Search Results (334)

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

Traffic congestion poses a significant challenge to modern urban environments, impacting both driver satisfaction and road safety. This paper investigates the effectiveness of a smart traffic light system (STL), a solution developed under the Intelligent Transportation System (ITS) initiative by the Ministry of Works Malaysia, to address these issues in Malaysia. The system integrates a network of sensors, AI-enabled cameras, and Automatic Number Plate Recognition (ANPR) technology to gather real-time data on traffic volume and vehicle classification at congested intersections. This data is utilized to dynamically adjust traffic light timings, prioritizing traffic flow on heavily congested roads while maintaining safety standards. To evaluate the system’s performance, a comprehensive study was conducted at a selected intersection. Traffic patterns were automatically analyzed using camera systems, and the performance of the STL was compared to that of traditional traffic signal systems. The average travel time from the start to the end intersection was measured and compared. Preliminary findings indicate that the STL significantly reduces travel times and improves overall traffic flow at the intersection, with average travel time reductions ranging from 7.1% to 28.6%, depending on site-specific factors. While further research is necessary to quantify the full extent of the system’s impact, these initial results demonstrate the promising potential of STL technology to enhance urban mobility and more efficient and safer roadways by moving beyond traditional traffic signal functionalities. Full article

Effective maintenance and management of road infrastructure are essential for community well-being, economic stability, and cost efficiency. Well-maintained roads reduce accident risks, improve safety, shorten travel times, lower vehicle repair costs, and facilitate the flow of goods, all of which positively contribute to GDP and economic development. Accurate intersection mapping forms the foundation of effective road asset management, yet traditional manual digitization methods remain time-consuming and prone to gaps and overlaps. This study presents an automated computational geometry solution for precise road intersection mapping that eliminates common digitization errors. Unlike conventional approaches that only detect intersection positions, our method systematically reconstructs complete intersection geometries while maintaining topological consistency. The technique combines plane surveying principles (including line-bearing analysis and curve detection) with spatial analytics to automatically identify intersections, characterize their connectivity patterns, and assign unique identifiers based on configurable parameters. When evaluated across multiple urban contexts using diverse data sources (manual digitization and OpenStreetMap), the method demonstrated consistent performance with mean Intersection over Union greater than 0.85 and F-scores more than 0.91. The high correctness and completeness metrics (both more than 0.9) confirm its ability to minimize both false positive and omission errors, even in complex roadway configurations. The approach consistently produced gap-free, overlap-free outputs, showing strength in handling interchange geometries. The solution enables transportation agencies to make data-driven maintenance decisions by providing reliable, standardized intersection inventories. Its adaptability to varying input data quality makes it particularly valuable for large-scale infrastructure monitoring and smart city applications. Full article

Battery electric vehicles (BEVs) are seeing widespread adoption globally due to technological improvements, lower manufacturing costs, and supportive policies aimed at reducing greenhouse gas emissions. Governments have introduced incentives such as purchase subsidies and investments in charging infrastructure, while automakers continue to broaden their electric vehicle portfolios. Although BEVs show high overall safety performance comparable to internal combustion engine vehicles (ICEVs), they also raise distinct safety challenges that merit policy attention. This review synthesizes the current literature on safety concerns associated with BEVs, with particular attention to fire risks, vehicle weight, low-speed noise levels, and unique driving characteristics. Fire safety remains a significant issue, as lithium-ion battery fires, although less frequent than those in ICEVs, tend to be more severe and difficult to manage. Strategies such as improved thermal management, fire enclosures, and standardized response protocols are essential. BEVs are typically heavier than ICEVs, affecting crash outcomes and braking performance. These risks are especially important for interactions with pedestrians and smaller vehicles. Quiet operation at low speeds can also reduce pedestrian awareness, prompting regulations for vehicle sound alerts. Together, these issues highlight the need for policies that address both emerging safety risks and the evolving nature of BEV technology. Full article

As aging urban expressways become more pronounced, maintenance and construction work on these roadways is increasingly necessary. Some lanes may need to be closed during maintenance and construction, decreasing driving safety and comfort in the work zone. This situation often leads to traffic congestion and a higher risk of traffic accidents. Notably, 80% of work zone traffic accidents occur in the warning and upstream transition areas (or simply warning and transition areas). Therefore, it is crucial to appropriately determine the lengths of these areas to enhance both safety and comfort for drivers. In this study, we examined three different warning lengths (1800 m, 2000 m, and 2200 m) and three transition lengths (120 m, 140 m, and 160 m) using the entropy weighting method to create nine simulation scenarios on a two-way, six-lane urban expressway. We selected various metrics for driving safety and comfort, including drivers’ eye movement, electroencephalogram, and driving behavior indicators. A total of 45 participants (mean age = 23.9 years, standard deviation = 1.8) were recruited for the driving simulation experiment, and each participant completed all 9 simulation scenarios. After eliminating 5 invalid datasets, we obtained valid data from 40 participants. We employed a combination of the analytic network process and entropy weighting method to calculate the comprehensive weights of the eight evaluation indicators. Additionally, we introduced the fuzzy theory, utilizing a trapezoidal membership function to evaluate the membership matrix values of the indicators and the comprehensive evaluation grade eigenvalues. The ranking of the experimental scenarios was determined using these eigenvalues. The results indicated that more extended warning lengths correlated with increased safety and comfort. Specifically, the best driver safety and comfort levels were observed in Scenario I, which featured a 2200 m warning length × 160 m transition length. However, the difference in safety and comfort across different transition lengths diminished as the warning length increased. Therefore, when road space is limited, a thoughtful combination of reasonable lengths can still provide high driving safety and comfort. Full article

The escalating disasters caused by the movement of shallow buried strata in China’s western mining areas are increasingly threatening operational safety. A critical issue in ensuring secure mining practices in these areas is the creep failure of weakly cemented soft rock under low-stress conditions. The unique particle contact mechanisms in weakly cemented mudstone, combined with the persistence of the cemented materials and the particulate matter they form, lead to mechanical responses that differ significantly from those of typical soft rocks during loading. Building on an existing multivariate linear regression equation for new similar materials, this study developed qualified weakly cemented medium similar materials, offering appropriate materials for long-term creep tests of weakly cemented formations. This was accomplished by employing orthogonal proportioning tests. The principal findings of our investigation are as follows: The new, similar material exhibits low strength and prominent creep characteristics, accurately simulating weakly cemented materials in western mining areas. The concentration of rosin–alcohol solution has a measurable impact on key parameters, such as σ_c, E, and γ in the weakly cemented similar material specimens. Furthermore, the creep characteristics of the specimens diminish progressively with an increase in the proportion of iron powder (I) and barite powder (B). The material was applied to a similar indoor model test simulating the weakly cemented material surrounding the auxiliary haulage roadway in Panel 20314 of the Gaojialiang Coal Mine, with speckle analysis employed for detailed examination. The experimental findings suggest that both the conventional mechanical properties and long-term creep characteristics of the material align with the required specifications, offering robust support for achieving optimal outcomes in the similar model test. Full article

This paper addresses the limitations of the A* algorithm in underground roadway path planning, such as proximity to roadway boundaries, intersection with obstacle corners, trajectory smoothness, and timely obstacle avoidance (e.g., fallen rocks, miners, and moving equipment). To overcome these challenges, we propose an improved path planning algorithm integrating an enhanced A* method with an improved Dynamic Window Approach (DWA). First, a diagonal collision detection mechanism is implemented within the A* algorithm to effectively avoid crossing obstacle corners, thus enhancing path safety. Secondly, roadway width is incorporated into the heuristic function to guide paths toward the roadway center, improving stability and feasibility. Subsequently, based on multiple global path characteristics—including path length, average curvature, fluctuation degree, and direction change rate—an adaptive B-spline curve smoothing method generates smoother paths tailored to the robot’s kinematic requirements. Furthermore, the global path is segmented into local reference points for DWA, ensuring seamless integration of global and local path planning. To prevent local optimization traps during obstacle avoidance, a distance-based cost function is introduced into DWA’s evaluation criteria, maintaining alignment with the global path. Experimental results demonstrate that the proposed method significantly reduces node expansions by 43.79%, computation time by 16.28%, and path inflection points by 80.70%. The resultant path is smoother, centered within roadways, and capable of effectively avoiding dynamic and static obstacles, thereby ensuring the safety and efficiency of underground robotic transport operations. Full article

This study focuses on the importance of the real-time monitoring of bolt loads in roadways affected by high-intensity mining and the limitations of conventional monitoring methods. Fiber Bragg grating (FBG) sensors were embedded and encapsulated in rock bolts, and tensile tests were conducted indoors to verify their feasibility. The research was conducted using the consolidated face of the Bultai Coal Mine in the Shendong Mining Area as the engineering background. Real-time monitoring wavelength data from the FBG bolt sensor were obtained through field tests. The analysis of the data aimed to assess the condition of the FBG sensor and variations in axial force within the service bolts of the mining roadway. Using these monitoring results, the real-time stability and safety of the roadway bolts were evaluated. The study indicates that as the working face advances, the axial force in the bolt progressively rises under the effect of mine pressure. The left gang bolt rod’s shaft force changes significantly, while the right gang’s change is relatively small. When the working face moves 60 m past the bolt rod, the axial force in the bolt rises sharply. Moreover, the axial force at different positions of the left and right gang bolts exhibits a distinct variation pattern. The real-time monitoring of bolt support in the return roadway provides essential data for assessing bolt safety. Full article

As a key roadside safety feature, longitudinal guardrail steel barriers are purposefully designed to contain and redirect errant vehicles to prevent roadway departure, dissipate impact energy through plastic deformation, and reduce the severity of vehicle crashes. Nevertheless, these systems should be carefully designed and assessed, as localized rupturing, especially near splice or impact locations, can lead to catastrophic failures, compromising vehicle containment, violating crash safety standards, and ultimately jeopardizing the safety of occupants and other road users. Before conducting full-scale crash testing, finite element analysis (FEA) tools are widely employed to evaluate the design efficiency, optimize system configurations, and preemptively identify potential failure modes prior to expensive physical crash testing. To accurately assess system behavior, calibrated material models and precise failure criteria must be utilized in these simulations. Despite the existence of numerous failure criteria and material models, the material characteristics of AASHTO M-180 guardrail steel have not been fully investigated. This paper significantly advances the FE modeling of ductile fracture in guardrail steel, addressing a critical need within the roadside safety community. This study formulates stress-state-dependent failure criteria and proposes advanced material modeling techniques. Extensive experimental testing was conducted on steel specimens having various triaxiality and Lode parameter values to reproduce a wide spectrum of complex, three-dimensional stress-state loading conditions. The test results were then used to identify material properties and construct a failure surface. Subsequent FEA, which incorporated the Generalized Incremental Stress-State-Dependent Damage Model (GISSMO) in conjunction with two LS-DYNA material models, illustrates the capability of the developed surface and material input parameters to predict material behavior under various stress states accurately. A parametric study was completed to further validate the proposed models, highlighting their robustness and reliability. Full article

Anchor–bolt support operations are lengthy and conducted under harsh conditions, restricting the efficiency and safety of roadway excavation. To address these challenges, we developed an integrated solution combining mechanical structure optimization with control algorithms. Specifically, we designed a novel automated drilling system equipped with a robotic manipulator and an anchor–bolt magazine to handle modular hollow self-drilling anchor bolts, enabling automated support operations. To achieve precise docking in unmanned conditions, we employed an inner-loop fractional-order proportional–integral–derivative (FOPID) controller optimized by an improved particle swarm optimization (ILPSO) algorithm. Additionally, robust control based on H∞ control theory was introduced to ensure reliable system performance under disturbances and model uncertainties. Simulation results indicate that the ILPSO-tuned FOPID controller significantly outperforms conventional controllers in dynamic response accuracy; frequency–domain analysis further confirms that the H∞ control approach enhances system stability. Collectively, these results provide a theoretical basis for advancing automated mining technologies. Full article

Based on the engineering conditions of the 1303 working face in Zhaoxian Coal Mine, this study investigates the characteristics of mine pressure behavior and the stress-relief mechanism of advanced presplit blasting in a working face with a thick and hard roof in an extra-thick coal seam. Through a combination of numerical simulations and field experiments, the effects of advanced presplit blasting on stress distribution, roadway stability, and microseismic activity are analyzed. Corresponding mitigation measures and optimization strategies are proposed. The results indicate that the primary cause of deformation in the gob-side roadway is the superposition of lateral abutment pressure from the goaf and the front abutment pressure of the advancing working face. Advanced presplit blasting effectively reduces the magnitude of front abutment stress, inhibits its transmission, decreases the hanging area of the goaf roof, and alleviates vertical stress on the roadway side adjacent to the goaf. Furthermore, both the daily average and peak microseismic energy levels decrease as the working face approaches the advanced blasting zone. The implementation of advanced presplit blasting technology in working faces with thick and hard roofs within extra-thick coal seams significantly mitigates rockburst hazards, enhances roadway stability, and improves overall mining safety. Full article

Emergency water release from underground reservoirs is characterized by its suddenness and significant harm. The quantitative prediction of water spreading processes in mine tunnels is crucial for enhancing underground safety. The study focuses on an underground roadway in a coal mine, constructing a three-dimensional physical model of the complex tunnel network to explore the spatiotemporal characteristics of water flow spreading after water release in coal mine tunnels. The Volume of Fluid (VOF) model of the Eulerian multiphase flow was adopted to simulate the flow state of water in the roadway. The results indicate that after water release from the reservoir, water flows along the tunnel network towards locations with relatively lower altitude terrain. During the initial stage of water release, sloping tunnels act as barriers to water spreading. The water level height at each point in the tunnel network generally experiences three developmental stages: rapid rise, slow increase, and stable equilibrium. The water level height in the tunnel area near the water release outlet rises sharply within a time range of 550 s; tunnels farther from the water release outlet experience a rapid rise in water level height only after 13,200 s. The final stable equilibrium water level in the tunnel depends on the location of the water release outlet and the relative height of the terrain, with a water level height ranging from 0.3 to 3.3 m. The maximum safe evacuation time for personnel within a radius of 300 m from the drainage outlet is only 1 h. In contrast, areas farther away from the drainage location benefit from the water storage capacity of the complex tunnel network and have significantly extended evacuation opportunities. Full article

This study applied 2019 macro-level data from DATASUS to model traffic fatalities at the scene. Ordinary least squares (OLS) and censored regression models (TOBIT) were the methodologies used to identify the significant variables explaining the occurrence of deaths on public roads due to crashes. The number of fatalities on public roadways was then modeled using a multilayer perceptron artificial neural network employing the significant variables as predictors according to the generalization capacity of complex predictive models. The OLS and TOBIT findings indicated that the variables motorcycles and scooters per capita, municipal human development index, and number of SUS emergency units were the most important for modeling traffic fatalities at the scene at the national and regional levels. Applying these variables, the neural network’s best results achieved a hit rate of 88% for Brazil and 95% for the Northeast model. The contribution of this study is providing an approach combining various methods and considering a range of variables influencing traffic fatalities at the scene. The findings offer insights for policymakers, researchers, and practitioners involved in road safety initiatives, mainly where crash data are scarce, and macro-level analysis is necessary. Full article

To address ventilation challenges in the working face of metal mine excavation, an equal-scale physical model was established with a mine section as the test site, combined with field-measured data and relevant parameters of spent air reuse equipment. Numerical simulations were carried out using Fluent 2020 R2 software to analyse the characteristics of the airflow field, temperature field, and dust distribution in the excavation roadway. The results show that when the cold air outlet temperature (T₀) is 22 °C, the temperature within the cooling zone does not exceed 26.3 °C, thereby demonstrating effective cooling. The equipment parameters significantly impacted cooling and dust removal. When the distance from the cold air outlet to the heading face was set to Z_m = 8 m, the air outlet temperature was T₀ = 22 °C, and the ventilation circulation rate was F = 40%, the working area achieved better cooling and dust removal effects. On-site application showed that within 15 m of the working face, temperatures dropped by 3–3.5 °C, reaching a low of 25.1 °C. The relative humidity at a point 1 m away from the working face decreased from 90.6% to 70.2%, and the average dust removal efficiency was 44.9%, which significantly improved the comfort and safety of the working environment at the heading face. Full article

Facing the support challenges of short-wall working face (15–40m) roadways in the ‘excavation–backfill–retention’ tunneling method for section coal pillars, traditional equipment struggled to achieve stable, reliable, and efficient support. This paper designed a temporary support robot for the excavation and mining system of section coal pillars to ensure the safety of equipment and personnel in short-wall working faces. The support requirements of the section coal pillar excavation and mining system were analyzed, and a general ‘driving under pressure’ temporary support scheme was proposed. The working principle of the temporary support robot was analyzed. A mechanical model for the stable support of the temporary support robot was established. The mechanical properties of the surrounding rock were analyzed, and the allowable range of the temporary support robot’s supporting force was determined while ensuring the stability of the surrounding rock. Based on the Stribeck friction theory, a dynamic model of the temporary support robot in the driving under pressure state was constructed. The boundary conditions of the dynamic model were set, and the corresponding relationship between the temporary support robot’s supporting force and its maximum static friction force was determined. This accurately described the influence of the supporting force and pushing (pulling) force on the movement during the process of driving under pressure. Through finite element simulation, the stress conditions of the temporary support robot and the floor under maximum load were analyzed, indicating that this load condition would not cause damage to the temporary support robot or the surrounding rock. Through multi-body dynamics simulation, the pushing (pulling) forces required for the temporary support robot’s movement under different supporting force conditions were obtained, verifying the feasibility of the driving under pressure action under different supporting force conditions. Moreover, the model-predicted and simulated values of the required pushing (pulling) forces during the process of driving under pressure were consistent, validating the accuracy of the driving under pressure dynamic model. This research provides a new theoretical framework for the design and dynamic analysis of temporary support equipment for short-wall working faces in section coal pillar mining, holding significant academic value and broad application prospects. Full article