Search Results (31)

This study addresses the limited nationwide examination of Mountain Villages as strategic targets for regional revitalization amid rapid depopulation and population aging. Focusing on Mountain Villages located within Depopulation Regions in the Republic of Korea, this study quantitatively assessed workation suitability at the Eup-Myeon-Dong level and identified priority areas and differentiated policy directions. A workation suitability index was calculated using the CRITIC (Criteria Importance Through Intercriteria Correlation) method, and spatial clustering and potential–demand characteristics were examined through LISA (Local Indicators of Spatial Association) and quadrant analysis. The results showed that transportation accessibility indicators, including travel time to expressway interchanges and railway stations, had high information content in differentiating workation suitability among Mountain Villages. Suitability was high in the border areas between Gyeonggi-do and Gangwon State and parts of the central inland region, whereas low suitability was observed in northern Gangwon State and northern Gyeongsangbuk-do. High–High clusters tended to overlap with high-potential and high-demand areas, while Low–Low clusters were mainly associated with low-potential areas. By integrating suitability, spatial clustering, and demand conditions, this study provides an empirical framework for spatial decision-making. The findings suggest that workation policies for Mountain Villages should distinguish priority implementation areas from foundation-building areas according to accessibility, infrastructure, and demand levels. Full article

Traffic flow prediction is important for traffic management and safety control in mountainous areas. In these environments, traffic flow is affected by complex terrain, changing weather, and mixed vehicle types, so the resulting time series often show strong fluctuation and poor stability. Many existing prediction models were developed for urban roads or flat highways, and their performance is therefore limited in mountainous scenarios. To address this problem, this paper proposes a hybrid model called DK-VCA Net. The model combines adaptive signal decomposition with a terrain-aware deep learning structure to separate useful traffic variation from complex noise. It also integrates traffic flow, speed, slope, and weather information to better describe mountain traffic conditions. The proposed method is evaluated using real traffic data collected at 5 min intervals from detection stations on the Guibi Expressway in Guizhou Province, China, during September 2020. Experimental results show that DK-VCA Net achieves better prediction accuracy than several representative baseline models, including 1D-CNN, LSTM, Transformer, STWave, and Mamba. Across the 15 min, 30 min, and 60 min forecasting tasks, the proposed model reduces the average RMSE by 14.8% compared with the conventional 1D-CNN model and by 8.9% compared with the baseline Transformer model. The ablation study further proves the effectiveness of the decomposition strategy, terrain-related features, and the attention mechanism. The results show that the proposed method is effective for traffic flow prediction in the studied mountainous highway scenario. Full article

Fog is a near-surface weather phenomenon with low visibility that significantly threatens transportation safety. Understanding the spatiotemporal evolution and formation mechanisms of fog is essential for improving fog forecasting and warning services to reduce related casualties and economic losses. This study examines consecutive dense fog events with long duration and high intensity that occurred along the Ma-Zhao Expressway in northeastern Yunnan from 24 to 30 October 2022. Yunnan is a typical low-latitude plateau region in southwestern China with complex terrain and diverse climates, leading to particularly complicated fog formation processes. Correlation analysis indicates that thermal and vapor factors show stronger correlations with visibility, with correlation coefficients reaching 0.68 for vertical temperature difference and −0.63 for surface relative humidity, both significant at the 99% confidence level. These values are notably higher than those of dynamic factors such as near-surface wind speed, which yields a correlation coefficient of 0.47. The results confirm the dominant role of thermal and vapor conditions in the formation and maintenance of these dense fog events, together with favorable conditions including near-surface air saturation, weak dynamic processes, and a temperature inversion in the lower troposphere. Standardized anomaly analysis reveals obvious atmospheric anomalies during the fog episodes. A strong southerly wind anomaly appears in the lower troposphere, driven by a cyclone over the Philippines and an anomalous anticyclone east of Yunnan. This southerly transport delivers warm and moist air toward the Ma-Zhao Expressway, accompanied by a positive temperature anomaly of 1.7, standard deviations near 700 hPa and a positive specific humidity anomaly of more than 2 standard deviations in the lower troposphere. These conditions favor the development of temperature inversions and atmospheric saturation, further promoting the occurrence and persistence of consecutive dense fog events. This study clarifies the key effects of thermal and vapor conditions as well as low-level southerly wind anomalies on dense fog over the Yunnan low-latitude plateau. These conclusions deepen the understanding of fog formation mechanisms in complex plateau terrain and provide a scientific reference for fog forecasting and early warning along mountain expressways in similar low-latitude plateau regions. Full article

Against the background of the acceleration of the integration of the “double carbon” target and transportation energy, the green transformation and business model innovation of highway service areas, as a high-energy-consumption traffic node, are becoming more and more urgent. However, the existing research focuses on a single technology path, and lacks a systematic quantitative evaluation of the “PV–charging–new format” coordination mechanism and its operating efficiency. Therefore, this paper proposes a collaborative framework that integrates photovoltaic power generation, new energy charging piles, and diversified new formats, and introduces a random forest regression algorithm. Based on the actual operation data of the Guangxi expressway service area, the synergistic effect and regional heterogeneity of multiple factors are systematically evaluated. The results show that a photovoltaic system can reduce the unit electricity price by 25–35%, and the investment recovery period is about 7 years. When the penetration rate of charging piles increases to 35%, the annual income can reach CNY 3.285 million, and the return on investment increases to 2.3 times when the utilization rate exceeds 80%. The new business combination can increase the average daily income by 13.3–26.7%. At the same time, the coordinated implementation of the three elements can achieve an annual net income increase of 27–32%, which is better than the linear superposition of the benefits of a single measure. In addition, the analysis of regional heterogeneity shows that the photovoltaic benefit in the western mountainous area is outstanding, the charging benefit in the coastal area is significant, and the comprehensive benefit in the central hub area is the best. This study provides a quantitative basis to support decisions on the differentiated development path of expressway service areas in the background of traffic–energy integration. Full article

The construction of suspension bridges in mountainous expressways often involves tunnel-type anchorages in close proximity to shallow-buried bifurcated tunnels, particularly in soft rock strata with dense overlying structures. This proximity poses significant challenges to construction safety and stability. This study aims to investigate the influence of tunnel-type anchorage construction on the ground surface, surrounding rock, and adjacent bifurcated tunnels under such complex conditions. It was hypothesized that the anchorage load transfer and deformation mechanisms would significantly affect the adjacent tunnel, with potential cumulative effects due to the twin-anchor configuration. To address this, a combined approach of in situ scaled model testing (1:10 scale) and three-dimensional numerical simulation was employed. The model test incorporated monitoring of deformation and stress at key locations (anchor plug, rock mass, and anchor–rock interface) under incremental cable loads. Quantitative results from the model test indicate that at the design load (1P, equivalent to 2016.84 kN per anchor), deformations were minimal (e.g., maximum anchor displacement 0.35 mm). The anchor–rock interface exhibited limited slip (max 0.06 mm at 1P), and contact stresses were highest in the rear part of the anchor plug, indicating a non-uniform load transfer. Under overload conditions, the system reached yield at 7P and peak strength at 10.5P, with measured ground surface cracks up to 5 mm. Numerical simulations, calibrated against the experimental data, revealed that under increasing load (up to 10P), the plastic zones around the two anchors progressively expanded and eventually coalesced, leading to a characteristic “inverted trapezoid” failure pattern propagating to the surface, accompanied by shear failure along the 14° bedding plane. The combined results quantify the progressive interaction between the twin anchorages and the surrounding rock, highlighting the critical role of the anchor–rock interface and the cumulative effect of twin anchors on ground deformation and potential failure mechanisms. This research provides a scientific basis for the design and construction of tunnel-type anchorages in similar challenging geological and spatial settings. Full article

In high-density expressway environments, lane-changing (LC) maneuvers act as stochastic perturbations that compromise the hydrodynamic stability of traffic flow, leading to safety hazards and operational delays. While existing literature has extensively modeled crash severity in static complex environments (e.g., tunnels and mountainous terrains), there remains a critical deficiency in quantifying the dynamic, systemic risks induced by LC maneuvers under saturation conditions. To address this gap, this study proposes a novel Systemic Risk Assessment Framework. First, a Hidden Markov Model (HMM) is employed to decode the latent state transitions of following vehicles, quantifying the systemic consequence of LC maneuvers as “operational delay” based on traffic wave theory. Second, a Bayesian Network (BN) is constructed to infer the causal probability of risk, integrating geometric proxies such as insertion angle with kinematic variables. Validated with real-world trajectory data, the model achieves high accuracy in identifying risk accumulation precursors. This research contributes to the field of transportation systems by shifting the risk paradigm from static collision prediction to dynamic system reliability analysis, offering theoretical support for Connected and Autonomous Vehicle (CAV) decision logic. 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

China’s expressways generate substantial carbon emissions annually. To mitigate these emissions, this study explores the deployment of photovoltaic (PV) modules in the available areas of expressway service areas. As critical energy consumption nodes along the expressway network, service areas offer notable advantages for PV deployment compared to other highway segments, including ease of management, cost-effectiveness, and reduced transmission losses. However, the scattered distribution of service areas—many of which are located in mountainous and complex terrains—poses significant challenges to accurately assessing their PV potential. To address this issue, this study develops a spatiotemporal model to evaluate the solar photovoltaic power generation potential of expressway service areas across China. First, national service area coverage is determined using highway network data. Second, digital elevation model (DEM) data are used to estimate hourly shadow areas caused by surrounding terrain; solar radiation within these shadowed regions is assumed to be zero. Finally, by integrating ground-based solar radiation data with a radiation estimation model, the PV potential of service areas in each province is calculated. The model integrates expressway service area data, high-resolution digital elevation models, and ground-based solar radiation datasets to simulate spatially and temporally resolved irradiance conditions, enabling accurate estimation of photovoltaic potential at the provincial and national scales. Based on data from approximately 3225 expressway service areas as of the end of 2022, the results indicate an annual photovoltaic potential of 1400.72 TW, with an estimated installable capacity of 51.85 GW, yielding an annual electricity generation of 66.37 TWh. The southeastern regions, particularly Guangdong Province, exhibit greater PV potential due to their higher density of service areas, compared to the northwestern regions. Nationwide adoption of PV systems in expressway service areas is projected to reduce carbon emissions by 48.85 million tons. This study provides a valuable reference for regional planning and suitability assessment of PV expressway infrastructure development in China. Moreover, this study provides a novel spatiotemporal assessment framework and the first national-scale case study of PV potential in expressway service areas, offering valuable guidance for highway energy planning and low-carbon infrastructure development in China. Full article

Accurate and comprehensive characterization of high-steep slopes is crucial for real-time risk prediction, disaster assessment, and damage evolution monitoring. The study focused on a high-steep rocky slope along the Yanjiang Expressway in Sichuan Province, China. A novel digital reconstruction method was introduced, which integrates terrestrial laser scanning (TLS) and unmanned aerial vehicle (UAV) photogrammetry through a Transformer-based method combining GeoTransformer with the Maximal Cliques (MAC) algorithm. The results indicated that TLS excels in capturing fine-scale features, whereas UAV demonstrates superior performance in large-scale terrain reconstruction. However, multi-sensor data exhibit heterogeneity in terms of partial overlap, large outliers, and density differences. To address these challenges, the GeoTransformer-MAC framework extracts geometrically invariant features from cross-source point cloud (CSPC) to establish initial correspondences, followed by rigorous screening of high-quality locally consistent correspondences to optimize transformation parameters. This method achieves accurate digital reconstruction of the high-steep rock slope. Global and local error analyses verify the model’s superiority in both overall slope characterization and fine-scale feature representation. Compared with the TLS-only model and the conventional method, the Transformer-based method improves the slope model integrity by 85.58%, increases the data density by 9.71%, and improves the accuracy by nearly threefold. This study provides a novel approach for the digital modeling of complex terrains, which serves the refined identification and modeling of geohazards for high-steep slopes in complex mountainous regions. Full article

In China, weir-gully-type debris flows pose severe threats to transportation infrastructure, yet existing studies lack systematic analysis of their dynamic processes and early-warning strategies. This study innovatively integrates depth-integral modeling and field monitoring to investigate two unstable weirs upstream of the Zangyinggou Tunnel on the G30 Saiguo Expressway. The main research conclusions are as follows: (1) the influence of terrain and water source conditions on the weir-valley debris flow plays a dominant role; (2) the debris flows triggered by Weir I and II collapses reach the G30 Saiguo Expressway at 3560 s and 4000 s, respectively, with peak destructive capacities (cross-sectional sweep areas of 10.26 m²/s and 11.69 m²/s); (3) a three-level early-warning strategy was proposed, mainly based on water-level gauge monitoring and early warning, supplemented by video surveillance and regular measurement by small unmanned aerial vehicles. This study has established a brand-new idea for the monitoring and early warning of debris flow disasters induced by the collapse of barrier lakes along the G30 km line in Xinjiang. These achievements provide feasible insights for disaster reduction in mountainous transportation corridors, thus having significant practical value for promoting the sustainable development of infrastructure under the United Nations Sustainable Development Goals (SDGs). Full article

To study the generation and dissipation process of agglomerate fog in mountainous expressways and deeply understand the hazard mechanisms of agglomerate fog sections in mountainous expressways, based on the analysis of the geographical location characteristics of mountainous expressways and the spatial and temporal distribution characteristics of agglomerate fog, the airspace constitutive model of agglomerate fog in mountainous expressways was constructed based on Newton constitutive theory. Firstly, the properties of the Newtonian fluid and cluster fog were compared and analyzed, and the influence mechanism of environmental factors such as the altitude difference, topography, water system, valley effect, and vegetation on the generation and dissipation of agglomerate fog in mountainous expressways was analyzed. Based on Newton’s constitutive theory, the constitutive model of temperature, humidity, wind speed, and agglomerate fog points in the foggy airspace of the mountainous expressway was established. Then, the time and spatial distribution of fog in Chongqing and Guizhou from 2021 to 2023 were analyzed. Finally, the model was verified by using the meteorological data and fog warning data of Liupanshui City, Guizhou Province in 2023. The results show that the foggy airspace of mountainous expressways can be defined as “the space occupied by the agglomerate fog that occurs above the mountain expressway”; The temporal and spatial distribution of foggy airspace on expressways in mountainous areas is closely related to the topography, water system, vegetation distribution, and local microclimate formed by thermal radiation. The horizontal and vertical movements of the atmosphere have little influence on the foggy airspace on expressways in mountainous areas. The specific manifestation of time distribution is that the occurrence of agglomerate fog is concentrated from November to April of the following year, and the daily occurrence time is mainly concentrated between 4:00–8:00 and 18:00–22:00. The calculation results of the foggy airspace constitutive model of the expressway in the mountainous area show that when there is low surface radiation or no surface radiation, the fogging value range is [90, 100], and the fogging value range is [50, 70] when there is high surface radiation (>200), and there is generally no fog in other intervals. The research results can provide a theoretical basis for traffic safety management and control of mountainous expressway fog sections. Full article

In the Taihang Mountain Tourism Development Plan (2020–2035), the Taihang Mountain Expressway is included in the construction of the National Tourism Scenic Road around Taihang Mountain to promote the integrated development of regional transportation and tourism. The Lai-Qu Expressway is part of the Baoding section of the Taihang Mountain Expressway. Based on the data of traffic flow on the Lai-Qu Expressway, data of regional tourism resources, and data of regional economic and social development, this paper studies the interaction between the traffic and tourism space of the Lai-Qu Expressway by using spatial interaction, geographically weighted regression (GWR), and other geospatial analysis theories and methods. The results show that the traffic flow of the Baishishan Tollgate is directly correlated with the passenger flow of the Baishishan scenic spot. The spatial pattern of two tourism resource cluster centers and one sub-center, and one residential cluster center and one sub-center is expected to be formed along the Lai-Qu Expressway. The newly built traffic routes extend the influence of the traffic space and overlaps with the regional tourism space, not only providing new opportunities and possibilities for the development of regional tourism, but also promoting the change in the regional tourism spatial pattern and the cluster form of tourism resources. The research on the interaction between the traffic–tourism space in this paper can help to enrich the theoretical connotation of the research on the integration of transport and tourism, and can also be used to evaluate the tourism impact of newly built transport routes and serve the regional tourism development. Full article

To address the challenge of repairing the damage to concrete box girder bridge piers on mountainous highways caused by falling rocks, this paper proposes an active underpinning technique that integrates a “井”-shaped cap system, graded preloading of the foundation, and synchronized beam body correction. The technique utilizes lateral beam preloading (to eliminate the inelastic deformation of the new pile foundation) and longitudinal beam connections (to form overall stiffness). The method involves building temporary and permanent support systems in stages. Through the two-stage temporary support system transition, the removal and in situ reconstruction of the old piers, a smooth transition from the pier–beam consolidation system to the basin-type bearing system is achieved while simultaneously performing precise correction of beam torsion. The structural safety during the construction process was verified through finite element simulations and dynamic monitoring. Monitoring results show that the beam torsion recovery effect is significant (maximum lift of 5.2 mm/settlement of 7.9 mm), and the pier strain (−54.5~−51.3 με) remains within a controllable range. Before the bridge was opened to traffic, vehicle load and impact load tests were conducted. The actual measured strength and vertical stiffness of the main beam structure meet the design requirements, with relative residual deformation less than 20%, indicating that the structure is in good, elastic working condition. The vehicle running and braking dynamic coefficients (μ = 0.058~0.171 and 0.103~0.163) are both lower than the theoretical value of 0.305. The study shows that this technique enables the rapid and safe repair of bridge piers and provides important references for similar engineering projects. Full article

The increasing frequency of extreme weather events such as typhoons and heavy rains, driven by climate change, has intensified debris flow risks during Korea’s monsoon season, causing considerable human and economic losses. In South Korea, where mountainous terrain covers 64% of the country, localized downpours exacerbate the risk of debris flows, endangering communities and critical infrastructure. To enhance resilience and ensure sustainable risk management, the Korea Expressway Corporation developed a quantitative debris flow risk assessment system based on sensitivity and vulnerability indicators. An early warning system utilizing rainfall thresholds was subsequently introduced. However, discrepancies between rainfall data from local AWS stations and actual site conditions compromised its predictive accuracy. This study addresses those limitations by integrating the Parameter-elevation Regressions on Independent Slopes Model (PRISM) into the early warning system to enhance prediction accuracy at debris flow occurrence and non-occurrence points. Comparative analysis revealed that the PRISM-enhanced system significantly improved predictive performance. Furthermore, cumulative rainfall data from five highway sites validated the system’s reliability in short-term prediction while offering a sustainable, data-driven framework for long-term debris flow risk management. This approach strengthens adaptive infrastructure strategies, promoting more resilient transportation networks and improving public safety while minimizing environmental impacts. Full article

The Tianshan Expressway plays a crucial role in China’s “Belt and Road” strategy, yet the extreme climate of the Tianshan Mountains poses significant traffic safety risks, hindering local economic development. Efficient detection of hazardous road surface conditions (RSCs) is vital to address these challenges. The complexity and variability of RSCs in the region, exacerbated by harsh weather, make traditional surveillance methods inadequate for real-time monitoring. To overcome these limitations, a vision-based artificial intelligence approach is urgently needed to ensure effective, real-time detection of dangerous RSCs in the Tianshan road network. This paper analyzes the primary structures and architectures of mainstream neural networks and explores their performance for RSC recognition through a comprehensive set of experiments, filling a research gap. Additionally, T-Net, specifically designed for the Tianshan Expressway engineering project, is built upon the optimal architecture identified in this study. Leveraging the split-transform-merge structure paradigm and asymmetric convolution, the model excels in capturing detailed information by learning features across multiple dimensions and perspectives. Furthermore, the integration of channel, spatial, and multi-head attention modules enhances the weighting of key features, making the T-Net particularly effective in recognizing the characteristics of snow-covered and icy road surfaces. All models presented in this paper were trained on a custom RSC dataset, compiled from various sources. Experimental results indicate that the T-Net outperforms fourteen once state-of-the-art (SOTA) models and three models specifically designed for RSC recognition, with 97.44% accuracy and 9.79% loss on the validation set. Full article