Search Results (14)

Logistics centers play a significant role in regional economic growth and development by optimizing logistics chains, minimizing transportation and transfer costs, shortening transit times, and enabling centralized management through support services. Intermodal transportation is an important function that enables goods to be transported efficiently using multiple modes of transport at logistics centers. This study examines 12 operational logistics centers in Türkiye, evaluating five types of transportation: unimodal (highway, railway) and intermodal (highway/railway, highway/airway, and highway/marine). The assessment considers four key criteria (transportation cost, carbon emissions, transportation risk, and transportation time) under various transportation distance and volume scenarios. The Fuzzy AHP method is employed to weight these criteria, and a goal programming model is developed to optimize transport mode selection. Among the evaluated transport modes, air transportation was not selected in any scenario due to its high cost and carbon emissions, aligning with the study’s focus on cost-efficiency and sustainability. The findings provide scenario-based recommendations for the most suitable transportation modes at each logistics center, contributing to more efficient and sustainable logistics operations. 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

This study statistically evaluates the suitability of the construction industry as a diversification target for infrastructure corporations by integrating Data Envelopment Analysis (DEA-BCC), panel data regression, and entropy-based diversification metrics. Twenty actively operating highway companies in China were selected, and their annual reports from 2011 to 2021 were meticulously reviewed. This study quantifies the impact of diversification strategies on firm performance, resource allocation efficiency, and X-inefficiency. The findings reveal that strategic diversification into construction-related activities enhances operational efficiency and mitigates X-inefficiency, aligning with Penrose’s theory of surplus resource deployment. The study contributes a robust analytical framework for assessing diversification in the infrastructure sectors, offering actionable insights for corporations considering expansion into construction. The results underscore the importance of organizational optimization and business capability in reducing X-inefficiency and enhancing sustainable development, particularly in maturing markets where traditional growth avenues are limited. Full article

Bridges are assets in every society, and their deterioration can have severe economic, social, and environmental consequences. Therefore, implementing effective asset management strategies is crucial to ensure bridge infrastructure’s long-term performance and safety. Roadmaps can serve as valuable tools for bridge asset managers, helping bridge engineers make informed decisions that enhance bridge safety while maintaining controlled life cycle costs. Although some bridge asset management roadmaps exist, such as the one published by the United States Federal Highway Administration (FHWA), there is a lack of structured research roadmaps that are both region-specific and adaptable as guiding frameworks for similar studies. For instance, the FHWA roadmap cannot be universally applied across diverse regional contexts. This study addresses this critical gap by developing a research roadmap tailored to Idaho, USA. The roadmap was developed using a three-phase methodological approach: (1) a comprehensive analysis of past and ongoing Department of Transportation (DOT)-funded research projects over the last five years, (2) a nationwide survey of DOT funding and research practices, and (3) a detailed assessment of Idaho Transportation Department (ITD) deficiently rated bridge inventory, including individual element condition states. In the first phase, three filtering stages were implemented to identify the top 25 state projects. A literature review was conducted for each project to provide ITD’s Technical Advisory Committee (TAC) members with insights into research undertaken by various state DOTs. Moreover, in the second phase, approximately six questionnaires were designed and distributed to other state DOTs. These questionnaires primarily covered topics related to bridge research priorities and funding allocation. In the final phase, a condition state analysis was conducted using data-driven methods. Key findings from this three-phase methodological approach highlight that ultra-high-performance concrete (UHPC), bridge deck preservation, and maintenance strategies are high-priority research areas across many DOTs. Furthermore, according to the DOT responses, funding is most commonly allocated to projects related to superstructure and deck elements. Finally, ITD found that the most deficient elements in Idaho bridges are reinforced concrete abutments, reinforced concrete pile caps and footings, reinforced concrete pier walls, and movable bearing systems. These findings were integrated with insights from ITD’s TAC to generate a prioritized list of 23 high-impact research topics aligned with Idaho’s specific needs and priorities. From this list, the top six topics were selected for further investigation. By adopting this strategic approach, ITD aims to enhance the efficiency and effectiveness of its bridge-related research efforts, ultimately contributing to safer and more resilient transportation infrastructure. This paper could be a helpful resource for other DOTs seeking a systematic approach to addressing their bridge research needs. Full article

Highway alignment optimization is critical for developing sustainable and resilient transportation infrastructure. Traditional alignment selection methods frequently fail to comprehensively account for all of the diverse factors, including geometric compliance, traffic efficiency, land use factors, environmental impacts, and cost considerations, ultimately resulting in suboptimal project outcomes. To address these challenges, this study proposes a building information modeling (BIM)-based alignment optimization framework that integrates diverse datasets, sophisticated modeling techniques, and stakeholder collaboration. The proposed framework systematically enables the user to model terrain, design geometric features, simulate traffic, and conduct cost analysis and environmental impact assessments. A case study of the Dera Ghazi Khan Northern Bypass project in Pakistan, a critical infrastructure project designed to ease congestion and enhance regional connectivity, is presented to validate the proposed framework. Three alignment alternatives were analyzed, with the optimized solution (Alignment Option 2) demonstrating a 30% reduction in congestion, a 20% decrease in travel time, and a 6.48% reduction in construction costs compared to the other alignment alternatives. These outcomes highlight the transformative potential of BIM-driven optimization to significantly enhance sustainability, cost-efficiency, and operational performance. This framework offers a scalable and adaptable model to guide future infrastructure development initiatives toward more sustainable outcomes. Full article

Cold mix asphalt (CMA) pothole repair is extensively utilized in time-sensitive highway maintenance due to its rapid deployment and all-weather applicability. However, premature failures caused by suboptimal construction practices under operational constraints (e.g., emergency repairs and adverse weather) necessitate frequent reworks, inadvertently escalating material consumption and associated environmental burdens. To address this challenge, this study proposes a quality-driven optimization framework integrating enhanced Analytic Hierarchy Process (AHP) and Grey Relational Analysis (GRA). The methodology systematically evaluates 18 technical parameters across six critical construction phases—grooving/molding, cleaning/drying, bonding layer application, material paving, compaction, and edge trimming—to identify dominant quality determinants. The analysis highlights material placement and compaction as the most significant phases in the repair process, with specific technical parameters such as compaction standardization, paving uniformity, compactor dimension selection, and material application emerging as key quality drivers. To assess the feasibility of the optimized process, a grey relational analysis was adopted to compare the proposed protocol with the cold-patch practices currently adopted by two municipal maintenance agencies in Shanghai, demonstrating superior alignment with an ideal repair benchmark. The developed model empowers highway agencies to achieve dual operational–environmental gains: maintaining urgent repair efficiency while mitigating secondary resource depletion through reduced repetitive interventions. Full article

The increasing number of heavy-duty vehicles (HDVs) on roads has become a major contributor to harmful emissions, posing critical environmental challenges and exacerbating global warming. This study aims to establish correlations between road types and the emissions they generate, offering actionable insights for logistics planning and strategies to mitigate diesel vehicle emissions. The analysis is based on input data from a selected transport company, covering parameters such as vehicle type, average mileage, speed, and driving style, as well as environmental conditions like ambient temperature and humidity. Emissions and energy consumption levels are estimated using the COPERT model. A key research challenge involves accurately predicting and managing air pollution caused by HDVs under varying vehicular, technological, and fuel conditions, as well as fluctuating atmospheric and operational factors. The findings indicate that highway driving produces the highest emissions of pollutants such as Se and Zn, while urban peak hours record the highest levels of NO_x, NO, and NO₂. These results emphasise the critical role of strategic route selection in reducing total emissions and managing levels of individual harmful substances. This research highlights the importance of integrating sustainable practices into transport planning to reduce environmental impacts, align with global climate objectives, and advance sustainable development in the transport sector. Full article

This study presents an innovative methodology for Highway Route Selection (HRS), specifically tailored for mountainous terrains. The approach focuses on selecting the most suitable route for road alignment while prioritizing road safety and hydrological and geological considerations. Through systematic analysis, the methodology evaluates alternative road alignments by examining various risk factors related to geometric design, hydrological, and geological impacts. Utilizing Fault-Tree Analysis (FTA), 14 key design factors related to geometric design and environmental factors are identified. The results demonstrate the effectiveness of the methodology in selecting road alignments that enhance safety and mitigate environmental risks. A case study is presented where a 90-km segment of a road in Egypt’s Golden Triangle Project, characterized by challenging terrain and diverse geological features, is examined. Through detailed analysis, the study identifies critical design factors to enhance road safety and minimize environmental impact. The methodology’s comprehensive approach offers insights into road design, providing a quantitative framework for decision-making and mitigation strategies. Full article

In China, a substantial portion of highway asphalt pavements are no longer capable of accommodating increasing traffic volumes and necessitate renovation and expansion. Prior to commencing such activities, it is crucial to evaluate the performance of the existing asphalt pavements. This study developed a novel normal cloud framework integrating a comprehensive weighted indicator system for existing asphalt pavement. Five key performance indicators including riding quality index (RQI), rutting area ratio (R_r), cracking area ratio (C_r), patching area ratio (P_r), and pavement structural strength index (PSSI) were selected to holistically represent the pavement condition in highway renovation and expansion projects. Subsequently, a method was proposed to determine the weights of these indicators by integrating the analytic hierarchy process (AHP) and entropy. A normal cloud model was constructed to address data characteristics and representation of indicator fuzziness/randomness through digital cloud modeling. The model was applied to 12 sections of the Jingjintang Expressway (Tianjin section). The results revealed only one section where the normal cloud model differed from the pavement maintenance quality assessment (PQI) model. The 3D ground-penetrating radar detection results of this different section indicated that the normal cloud model more closely aligned with the road structure condition. Compared to absolute pass/fail criteria of the traditional PQI model, the cloud model offered enhanced sensitivity to define graded condition assessments essential for reconstruction planning and decision analysis. Therefore, the normal cloud model is more suitable for assessing the performance of existing asphalt pavements in highway reconstruction and extension projects compared to the PQI model. Full article

Landslides recurrently cause severe damage and, in some cases, the full disruption of many highways in mountainous areas, which can last from a few days to even months. Thus, there is a high demand for monitoring tools and precipitation data to support highway alignment selections before construction. In this study, we proposed a new system highway alignment selection method based on coherent scatter InSAR (CSI) and ~1 km high-spatial-resolution precipitation (HSRP) analysis. Prior to the CSI, we calculated and analyzed the feasibility of Sentinel-1A ascending and descending data. To illustrate the performance of the CSI, CSI and SBAS–InSAR were both utilized to monitor 80 slow-moving landslides, which were identified by optical remote-sensing interpretation and field investigation, along the Barkam–Kangting Highway Corridor (BKHC) in southwestern China, relying on 56 Sentinel-1A descending images from September 2019 to September 2021. The results reveal that CSI has clearer deformation signals and more measurement points (MPs) than SBAS-InSAR. And the maximum cumulative displacements and rates of the landslides reach −75 mm and −64 mm/year within the monitoring period (CSI results), respectively. Furthermore, the rates of the landslides near the Jinchuan River are higher than those of the landslides far from the river. Subsequently, to optimize the highway alignment selection, we analyzed the spatiotemporal evolution characteristics of feature points on a typical landslide by combining the −1 km HSRP, which was calculated from the 30′ Climatic Research Unit (CRU) time-series datasets, with the climatology datasets of WorldClim using delta spatial downscaling. The analysis shows that the sliding rates of landslides augment from the back edge to the tongue because of fluvial erosion and that accelerated sliding is highly related to the intense precipitation between April and September each year (ASP). Consequently, three solution types were established in our method by setting thresholds for the deformation rates and ASPs of every landslide. Afterward, the risk-optimal alignment selection of the BKHC was finalized according to the solution types and consideration of the construction’s possible impacts. Ultimately, the major problems and challenges for our method were discussed, and conclusions were given. Full article

Traffic sensors play a pivotal role in monitoring and assessing network-wide traffic conditions. However, the substantial costs associated with deploying an extensive sensor network across real-world highway systems can often prove prohibitive. Thus, the strategic selection of optimal sensor locations within budget and resource constraints becomes imperative, leading to the well-known Traffic Sensor Location Problem (TSLP). In this study, we introduce a novel framework to address the TSLP for large-scale highway networks, focusing on maximizing information gain in a joint vector space that comprehensively captures both network topology and segment-level features. To solve this optimization problem, we devised a genetic algorithm (GA) with penalty handling. Additionally, we developed a physics-guided random walk algorithm, which not only significantly reduces the search space but offers remarkable flexibility in striking a practical balance between computational load and the confidence of achieving global optimality. For illustration purposes, the proposed framework was applied to the Savannah highway network in Georgia. The results from our GA method align well with those from exhaustive research, but with significantly reduced computational time. By leveraging information theory and maximizing information gain in a low-dimensional vector space, the proposed framework permits parallel, scalable computation and offers considerable potential in the strategic planning and deployment of various sensors for expansive, real-world highway networks. Full article

Promoting the management of the over-limit of freight transport vehicles plays an important role in the sustainable development of the highway industry. Vehicle outer contour dimension measurement is a key element in highway over-limit detection. The current detection approaches and research methods, however, are insufficient for high-precision flow detection. Therefore, this study proposes an algorithm for measuring the dimensions of a truck’s outer contours, using unmanned aerial vehicle (UAV) binocular stereo vision. First, this study leverages a binocular camera mounted on a UAV to reconstruct the 3D point clouds of the truck. Second, the point cloud data are clustered using an FoF (Friends-of-Friends algorithm); this recognizes the cluster of truck points according to the truck’s characteristics. Finally, the principal component analysis and the Gaussian kernel density estimation are used to generate the outer contour dimensions of the trucks. Twenty model vehicles are selected as test objects to verify the reliability of the algorithm. The average error of the algorithm is represented by calculating the average value of the difference between the real size and the predicted size of the three dimensions. The experimental results demonstrate that the average error of this measurement approach is less than 2.5%, and the method is both stable and robust. This approach aligns with national regulations for over-limit detection. Full article

Using the plane alignment design of the Wuhai–Maqin highway as the background of this study, based on the Fluent–Euler two-fluid model, the response law of the wind–sand flow to the embankment under different angles, different curve radii, and different surface windward factors were studied. Additionally, the accuracy of the numerical simulation was verified by the distribution of sand accumulation on the embankment site. The results show that when the wind–sand flow passes through the embankment, and when the angle between the wind direction and the straight embankment gradually decreases from 90° (vertical) to 0° (parallel), the speed-division range is correspondingly shortened. Under the influence of plane alignment, the diversion effect leads to a certain difference in the flow-field structure at different positions of the line. The convex windward embankment has the effect of dredging the wind–sand flow outward. The concave windward embankment has the effect of gathering the wind–sand flow inward. The dredging and gathering effects of the flat curve on the wind–sand flow decreases with the increase in the radius. In the plane linear design, line direction should be parallel to the dominant wind direction as much as possible. If a flat curve needs to be set, the convex windward curve should be given priority, and a large radius curve should be selected as much as possible. Full article

The main objective of this work is to analyse the potential for potable water savings in university buildings by using stormwater collected from permeable pavements. Six buildings located on the campus of the Federal University of Santa Catarina (UFSC) were selected to obtain monthly water consumption patterns and parking lot areas. The same six buildings were then evaluated considering their location in eight different cities in Brazil, with different rainfall patterns. Simulations using the computer programme Netuno were run to obtain the potential for potable water savings in each building and city combined. The structural design of permeable pavements was also assessed using two methods available in the literature, that is, the American Association of State Highway and Transportation Officials (AASHTO) and Brazilian Portland Cement Association (ABCP). The hydrological-hydraulic design of the permeable pavement was also carried out. The designed thicknesses were compared with the thicknesses obtained using the computer programme Permeable Design Pro. The potential for potable water savings between 18.4% and 84.8% was obtained, depending on the city, building and non-potable water demand considered. For the structural design, the thicknesses obtained by using both methods were similar; however, it was observed that the AASHTO method better represents the pavement model. Regarding the hydrological-hydraulic design, the differences obtained show that the simplification performed for the pavement drainage was in favour of safety. In conclusion, the use of permeable pavements in stormwater harvesting systems is promising, aligning the drainage aid, structural capacity and potential for saving potable water. Full article