Search Results (14)

Rail freight transport represents a key tool for the decarbonisation and greening of logistics chains within the European Union. However, in many Central and Eastern European countries, including the Slovak Republic, a vast network of industrial sidings (rail spurs) remains underutilized or neglected. This reduces the overall efficiency of transport infrastructure and represents a missed opportunity for sustainable transport development. This paper proposes a comprehensive public support model for rail sidings. It combines legislative analysis, a tax incentive mechanism, and analytical evaluation of transport and investment benefits. The methodology calculates the potential transport output of reactivated sidings. It also introduces three quantitative indexes: the Siding Efficiency Index (IEV), the Comprehensive Importance Index (ICV), and the Reactivation Value Index (RVI). These indicators allow for a structured, objective assessment of siding suitability for restoration and public funding. We applied the model to a sample of five sidings in Slovakia, deriving values from expert evaluations. The results show that objective indicators, performance estimates, and targeted public support can identify infrastructure with high revitalization potential. These tools help reintegrate such assets into sustainable transport flows. The analysis indicates that reactivating 5% of existing sidings could shift hundreds of thousands of tonnes of freight annually from road to rail. This change would reduce emissions and improve network efficiency. Full article

Grounded in information processing theory, this study explores how ecotourism decisions were formed within the rural district of Akdağmadeni (Türkiye), integrating both heuristic and systematic decision-making processes. The research adopts a two-phase mixed-methods design: First, it employs a survey-based factorial analysis involving 383 participants to examine preferences for nature-based activities such as trekking, cycling, and cultural tourism. Second, it uses in-depth interviews to investigate participants’ strategic evaluations of local landscape and heritage assets. The results reveal that individuals flexibly switch between intuitive and analytical judgments based on contextual factors. Key decision drivers identified include alignment with local development, ecological integrity, and socioeconomic contribution. This dual-process insight is operationalized through a novel “feature-based evaluation model” that synthesizes landscape identity values with cognitive-perceptual cues, providing a new lens for assessing geoheritage-based tourism behavior. It was determined that participants used both intuitive and systematic information processing strategies in their decision-making processes, and factors such as harmony with nature, economic contribution, and local identity were found to affect preferences. The study draws attention to the need to develop sustainable tourism policies, raise public awareness, and support infrastructure investments, and provides a road map for the effective use of the region’s ecotourism potential. Full article

In the age of digital twins, the digitalization of the urban environment is one of the key aspects in the optimization of urban management. The goal of urban digitalization is to provide a digital representation of physical infrastructure, data, information, and procedures for the management of complex anthropogenic systems. To meet this new goal, one must be able to understand the urban system through the integrated use of different methods in a multi-level approach. In this context, mobile surveying is a consolidated method for data collection in urban environments. A recent innovation, the mobile mapping system (MMS), is a versatile tool used to collect geospatial data efficiently, accurately, and quickly, with reduced time and costs compared to traditional survey methods. This system combines various technologies such as GNSS (global navigation satellite system), IMU (inertial measurement unit), LiDAR (light detection and ranging), and high-resolution cameras to map and create three-dimensional models of the surrounding environment. The aim of this study was to analyze the limitations, possible implementations, and the state of the art of MMSs for road infrastructure monitoring in order to create a DT (digital twin) for road infrastructure management, with a specific focus on extracting value-added information from a survey dataset. The case study presented here was part of the Turin Digital Twin project. In this context, an MMS was tested in a specific area to evaluate its potential and integration with other data sources, adhering to the multi-level and multi-sensor approach of the DT project. A key outcome of this work was the integration of the extracted information into a comprehensive geodatabase, transforming raw geospatial data into a structured tool that supports predictive maintenance and strategic road asset management toward DT implementation. Full article

Many studies and technology companies highlight the actual or potential value of Digital Twins, but they often fail to demonstrate this value or how it can be realised. This gap constitutes a barrier for infrastructure asset management organisations in their attempt to innovate and incorporate digital twinning opportunities in their decision-making processes and their asset management planning activities. Asset management planning activities often make use of existing value-based decision-support tools to select and prioritise investments in physical assets. However, these tools were not originally designed to consider digital twinning investments that also compete for funding. This paper addresses this gap and proposes a value-based analysis for digital twinning opportunities in infrastructure asset management. The proposed analysis method is tested with three rail and road infrastructure case studies: (i) real-time monitoring of a power transformer; (ii) BIM for the design, construction, and maintenance of a new railway line; and (iii) infrastructure displacement monitoring using satellite data (InSAR). The study shows that the proposed method provides a conceptual construct and a common language that facilitates the communication of digital twinning opportunities in terms of their relevance in different contexts. The proposed method can be used to support the investment decision-making process for investments in both physical and non-physical assets and help derive maximum value from the limited available resources. Full article

In the realm of transportation system management, various remote sensing techniques have proven instrumental in enhancing safety, mobility, and overall resilience. Among these techniques, Light Detection and Ranging (LiDAR) has emerged as a prevalent method for object detection, facilitating the comprehensive monitoring of environmental and infrastructure assets in transportation environments. Currently, the application of Artificial Intelligence (AI)-based methods, particularly in the domain of semantic segmentation of 3D LiDAR point clouds by Deep Learning (DL) models, is a powerful method for supporting the management of both infrastructure and vegetation in road environments. In this context, there is a lack of open labeled datasets that are suitable for training Deep Neural Networks (DNNs) in transportation scenarios, so, to fill this gap, we introduce ROADSENSE (Road and Scenic Environment Simulation), an open-access 3D scene simulator that generates synthetic datasets with labeled point clouds. We assess its functionality by adapting and training a state-of-the-art DL-based semantic classifier, PointNet++, with synthetic data generated by both ROADSENSE and the well-known HELIOS++ (HEildelberg LiDAR Operations Simulator). To evaluate the resulting trained models, we apply both DNNs on real point clouds and demonstrate their effectiveness in both roadway and forest environments. While the differences are minor, the best mean intersection over union (MIoU) values for highway and national roads are over 77%, which are obtained with the DNN trained on HELIOS++ point clouds, and the best classification performance in forested areas is over 92%, which is obtained with the model trained on ROADSENSE point clouds. This work contributes information on a valuable tool for advancing DL applications in transportation scenarios, offering insights and solutions for improved road and roadside management. Full article

In order to alleviate the conflict between populations and land resource, Tianjin adopted multi-phase reclamation projects to the formed large-scale artificial reclamation land. The reclamation areas, however, are prone to subsidence, which poses a significant threat to infrastructure as well as the safety and assets of the residents. The SBAS-InSAR was used to acquire surface deformation of Tianjin Binhai New Area from January 2017 to December 2022, analyze in depth the response relationship between land subsidence, reclamation project time, and land-use type. There is a strong correlation between surface deformation and reclamation time. Severe land subsidence occurred over newly reclaimed areas. In the offshore direction, the deformation values of the Nangang Industrial Zone, the Lingang Industrial Zone, and Hangu Harbor were −98 mm to −890 mm, 45 mm to −580 mm, and −140 mm to −290 mm, respectively. Significant differences in deformation were detected among different land-use types where reclamation projects were completed in the same time. Subsidence was positively correlated with surface load; in areas with higher surface loads, the surface settlement was also more severe. The average surface settlement for the heavy shipyard, with 67 grain storage tanks and 27 grain storage tanks, road, and bare land were −201 mm, −166 mm, −107 mm, −64 mm, and −43 mm, respectively. This study reveals significant differences of surface deformation in the reclamation completed at different times, and determines that the load is the main driving factor of settlement difference in the reclamation land completed at the same time. This has important guiding significance for preventing and controlling geological disasters in the reclamation area and later development planning. Full article

In the 21st century, one of the key requirements is to develop and maintain our infrastructure facilities most efficiently using the available resources. Tramways are of significant national economic importance and represent an important national asset. There are currently seven different types of superstructure systems in Hungary, based on the national regulations and the related requirements currently in force. This paper compares the paved tramway superstructure systems in the context of track geometry, through-rolled axle tons of track, and the age of track sections. Paved tracks have many benefits, but the main ones are easier maintenance and road traffic use. Elastically supported continuous rail bedding (ESCRB; in Hungary, this is known as “RAFS”) and “large” slab superstructure systems are used to create paved superstructure systems. Road crossings use the latter systems, while heavily loaded lines use several ESCRB systems. This article examines the geometrical changes in several ESCRB superstructure systems. A TrackScan 4.01 instrument was used to take measurements in June and September 2021 and in April 2022, September 2022, and May 2023. Track gauge, alignment, and longitudinal level are examined. Regardless of the ESCRB superstructure system or age, a medium-loaded line’s track gauge trendline increases, which means that the track gauge is widening and, regardless of traffic load or age, the average longitudinal level is constantly increasing from year to year. When it is a medium-loaded line, the average value of alignment increases slightly, and the trendline is almost straight, but it decreases when it is an extremely heavily loaded line. The authors will analyze how the reference track section will change in the future. Based on the results, it is important to assess how subsequent measurements affect the trend lines. Because the data evaluations show similar results, comparing open tramway tracks to paved ones is crucial. Full article

Recently, in Chile, infrastructure asset value has been incorporated into highway concession contracts. However, the current valuation model used for rigid pavements is not adapted to the standards and conditions of such projects. This study develops a valuation model for rigid pavements of interurban highway concessions and evaluates it in a case study. The proposed model captures the loss in asset value associated with the performance degradation over time, considering a typical Jointed Plain Concrete Pavement (JCPC) configuration. The value is calculated using performance indicators that represent the structural capacity and level of service provided to road users. The model represents a significant improvement compared to current asset valuation models used in highway concessions. It enables the public agency to objectively evaluate the preservation of asset value carried out by the private partner during the concession. Additionally, it could also be used as a tool to establish payments between infrastructure stakeholders. Some of the concepts applied could also be relevant for other highway assets existing in Public–Private Partnership (PPP) projects. Full article

Infrastructural assets such as roads, bridges, and buildings make a considerable contribution to national economies. These assets deteriorate due to aging, environmental conditions, and other external factors. Maintaining the performance of an asset in line with rational repair strategies represents a considerable challenge for decision-makers, who may not pay attention to developing adequate maintenance plans or leave the assets unmaintained. Worldwide, organizations are under pressure to ensure the sustainability of their assets. Such organizations may burden their treasury with random maintenance operations, especially with a limited budget. This research aims to develop a generalized condition assessment approach to monitor and evaluate existing facility elements. The proposed approach represents a methodology to determine the element condition index (CI). The methodology is reinforced with an artificial neural network (ANN) model to predict the element deterioration. The performance of this model was evaluated by comparing the obtained predicted CIs with ordinary least squares (OLS) regression model results to choose the most accurate prediction technique. A case study was applied to a group of wooden doors. The ANN model showed reliable results with R² values of 0.99, 0.98, and 0.99 for training, cross-validation, and testing sets, respectively. In contrast, the OLS model R² value was 1.00. These results show the high prediction capability of both models with an advantage to the OLS model. Applying this approach to different elements can help decision-makers develop a preventive maintenance schedule and provide the necessary funds. Full article

The article presents a comprehensive asset management method. Here presented method aims to bridge the economic approach to asset management with the technical approach to road infrastructure life cycle, namely its resilience and performance. The presented asset value calculation methods are based both on socio-economic viewpoints on community benefits of an asset, as well as the technical aspect of the technical condition and residual life calculations of a road infrastructure. In contrast to common road asset management methods, asset value is not arbitrarily annually depreciated, instead, it is exactly calculated based on pavement performance models, pavement construction fatigue and paving material properties. Road asset value calculation is based on the asset performance and the technical condition of a pavement structure and other objects. Road asset performance is defined in terms of society and road user demands put on road category and its qualitative standard. Road asset technical condition is evaluated by the procurement cost calculation and condition deterioration. Value of condition deterioration is defined by residual life expectancy based on fatigue and construction reliability of the road infrastructure. The cross-asset allocation method is used for the creation of programs for claim and allocation of funding. The aim was to increase the credibility of the road administrators with the public as they present their decisions based on road asset management, and to increase the level of acceptance for practitioners. Full article

One of the biggest problems of environmental protection in Serbia is landfills. It is often a case that the economic interests are predominant in the landfill sitting; thus, most landfills are not located according to standards. This study shows that detailed geological data assets combined with geographical modeling represents a reliable way to define and locate the landfill site. Geological evaluation is discussed in detail with regard to bedrock lithology, quaternary geology, geological structure, hydrogeology, surface runoff patterns, and topography. An approach combining geographical modeling and geology is presented for determining the sites suitable for landfill selection with respect to their geologic favorability. As opposed to numerous research papers on this topic, in the methodological procedure, special importance is devoted to the analysis of the geological criteria. In this way, it is significantly easier to determine the landfill area with the best characteristics due to geological structure and lithology which unequivocally and precisely indicates inadequate territories for candidate sites. The multicriteria decision analysis (MCDA) is based on geological criteria upgraded with road (primary, residential, secondary, and tertiary), settlements network, railway, airport, infrastructure, land use, hypsometry aquifer, wetland, and surface water. The score values are divided into four classes, i.e., restricted areas, suitable but avoid, suitable, and most suitable. Combining geographical modeling with geology led to the recognition of two locations to be most favorable for landfill site located in the most suitable area, which represents 25.3% of the study area. Full article

Road networks are disseminated of bridge structures whose typology reflects the time of design and construction of the transportation infrastructure and its relevance in the reference geographical area. Among others, masonry bridges are still widely operational, especially in those regions affected by a limited urbanization and a very high landscape value. As a consequence, the maintenance and the reliability of existing structures is a key issue for owners and managers of road and railway infrastructures. This circumstance leads to the development of an integrated approach able to cover the needs of knowledge of the technological and structural features of the bridge along with its history and current conditions. The main contribution of the study lies in the implementation of such an interdisciplinary approach through the application of archaeological stratigraphic method and 3D data management to historical masonry bridges. The survey and inspection protocol, whose first results are here presented, aims to improve the knowledge of the assets, and facilitate the visual inspection. The results refer to a road infrastructure located along the Aterno River in the surroundings of L’Aquila (Central Italy) and point out promising perspectives in terms of feasibility and scalability of the approach to large stocks of assets. Full article

Seasonality is a major issue for sustainable tourism as it governs the optimal use of investment, infrastructure and human capital. Given the increasing numerical and financial significance of Chinese outbound tourism, the ex-Yugoslavia (ex-Yu) countries, partaking in the Belt and Road Initiative, are presented with a potential boost to their Tourism and Travel Industry (T&T) by attracting Chinese travelers during the low season. In an attempt to provide an answer to the RQ and justify grounds for future research and efforts towards developing content and services for Chinese travelers, to be undertaken mostly by Tourism Boards and DMOs in ex-Yugoslavia, this paper explores several aspects: The importance of the T&T in the 6 ex-Yu countries, with focus on the Economic indicators; within the Triple Bottom Line’s (TBL) theme of Seasonality, the existence of meaningful overlaps or mismatches between trends in inbound tourism across ex-Yugoslavia countries and trends in China’s outbound tourism; if meaningful mismatches exist, especially in ex-Yu low seasons, could Chinese tourists be an asset? Although the focus is on the Economic dimension of the TBL through its theme of Seasonality, the other two dimensions, Social and Environmental, are also considered; potential effects and interactions of the Viable, Equitable and Bearable sub-dimensions are also discussed. The final findings present a very significant mismatch, with extreme gaps in trends between the ex-Yu countries’ inbound tourism in low seasons and the corresponding Chinese outbound tourism, the latter presenting very strong shoulders, almost matching the values of high, or even peak, season. In a scenario projecting a range of 0.04–0.38% of Chinese outbound tourists visiting ex-Yu countries, benchmarked vs. January 2018 values, indicates the statistical significance of the potential boost to the low season, with important growth rates for all countries except Croatia and Slovenia for the 0.04% case. Full article

In this study, we focus on resilience as the ability of specific infrastructure systems at the regional scale to absorb the shocks of extreme events, such as earthquakes. The occurrence of a disaster such as an earthquake leads to a rapid decrease in infrastructure performance. In the case of road networks, performance might refer to the number of drivers using the road within a certain period of time. The objective of this study is to propose a quantitative evaluation method to analyze road network performance (or performance loss) when natural disasters occur. Furthermore, we use cluster analysis and consider the performance loss and asset value in an attempt to propose a method to determine the critical path that should be prioritized for maintenance. This study aimed at analyzing hazard resilience from the network aspect through a scenario analysis depending on damage recovery after disaster occurrence. This study compared the hazard resilience speed to recover existing performance according to the scenario for damage recovery targeting the selected road network. It was found that the total increase in the utility (e.g., total travel time saved) gradually diminished as the restoration cost increased. Full article