteristics and pavement-condition metrics from the National Road Safety Center. The findings reveal that SRS reduces fatal and injury run-off-road crashes by 52.7% (CMF = 0.473) with a benefit–cost ratio of 14.12, highlighting their high cost-effectiveness. Road lighting, focused on nighttime crash reduction, decreases such crashes by 24% (CMF = 0.760), with a benefit–cost ratio of 1.25, although the adoption of solar-powered lighting systems offers potential for greater sustainability gains and a higher benefit–cost ratio. These interventions align with global sustainability goals by enhancing road safety, reducing the socio-economic burden of crashes, and promoting the integration of green technologies. This study not only provides actionable insights for achieving KSA Vision 2030’s target of improved road safety but also demonstrates how engineering solutions can be harmonized with sustainability objectives to advance equitable, efficient, and environmentally responsible transportation systems. Full article

Water migration occurs in unsaturated loess subgrade due to extreme rainfall, making it prone to subgrade subsidence and other water damage disasters, which seriously impact road safety and sustainable development of the Loess Plateau. The study performed a rainfall test using a compacted loess subgrade model based on a self-developed water migration test device. The effects of extreme rainfall on the water distribution, wetting front, and infiltration rate in the subgrade were systematically explored by setting three rainfall intensities (4.6478 mm/h, 9.2951 mm/h, and 13.9427 mm/h, namely J1 stage, J2stage, and J3 stage), and a lateral water migration model was proposed. The results indicated that the range of water content change areas constantly expands as rainfall intensity and time increase. The soil infiltration rate gradually decreased, and the ratio of surface runoff to infiltration rainfall increased. The hysteresis of lateral water migration refers to the physical phenomenon in which the internal water response of the subgrade is delayed in time and space compared to changes in boundary conditions. The sensor closest to the side of the slope changed first, with the most significant fluctuations. The farther away from the slope, the slower the response and the smaller the fluctuation. The bigger the rainfall intensity, the faster the wetting front moved horizontally. The migration rate at the slope toe is the highest. The migration rate of sensor W3 increased by 66.47% and 333.70%, respectively, in the J3 stage compared to the J2 and J1 stages. The results of the model and the measured data were in good agreement, with the R² exceeding 0.90, which verifies the reliability of the model. The study findings are important for guiding the prevention and control of disasters caused by water damage to roadbeds in loess areas. Full article

Glass microspheres are essential components in horizontal road markings due to their retroreflective properties, enhancing visibility and safety under low-light conditions. Traditionally produced from soda-lime glass made with high-purity silica from sand, their manufacturing raises environmental concerns amid growing global sand scarcity. This study explores the viability of rice husk ash (RHA)—a high-silica byproduct of rice processing—as a sustainable raw material for microsphere fabrication. A glass composition containing 70 wt% SiO₂ was formulated using RHA and melted at 1500 °C. Microspheres were produced through flame spheroidization and characterized following the Brazilian standard NBR 16184:2021 for Type IB beads. The RHA-derived microspheres exhibited high sphericity, appropriate size distribution (63–300 μm), density of 2.42 g/cm³, and the required acid resistance. UV-Vis analysis confirmed their optical transparency, and the refractive index was measured as 1.55 ± 0.03. Retroreflectivity tests under standardized conditions revealed performance comparable to commercial counterparts. These results demonstrate the technical feasibility of replacing conventional silica with RHA in glass microsphere production, aligning with circular economy principles and promoting sustainable infrastructure. Given Brazil’s significant rice production and corresponding RHA availability, this approach offers both environmental and socio-economic benefits for road safety and material innovation. Full article

Traditional stabilization techniques, such as lime and cement, widely used for their effectiveness, albeit with economic and environmental limitations, are leading to the search for sustainable approaches that utilize agricultural and industrial waste, such as rice husk ash, bagasse, and natural fibers. These have been shown to improve key geotechnical properties, even under saturated conditions, significantly. In particular, the combination of rice husk ash and recycled ceramics has shown notable results in Ecuadorian coastal soils. The article emphasizes the importance of selecting techniques that balance effectiveness, cost, and sustainability and identifies existing limitations, such as the lack of long-term data (ten years) and predictive models adapted to the Ecuadorian climate. From a bibliographic perspective, this article analyzes the challenges posed by expansive soils in the western coastal region of Ecuador, whose high plasticity and instability to moisture negatively affect civil works such as roads and buildings. The Ecuadorian clay contained 30% kaolinite and only 1.73% CaO, limiting its chemical reactivity compared to soils such as Saudi Arabia, which contained 34.7% montmorillonite and 9.31% CaO. Natural fibers such as jute, with 85% cellulose, improved the soil’s mechanical strength, increasing the UCS by up to 130%. Rice husk ash (97.69% SiO₂) and sugarcane bagasse improved the CBR by 90%, highlighting their potential as sustainable stabilizers. All of this is contextualized within Ecuador’s geoenvironmental conditions, which are influenced by climatic phenomena such as El Niño and La Niña, as well as global warming. Finally, it is proposed to promote multidisciplinary research that fosters more efficient and environmentally responsible solutions for stabilizing expansive soils. Full article

The use of chloride-based deicing salts, particularly sodium chloride (NaCl) and calcium chloride (CaCl₂), is a common practice in cold regions for maintaining road safety during winter. However, the accumulation of salt residues in adjacent soils poses serious environmental threats, including reduced pH, increased electrical conductivity (EC), disrupted soil structure, and plant growth inhibition. This study aimed to evaluate the combined effect of activated carbon (AC) and Pennisetum alopecuroides, a salt-tolerant perennial grass, in alleviating salinity stress under deicer-treated soils. A factorial greenhouse experiment was conducted using three fixed factors: (i) presence or absence of Pennisetum alopecuroides, (ii) deicer type (NaCl or CaCl₂), and (iii) activated carbon mixing ratio (0, 1, 2, 5, and 10%). Soil pH, EC, and ion concentrations (Na⁺, Cl⁻, Ca²⁺) were measured, along with six plant growth indicators. The results showed that increasing AC concentrations significantly increased pH and reduced EC and ion accumulation, with the 5% AC treatment being optimal in both deicer systems. Plant physiological responses were improved in AC-amended soils, especially under CaCl₂ treatment, indicating less ion toxicity and better root zone conditions. The interaction effects between AC, deicer type, and plant presence were statistically significant (p < 0.05), supporting a synergistic remediation mechanism involving both adsorption and biological uptake. Despite the limitations of short-term controlled conditions, this study offers a promising phytomanagement strategy using natural adsorbents and salt-tolerant plants for sustainable remediation of salt-affected soils in road-adjacent and urban environments. Full article

The cold recycling (CR) technique is gaining traction, with an increasing demand for sustainable pavement construction practices. Cold in-place recycling (CIR) and cold central plant recycling (CCPR) are two strategies under the umbrella of cold recycling. These techniques use reclaimed asphalt pavement (RAP) to rehabilitate pavement, and CCPR offers the added advantage of utilizing stockpiled RAP. While many agencies have expertise in cold recycling techniques including CCPR, the lack of pavement performance data prevented the largescale implementation of these technologies. Recent studies in high-traffic volume applications demonstrate that CCPR technology can be implemented on the entire road network across all traffic levels. This reignited interest in the widespread implementation of CCPR. Therefore, the purpose of this study is to provide agencies with the most up-to-date information on CCPR to help them make informed decisions. To this end, this paper comprehensively reviews the mix-design for CCPR, the structural design of pavements containing CCPR layers, best construction practices, and the agency experience in using this technology on high-traffic volume roads to provide in-depth information on the steps to follow from project selection to field implementation. The findings specify the suitable laboratory curing conditions to achieve the optimum mix design and specimen preparation procedures to accurately capture the material properties. Additionally, this review synthesizes existing quantitative data from previous studies, providing context for the comparison of findings, where applicable. The empirical and mechanistic–empirical design inputs, along with the limitations of AASHTOWare Pavement ME software for analyzing this non-conventional material, are also presented. Full article

Urban road traffic congestion poses significant challenges to sustainable mobility in smart cities. Traditional traffic light systems, reliant on static or semi-fixed timers, fail to adapt to dynamic traffic conditions, exacerbating congestion and limiting inclusivity. To address these limitations, this paper proposes H-ATLM (a hybrid adaptive traffic lights management), a system utilizing the deep deterministic policy gradient (DDPG) reinforcement learning algorithm to optimize traffic light timings dynamically based on real-time data. The system integrates advanced sensing technologies, such as cameras and inductive loops, to monitor traffic conditions and adaptively adjust signal phases. Experimental results demonstrate significant improvements, including reductions in congestion (up to 50%), increases in throughput (up to 149%), and decreases in clearance times (up to 84%). These findings open the door for integrating accessibility-focused features such as adaptive signaling for accessible vehicles, dedicated lanes for paratransit services, and prioritized traffic flows for inclusive mobility. Full article

Road infrastructure is the foundation of the predominant modes of transport, and its effective management is crucial to meet mobility needs. Although necessary for reconstruction, maintenance, and expansion projects, roadworks produce negative impacts, resulting in further risk for workers and drivers and failing to ensure sustainable development. The objective of this paper is twofold: Firstly, investigate the contributing factors to the occurrence of crashes in roadworks. Secondly, develop a model to estimate crash numbers in these areas. The results, which could support municipalities at the planning stage and implement policies for safe and sustainable development, are achieved by examining 121 sites, where 549 crashes occurred, and 25 contributing factors. The variables are divided into three categories: technical characteristics of the site, infrastructural, and environmental. Besides the conventional variables, a risk-increasing factor is calibrated. It assesses the impact of roadworks according to the manoeuvres imposed and the number of lanes. Consistent with previous findings, several variables related to the work zone layout, traffic conditions, infrastructure, and surrounding environment are correlated with the crash number. After performing a further statistical analysis, a multiple linear regression model, statistically significant (0.000) and suitable for accurately estimating the possible number of crashes (R²_adj = 0.41), is determined. Full article

The transport industry in the European Union plays a key role in the economy. However, due to persistent political, social, and technological changes, examining optimization strategies in transportation has become a crucial task to minimize expenditure, promote sustainable solutions, and address environmental degradation concerns. This study analyzes the effectiveness of a new truck trailer design, adapted from existing European models, which improves load capacity through an extended trailer length. The increased length (and, by extension, volume) is expected to reduce the number of vehicles for freight transportation, thereby improving road congestion and reducing environmental impacts, which include GHG emissions and overall carbon footprint. To achieve this objective, a comprehensive analysis of current European regulations on articulated vehicles and road trains was carried out, alongside a review of related case studies implemented or under development across the European Union member states. Additionally, a pilot study was conducted using the proposed 18 m semi-trailer across 14 real-life freight routes involving loads from several suppliers and manufacturers. This study therefore demonstrates the economic benefits and reduction in pollutant emissions related to the extended design and evaluates its impact on road infrastructure conditions, given the total length of 20.55 m. Full article

This article presents the design, implementation, and validation of a Remotely Piloted Safety Cone (RPSC), an autonomous robotic system developed to enhance safety and operational efficiency in road maintenance. The RPSC addresses challenges associated with road works, including workers’ exposure to traffic hazards and inefficiencies of traditional traffic cones, such as manual placement and retrieval, limited visibility in low-light conditions, and inability to adapt to dynamic changes in work zones. In contrast, the RPSC offers autonomous mobility, advanced visual signalling, and real-time communication capabilities, significantly improving safety and operational flexibility during maintenance tasks. The RPSC integrates sensor fusion, combining Global Navigation Satellite System (GNSS) with Real-Time Kinematic (RTK) for precise positioning, Inertial Measurement Unit (IMU) and encoders for accurate odometry, and obstacle detection sensors within an optimised navigation framework using Robot Operating System (ROS2) and Micro Air Vehicle Link (MAVLink) protocols. Complying with European regulations, the RPSC ensures structural integrity, visibility, stability, and regulatory compliance. Safety features include emergency stop capabilities, visual alarms, autonomous safety routines, and edge computing for rapid responsiveness. Field tests validated positioning accuracy below 30 cm, route deviations under 15 cm, and obstacle detection up to 4 m, significantly improved by Kalman filtering, aligning with digitalisation, sustainability, and occupational risk prevention objectives. Full article

With China’s emergence as a major global economy, its involvement in tackling climate change and fostering sustainable growth has garnered considerable focus. What impact does global direct investment have on carbon emissions within Belt and Road economies? This study innovatively utilizes a quantile regression model to analyze the varied impacts of international direct investment across distinct carbon emission quantiles, further delving into the conditional probability distribution of the dependent variable to provide a strong theoretical basis for precise policy-making by relevant departments and integrating time and space delays in examining the effects of carbon reduction strategies within the Belt and Road Initiative. Furthermore, this study aims to concentrate its research efforts on the host nations. Findings from this study indicate that global direct investments could escalate carbon emissions in economies with lower carbon emissions; yet, with the rise in the host nation’s carbon emissions, the ripple effect of international direct investments in green technology becomes increasingly evident. Empirical evidence indicates that global direct investment in Belt and Road economies demonstrates a significant mitigating effect on carbon emissions, thereby amplifying the decarbonization benefits associated with such cross-border capital flows. Full article

The article presents a new method of passive dynamic weighing of vehicles based on the registration of seismic signals that occur when wheels pass through strips specially applied to the road surface. Signal processing is carried out using spectral methods, including fast Fourier transform, consistent filtering, and regularization methods for solving inverse problems. Special attention is paid to the use of linear-frequency-modulated signals, which make it possible to distinguish the responses of individual axes even when superimposed. Field tests were carried out on a real section of the road, during which signals from vehicles of various classes were recorded using eight geophones. The average error in determining the speed of 1.2 km/h and the weight of 8.7% was experimentally achieved, while the correct determination of the number of axles was 96.5%. The results confirm the high accuracy and sustainability of the proposed approach with minimal implementation costs. It is shown that this system can be scaled up for use in intelligent transport systems and applied in real traffic conditions without the need to intervene in the design of the roadway. Full article

The application of superhydrophobic (SH) coatings in road construction has attracted growing attention due to their potential to improve surface durability, reduce cracking, and enhance skid resistance. Among various materials, SiO₂ nanoparticles have emerged as key components in SH coatings by contributing essential surface roughness and hydrophobicity. This review paper analyzes the role of SiO₂ nanoparticles in enhancing the water-repellent properties of coatings applied to road surfaces, particularly concrete and asphalt. Emphasis is placed on their influence on road longevity, reduced maintenance, and overall performance under adverse weather conditions. Furthermore, this review compares functionalization techniques for SiO₂ using different hydrophobic modifiers, evaluating their efficiency, cost effectiveness, and scalability for large-scale infrastructure. In addition to highlighting recent advancements, this study discusses persistent challenges—including environmental compatibility, mechanical wear, and long-term durability—that must be addressed for practical implementation. By offering a critical assessment of current approaches and future prospects, this short review aims to guide the development of robust, high-performance SH coatings for sustainable road construction. Full article