Search Results (511)

To support carbon stock assessment and ecological restoration under the “Carbon Neutrality” objective, this paper developed a high-precision vegetation biomass model for expressway corridors in Shanxi Province, China, by integrating Unmanned Aerial Vehicle(UAV) technology and the random forest algorithm. Based on climatic zoning and DEM data, 70 sample plots representing diverse vegetation and topography were selected. LiDAR point clouds and multispectral data were spatially connected using the BallTree algorithm, achieving an average matching rate of 73.98–82.01%. A joint biomass model incorporating tree height and crown width was constructed with spatial cross-validation. The results indicate that the model substantially outperformed single-factor models, with R² values ranging from 0.839 to 0.934 (highest in the Hengshan–Wutaishan forest area). Accuracy was higher in forest-dominated zones but lower in areas with significant human disturbance. A representative sample library was established for model optimization. This paper provides a robust technical framework for biomass monitoring across comparable Northern Hemisphere latitudes, thereby supporting sustainable green transport development. Full article

To meet real-time control requirements on expressway mainlines, this paper builds an observation–demand model centered on recurrent congestion and short-term congestion fronts and develops a joint planning method for UAV cruise paths and speeds. The method converts long-term priors and short-term forecasts into a priority field and speed constraints. With centerline guidance and a time-metric strategy, it generates trajectories that follow the mainline alignment and support low-speed cruising and loitering in key segments. On this basis, an automated framework comprising five layers, including data, orchestration, planning, execution, and safety, is established to achieve a stable mapping from observation demands to executable trajectories and speed profiles. The study provides actionable paths for proactive observation of recurrent congestion and short-term fronts and lays a practical foundation for integration with mainline control measures. Full article

This paper addresses the optimization of electric vehicle (EV) charging facility configuration on highways by proposing a collaborative planning method that integrates driver anxiety psychology, mixed traffic flow dynamics, and service area queuing characteristics. By abstracting the road travel and service area replenishment processes into an integrated queuing network, a system analysis framework is constructed to characterize the coupling relationship of “facility supply, traffic assignment, and state feedback.” On this basis, a bi-level optimization model is established with the objective of minimizing the generalized total social cost. The upper level makes decisions on the coordinated quantities of fixed charging piles and mobile charging vehicles, while the lower level describes the stochastic user equilibrium behavior of drivers under the influence of real-time congestion and anxiety. To tackle the high-dimensional nonlinear nature of the model, an efficient solution algorithm based on simultaneous perturbation stochastic approximation (SPSA) is designed. A case study of the Nei-Yi Expressway demonstrates that compared with the traditional peak demand proportional allocation method, the proposed approach can better balance construction costs, operation and dispatching costs, and user travel experience under limited investment, significantly reducing waiting times and psychological anxiety costs. It provides theoretical methods and decision support for planning a resilient energy replenishment network that achieves “fixed facilities ensuring base load and mobile resources responding to peak demands.” Full article

Coordinated control of ramp metering, variable speed limits, and intersection signals is critical for mitigating congestion and enhancing efficiency at urban expressway–arterial interfaces. Existing strategies often operate in isolation, leading to fragmented responses and limited adaptability under heterogeneous traffic demands. This study develops a multi-agent reinforcement learning framework based on MADDPG to achieve cooperative decision-making across heterogeneous controllers. An asynchronous control cycle mechanism is designed to accommodate different temporal requirements of ramp meters, speed limits, and signal controllers, ensuring practical feasibility in real-time operations. A conflict-aware reward design further embeds density regulation, speed harmonization, and spillback prevention to stabilize flow dynamics. Simulation experiments on a calibrated urban network demonstrate that the proposed framework delays congestion onset, reduces shockwave propagation, and improves throughput compared with classical benchmarks. In particular, at the mainline merge, average travel time is reduced to 13.56 s (62.4% of VSL-only); at the ramp, occupancy is lowered to 6.4% (40.6% of ALINEA); and at the signalized approach, average delay decreases to 85.71 s (62.7% of actuated control). These results highlight the scalability and deployment potential of the proposed cooperative control approach for system-level traffic management in mixed traffic environments. 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

Expressway traffic noise poses a critical threat to public health in developed high-density cities, causing chronic environmental stress in adjacent residential areas. While physical noise barriers are commonly used, the potential of audiovisual interactions in mitigating the adverse effects of traffic noise remains under-explored. Using immersive virtual reality (VR), this study examined the efficacy of visual greenery and auditory masking (birdsong) in promoting stress recovery, and tested whether audiovisual perception mediates the environment–restoration link. Following an acute stressor, 100 participants were randomly assigned to a 2 × 2 between-subjects experiment manipulating Green View Index (high vs. low) and soundscape composition (traffic noise vs. traffic noise plus birdsong), with 25 participants in each group. Restorative outcomes were assessed using self-reported measures and continuous physiological monitoring (heart rate variability [HRV] and electrodermal activity [EDA]). Results demonstrated that high-intensity visual greenery and natural sounds effectively enhance psychological restoration in noise-affected environments. Structural equation modeling revealed that audiovisual perception fully mediated the relationship between environmental features and restorative outcomes. The physiological outcome showed a distinct tiered restoration pattern, indicating that immediate psychological buffering can be achieved through natural sounds, while consistent visual reinforcement remained essential for deep physiological recovery. Consequently, soundscape planning in expressway-adjacent zones should integrate visual greening strategies to optimize the perceptual masking of traffic noise and enhance the environmental quality. Full article

To address the current research gap where studies on the failure mechanisms of fissured tunnels mainly focus on single tunnels with insufficient research on double tunnels, and to provide a scientific basis for disaster prevention and control of the Jinan Tunnel on Jinan Ring Expressway, this study investigates the mechanical behavior and failure characteristics of tunnel structures containing fissure–hole composite systems using experimental tests and numerical simulations. The crack initiation, propagation, and coalescence mechanisms are systematically analyzed to provide engineering references for tunnel design and stability assessment. Sand-based 3D printing technology was used to fabricate double-tunnel models with prefabricated fissures of different inclination angles α. Uniaxial compression tests were conducted, and crack evolution was monitored using DIC technology. Meanwhile, numerical simulation verification was performed based on the parallel bond (PB) model of the Discrete Element Method (PFC). The results show that the mechanical response of sand-based 3D-printed models conforms to the brittle characteristics of engineering rock masses. For models without fissures, cracks are preferentially initiated at the top and bottom of the tunnels. For models with fissures, the peak strength is the highest when α = 30° and 60°, and the lowest when α = 45° and 90°. As the fissure inclination angle increases, the tensile stress concentration shifts from the top and bottom of the tunnels and the middle of the fissure to the two ends of the fissure. The numerical simulation results are consistent with the experimental results and can accurately reproduce crack evolution. This study verifies the effectiveness of combining sand-based 3D printing with discrete element simulation, providing a reference for fissure prevention and control as well as operation and maintenance optimization of similar double-tunnel projects. Full article

To investigate the bearing characteristics of super-long and large-diameter cast-in-place piles with combined pile-end and pile-side post-grouting, double-load-box self-balanced static-load tests were conducted on two such piles of the Yellow River Bridge Project on Jiaoping Expressway both before and after grouting. This study aims to provide technical insights for the design and construction of similar pile foundations. The test results indicate that, after grouting, the ultimate bearing capacities of test piles SZ1 and SZ2 increased by 123.1% and 72.8%, respectively, with a significant reduction in pile top settlement under the same load level. Under each load level, the axial force of the pile shaft reaches its maximum near the upper load box, presenting a triangular distribution curve. Furthermore, the side frictions of SZ1 and SZ2 enhanced by 87.73% and 83.59%, respectively, after grouting, while their ultimate end resistances are improved by 362.6% and 120.6%. These findings demonstrate that post-grouting effectively optimizes the mechanical properties of the pile–soil interface and enhances the structural stiffness of the surrounding soil. Specifically, the grout hardens at the pile end, solidifies the sediment there, increases the density of the pile-end soil layer, and improves the bearing rigidity of the bearing stratum. This research validates the effectiveness of the combined pile-end and pile-side post-grouting technology in improving the bearing performance of super-long and large-diameter cast-in-place piles, providing valuable technical support for the safe and efficient construction of the Yellow River Bridge on the Jiaoping Expressway and similar engineering projects. Full article

Highway slope-mounted photovoltaic (HSPV) systems are increasingly deployed along expressways, yet wind loads on panel arrays can be strongly modified by slope-induced topographic effects. This study establishes a full-scale CFD framework (ANSYS Fluent, RANS with the SST k–ω model) to quantify the evolution of roadside wind profiles over embankments and the resulting wind loads on HSPV arrays. The inlet boundary layer, mesh independence, and surface pressure distributions were validated against theoretical profiles (errors < 5%), mesh refinement, and wind-tunnel data from the literature. Seven slope geometries (H = 2–10 m, i = 1:1–1:1.75) were analyzed to characterize wind-profile deviation and recovery height, followed by simulations of a 3 × 40-module array to evaluate shape and moment coefficients. Topographic effects are concentrated in the near-ground layer from the slope toe to crest, producing toe deceleration and mid-to-upper-slope acceleration; increasing H markedly enlarges the affected height range. For arrays, the slope ratio governs wake superposition and drives strong row-wise differentiation, with the rear row consistently yielding the most unfavorable net pressure and bending moment. Steep slopes can reverse the moment sign, with the moment coefficient varying approximately from −0.15 to +0.15 across the investigated cases, whereas gentler slopes amplify positive moments in the rear rows, suggesting that design checks should prioritize rear-row modules over single-row references. Full article

To address the complex influencing factors, divergent stakeholder demands, and the challenge of quantitative comparison in alignment selection for highway expansion and reconstruction, we systematically reviewed the relevant factors. These factors were classified into four categories—economy, technology, safety, and environment—and comprise 16 subfactors in total. The symmetry of the route selection process is disrupted by the varying priorities of different stakeholders, leading to asymmetric evaluations of the alternatives. Using the G30 Lianhuo Expressway Jingqing section expansion and reconstruction project as a case study, we applied the Analytic Hierarchy Process (AHP) combined with expert judgment to derive weights for each factor. The results indicate that environmental factors carry substantial weight, reflecting increased awareness of environmental protection in contemporary projects. We then developed a comparative model based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Applying this model to alignment alternatives between the Jingjiadian and Huachacun sections indicates that Option 4 is the preferred alignment. Overall, the AHP–TOPSIS composite evaluation framework effectively integrates expert knowledge with objective quantitative analysis. It enables the scientific ranking of alternatives and provides decision support for alignment selection in mountainous highways and other linear engineering projects. Full article

Transportation infrastructure is vulnerable to heterogeneous deformation, yet such deformation remains insufficiently monitored and characterized in metropolitan regions due to the lack of high-resolution deformation gradient products and comparison with industrial standards. Here, we generated a 45 m resolution interferometric synthetic aperture radar (InSAR) surface displacement time series across the Beijing Plain using Sentinel-1 SAR imagery acquired between 2014 and 2024, and calculated deformation gradients along all ring roads, major expressways, and airport runways. These deformation gradients are compared with national standards to evaluate their structural risks. Our analysis shows that (1) subsidence in the Beijing Plain is concentrated in the northern, eastern, and southern regions, where the northeastern region has been uplifting since 2018 due to the groundwater recovery in Beijing; (2) all ring roads, expressways, and airport runways are relatively stable during our observation period of 2015–2021, except for the central runway of Beijing Capital International Airport, which has accumulated a deformation gradient of 1.9‰ during 2015–2021, exceeding the safety limit of 1.5‰, indicating structural risks. These results demonstrate the effectiveness of high-resolution InSAR time series for monitoring deformation and pinpointing potential structural risks. Full article

To address the “silo effect” in construction waste management and the inefficiency of resource allocation in large-scale, multi-section engineering projects, this study developed a cloud-based regional collaborative platform for construction waste management. The platform adopts a technical framework based on Java 1.8.0, Spring Boot 2.4.4, and MySQL 8.0.16, and integrates a visual interactive interface. It supports dynamic access, data entry, quality review, and scheduling of construction waste information across multiple sections and projects. Validated through a case study on the Changhu section of the Guangdong Guanshen–Changhu Expressway expansion project, the platform successfully achieved spatial–temporal optimization of 740 thousand cubic meters of diversified construction waste across seven sections. The comprehensive utilization rate of construction waste increased by more than 25%. Practice has shown that the platform effectively promotes carbon emission reduction in earthworks, enhances resource circularity, and provides digital support for construction quality control. This platform presents an innovative informatics-driven approach to construction waste management, serving as a replicable model. Full article

Expressway networks represent evolving complex systems whose topological properties significantly impact regional development. This paper presents a decision support framework for addressing the expressway infrastructure sequencing problem using computational intelligence. We develop a novel framework that models expressways as L-space networks and evaluates how construction sequences create path-dependent evolutionary trajectories, introducing network science principles into infrastructure planning decisions. Our decision support framework quantifies project impacts on accessibility, connectivity, and reliability using nine topological metrics and a hybrid weighting mechanism that combines domain expertise with entropy-based uncertainty quantification. The system employs a hybrid TOPSIS algorithm that relies on geometric symmetry to simulate network evolution, capturing emergent properties in which each decision restructures possibilities for subsequent choices—a computational challenge that conventional planning approaches have not addressed. The system was validated with real-world Chongqing expressway planning data, demonstrating its ability to identify sequences that maximize synergistic network effects. Results reveal how topologically equivalent projects produce dramatically different system-wide outcomes depending on implementation order. Analysis shows that network science-informed sequencing substantially enhances system performance by exploiting structural synergies. This research advances decision support frameworks by bridging complex network theory with computational decision-making, creating a novel analytical tool that enables transportation authorities to implement evidence-based infrastructure sequencing strategies beyond the reach of conventional planning methods. Full article

Level 2 driving automation requires continuous driver supervision, yet common attention metrics often capture gaze allocation rather than the structure of supervisory scanning. This study proposes a quantitative approach for describing supervisory gaze organisation using first-order Markov chain analysis of gaze transitions. Forty-three licensed drivers ($N=43$) completed a simulator drive with Level 2 automation for either 5 or 15 min (between-subjects), representing typical Japanese expressway intervals between service areas. Supervisory behaviour was analysed at the scenario level, without introducing secondary tasks, allowing attentional drift to emerge naturally under automation. Eye-tracking data were manually annotated frame-by-frame at 60 Hz and modelled as transition probability matrices across key Areas of Interest (AOIs): road centre, mirrors, periphery, and the human–machine interface. Compared with the 5 min condition, the 15 min condition showed fewer mirror-to-road-centre recovery transitions and slower System-Recognised Reaction Time (SRRT) at the takeover request. These patterns suggest a gradual weakening of supervisory gaze organisation rather than a simple loss of attention. The proposed framework offers a reproducible way to calibrate driver monitoring and evaluate human–machine interfaces by linking gaze transition probabilities to takeover readiness. By quantifying how supervisory behaviour reorganises under extended automation in realistic driving scenarios, this study provides a practical basis for the development of safety-relevant driver monitoring indicators in Level 2 driver assistance systems. Full article

With accelerating urbanisation, extreme rainfall events have become increasingly frequent, leading to rising urban flooding risks that threaten city operation and infrastructure safety. The rapid expansion of impervious surfaces reduces infiltration capacity and accelerates runoff responses, making cities more vulnerable to short-duration, high-intensity storms. Although the SWMM is widely used for urban stormwater simulation, its application is often constrained by the lack of detailed drainage network data, such as pipe diameters, slopes, and node connectivity. To address this limitation, this study focuses on the main built-up area within the Second Ring Expressway of Chengdu, Sichuan Province, in southwestern China. As a regional core city, Chengdu frequently experiences intense short-duration rainfall during the rainy season, and the coexistence of rapid urbanisation with ageing drainage infrastructure further elevates flood risk. Accordingly, a technical framework of “open road data substitution–automated modelling–SWMM-based assessment” is proposed. Leveraging the spatial correspondence between road layouts and drainage pathways, open road data are used to construct a virtual drainage system. Combined with DEM and land-use data, Python-based automation enables sub-catchment delineation, parameter extraction, and network topology generation, achieving efficient large-scale modelling. Design storms of multiple return periods are generated based on Chengdu’s revised rainfall intensity formula, while socioeconomic indicators such as population density and infrastructure exposure are normalised and weighted using the entropy method to develop a comprehensive flood-risk assessment. Results indicate that the virtual drainage network effectively compensates for missing pipe data at the macro scale, and high-risk zones are mainly concentrated in densely populated and highly urbanised older districts. Overall, the proposed method successfully captures urban flood-risk patterns under data-scarce conditions and provides a practical approach for large-city flood-risk management. Full article