Regional Highway Research Articles

Identification of spatial clusters of potentially toxic elements in different soil types using unsupervised machine learning and compositional data analysis

Soil health is important, with soil chemical composition data, including potentially toxic elements (PTEs) being one of its conceptual components. This study aims to reveal the spatial distribution patterns of soil PTEs contents, identify their potential sources, and unveil their geochemical associations in Aragatsotn region, Armenia. For that purpose, the contents of Cr, V, Ti, As, Zn, Cu, Co, Fe, Mn, Ba, and Pb were determined using an X-ray fluorescence spectrometer. The mean contents of Cr and As exceeded their upper continental crust by 1.5 and 3.1 times and their maximum acceptable values by 1.5 and 1.5 times. The analysis demonstrated the presence of sites where all these elements displayed comparatively higher values. The combined application of compositional data analysis and geospatial mapping revealed multivariate outliers, which were located in structural-metallogenic zones with active ore exploitation . The application of unsupervised machine learning algorithm unveiled three groups within the main dataset and the clr-biplot identified the source-specific elements. Particularly, Group I included Cu and displayed the highest mean value among the identified groups. The soil samples included in Group I were in areas where Calcisols were developed and comparatively high Cu contents were attributed to agricultural activities and vehicle emissions. Group II is represented by the geochemical association of Fe, Co, Cr, Mn, Zn, and As. The formation of this group is conditioned by volcanic rocks of the local geological origin. However, no spatial pattern was identified in Group II distribution aligned with soil types. Group III included Ti, V, Pb, and Ba, which may have a mixed origin as it is spatially distributed in areas where regional highways pass through and where Group II elements also exhibit their higher values.

Analysis of the State of Highways of Regional Importance in the Russian Federation

The purpose of the article is to analyze the regional road network of the Russian Federation, to identify the main factors affecting its condition depending on the federal district. Recently, investments have improved the situation in the field of repair and construction of regional roads, but the condition of regional roads remains unsatisfactory — about half of all regional roads do not meet regulatory requirements. Based on the analysis of the regional road network, it is necessary to make a decision on the investment of a particular road facility. The article examines the relationship between factors such as the percentage of regional highways that do not meet regulatory requirements and the individual rating of the standard of living. The question is also raised about identifying the most problematic places in the regional road network based on mathematical statistics methods, building dependencies of the share of bad regional roads on the length of federal roads, on the road climate zone, on the gross regional product per capita, on population, on the density of the road network and other factors. The main research methods are correlation and regression analysis. As a result of the study, a statistical analysis of the quality of the highway network of regional significance in the federal districts of the Russian Federation for 2007–2022 was carried out, the main patterns and dependencies of the percentage of roads that do not meet regulatory requirements on the density of the road network, gross regional product, and road climate zone were revealed. Conclusions are obtained that at the moment the state of regional highways and the gross regional product are poorly correlated values. On the contrary, the condition of regional roads strongly correlates with the index of quality of life in the region and the length of federal roads. In the first case, there is a strong positive correlation, in the second — a strong negative one.

GEOGRAPHICAL FACTORS OF REVITALIZATION OF RURAL SETTLEMENTS “WITHOUT POPULATION

The article proposes a method for identifying “reviving” rural settlements (RS). Case studies of the Tver region RS revealed what features of the geographical location determine a settlement opportunities for revitalization. The previous typology, based on the analysis of satellite images, showed a considerable differentiation in the degree of RS degradation, classified according to the 2010 census as “without population”. Further work to determine the leading factors of revitalization was based on the study of those RS where the houses and outbuildings, identified by satellite images, have been preserved to the greatest extent. Nearness to rivers and water bodies, position relative to federal and regional highways, and location near the regional and/or district center were chosen as key features of the geographical location that have an effect on the prospects for revitalization of a territory. The presence of registered residents (according to current records) and demarcated cadastral plots are indicators of the RS revitalization. The study showed that one third of all RS, which fell into the category “without population” according to 2010 statistics, could now be considered “reviving”. A key factor in the revitalization of rural settlements of the Tver region is their nearness to the river, mainly to the Volga River. Another important factor is the location in the zone of influence of main centers, primarily the city of Tver. The main function is the recreational (dacha) use of such villages.

Spatial–Temporal Evolution of Coupling Coordination Development between Regional Highway Transportation and New Urbanization: A Case Study of Heilongjiang, China

The coupling coordination relationship between regional highway transportation and new urbanization is an increasingly important issue in the field of regional sustainable development. This paper aims to establish an index system and develop an integrated method to measure the coupling coordination between regional highway transportation and new urbanization. The evaluation index system comprised two hierarchies, six aspects and 19 indexes, which were weighted by the entropy weight method (EWM). Furthermore, a coupling degree model (CDM) and a coupling coordination degree model (CCDM) were established based on the statistical data from 2011 to 2017 in Heilongjiang Province, China. The ArcGIS spatial analysis method was utilized to analyze the spatial–temporal coupling evolution characteristics of the two subsystems. The findings revealed that the development level of the two subsystems showed an upward tendency. The coupling degree between the two subsystems was leaping from antagonistic stage to breaking-in period. The coupling coordination degree between the two subsystems was the transition stage from imbalance to coordination. Specifically, the spatial differentiation characteristics of the coupling coordination development between the two subsystems were prominent in Heilongjiang Province, China. The results showed that the approach combining CCDM with ArcGIS spatial analysis can be applied as an effective method to explore the spatial–temporal evolution of coupling coordination development.

The use of gravel crushing siftings sands for the production of cast emulsion-mineral mixtures «Slarri Sil»

In the article, the authors present the main use results of mineral materials from local open cast mines for the cast emulsion-mineral mixtures making «Slarri Sil» for the protective wearing course installation for asphalt concrete pavements. The production of cast emulsion-mineral mixtures «Slarri Sil» using sand sifting from crushing local gravel materials was carried out on regional category III highways (according to traffic intensity) of the Amur Federal Highway passing through the Amur Region. In accordance with the requirements for mineral materials for the production of cast emulsion-mineral mixtures «Slarri Sil», it was ruled to use the sandy fraction of the stone crushing sifting products of igneous rocks in accordance with National State Standard 8736 with the following properties quality indicators: strength grade greater than or equal to 1200, abrasion grade greater than or equal to I-1, frost resistance grade greater than or equal to F50. Due to the limited number of deposits with siftings for crushing dense rocks and the length of regional highways in the Amur Region, deposits use for the production of cast emulsion-mineral mixtures throughout the entire route make the construction of wear layers unprofitable. The research objective is the local sand and gravel mix of the Zeya and Bureya rivers for the production of Slurry Seal type cast emulsion-mineral mixtures. The authors present the results of determining the physical and mechanical parameters and grain compositions of sands from siftings of crushing sand and gravel mix and rock for protective wear layers of asphalt concrete pavements. The results of determining the adhesion of the binder with the mineral part of cast emulsion-mineral mixtures «Slarri Sil» on various sands of crushing siftings are presented. The results of testing sands from siftings of crushing gravel and siftings of igneous rocks for wet abrasion are shown. The results of experimental studies made it possible to substantiate the use of sand from gravel crushing siftings for the construction of a protective wear layer for asphalt concrete pavement made of cast emulsion-mineral mixtures type «Slarri Sil» on the roads of the Amur Region, including federal ones. The obtained results were used to prepare the standard of the organization company standard — closed stock corporation «Asfalt» — 001-2012 «Production of works on the installation of protective wear layers for asphalt concrete pavements from cast emulsion-mineral mixtures of the Slurry Seal type».

Anticipating Spatial–Temporal Distribution of Regional Highway Traffic with Online Navigation Route Recommendation

Detailed anticipation of potential highway congestion is becoming more necessary, as increasing regional road traffic puts pressure on both highways and towns its passes through; tidal traffic during vacations and unsatisfactory town planning make the situation even worse. Remote sensing and on-site sensors can dynamically detect upcoming congestion, but they lack global and long-term perspectives. This paper proposes a demand-network approach that is based on online route recommendations to exploit its accuracy, coverage and timeliness. Specifically, a presumed optimal route is acquired for each prefecture pair by accessing an online navigation platform with its Application Programming Interface; time attributes are given to down-sampled route points to allocate traffic volume on that route to different hours; then different routes are weighted with the origin–destination traveler amount data from location-based services providers, resulting in fine-level prediction of the spatial–temporal distribution of traffic volume on highway network. Experiments with data in January 2020 show good consistency with empirical predictions of highway administrations, and they further reveal the importance of dealing with congestion hotspots outside big cities, for which we conclude that dynamic bypassing is a potential solution to be explored in further studies.

Impact of Infrastructure Construction, Industrial Structure and Economic Development on Regional Highway Freight Volume

As an indispensable part of the urban economy, urban freight transport plays an essential role in promoting the development of the national economy. It is necessary to clarify how a series of socio-economic developments, such as infrastructure development and economic development, affect regional highway freight volumes. Based on the panel data of each city in China from 2005 to 2019, this study selects 14 indicators closely related to urban economy and highway freight volume and empirically analyzes the relationship between these 14 indicators and regional highway freight volume using panel regression and generalized additive model (GAM) regression. The results show that the infrastructure construction with various types of vehicles has a non-linear influence on highway freight volume. The proportion of secondary and tertiary industries shows that P values are all zero in the corresponding cointegration test and causality test, indicating that there is a cointegration relationship between them and highway freight volume. Both are one-way Granger reasons for urban freight volume.

Driver Source-Based Traffic Control Approach for Mitigating Congestion in Freeway Bottlenecks

On-ramp control is an effective way to mitigate traffic congestion in freeways. In this study, a traffic control approach is developed based on the OD data of a regional freeway to alleviate the traffic overload in freeway bottlenecks. We first locate the major driver sources of the freeway bottlenecks and identify the on-ramps for implementing the traffic control schemes. Next, the differential evolution algorithm is employed to calculate the optimal control time at each traffic control on-ramp. The results indicate that the major driver sources of the freeway bottlenecks are limited. Traffic congestion in the freeway bottlenecks can be effectively mitigated by adaptively controlling the waiting time of vehicles at the on-ramps of their major driver sources.

Research on Collaborative Optimization Model of Tourism Resources and Highway Network Based on IoT Network and Deep Learning

With the development of tourism, people's demand and concern for tourist transportation are increasing. Integrating expressway resources into the tourism transportation network is the current trend and direction of expressway network planning. With the rapid development of the Internet, people can easily get the information resources they want, but at the same time, the problem of information overload also arises. The depth of highway access is insufficient, there is a lack of systematic consideration of tourist resources in the area, a systematic tourism network has not been developed, and tourism resources are inaccessible. These issues have stifled regional tourism's fast growth, necessitating research into the convergence of tourist resource development and highway network optimization. The building of highway layouts and the growth of the tourist sector have reached a point where they interact and impact one another, and the degree of this contact has progressively risen. However, there is still a significant disparity in the degree of cooperation across areas. This paper considers the collaborative optimization of tourism resource development and highway network optimization, analyzes its impact on traffic volume distribution, introduces the two-level programming model of collaborative optimization, and determines that the goal of the upper model is to maximize social net income. It also considers the collaborative optimization of tourism resource development and highway network optimization on the basis of clarifying the game relationship between planning decision-makers and traffic travel and considers the collaborative optimization of tourism resource development and highway network optimization on the basis of in-depth learning. For the total investment of tourism construction projects, the time cost saved by highway network optimization, and the total tourism revenue, the lower-level model aims to minimize the travel time of a single user. This paper shows that the layout planning of the regional tourism highway network from the perspective of tourism resources can improve the accessibility of regional high-quality tourism resources and meet the requirements of the coordinated development of highway tourism and resources.

A scalable deep learning system for monitoring and forecasting pollutant concentration levels on UK highways

The construction of intercity highways by the government has resulted in a progressive increase in vehicle emissions and pollution from noise, dust, and vibrations despite its recognition of the air pollution menace. Efforts that have targeted roadside pollution still do not accurately monitor deadly pollutants such as nitrogen oxides and particulate matter. Reports on regional highways across the country are based on a limited number of fixed monitoring stations that are sometimes located far from the highway. These periodic and coarse-grained measurements cause inefficient highway air quality reporting, leading to inaccurate air quality forecasts. This paper, therefore, proposes and validates a scalable deep learning framework for efficiently capturing fine-grained highway data and forecasting future concentration levels. Highways in four different UK regions - Newport, Lewisham, Southwark, and Chepstow were used as case studies to develop a REVIS system and validate the proposed framework. REVIS examined the framework's ability to capture granular pollution data, scale up its storage facility to rapid data growth and translate high-level user queries to structured query language (SQL) required for exploratory data analysis. Finally, the framework's suitability for predictive analytics was tested using fastai's library for tabular data, and automated hyperparameter tuning was implemented using bayesian optimisation. The results of our experiments demonstrate the suitability of the proposed framework in building end-to-end systems for extensive monitoring and forecasting of pollutant concentration levels on highways. The study serves as a background for future related research looking to improve the overall performance of roadside and highway air quality forecasting models.

Geo-Locating and Identifying Wrong-Way Driving Entrance Points in Bexar County Highways by Implementing Mathematical Modeling and Land-Use Impact Assessment

Wrong-way driving (WWD) leads to high severity crashes and is a major concern for transportation managers. This study aims to identify WWD entry points of urban highway ramps and develop an analysis methodology using basic knowledge of WWD occurrences. The methodology examines the origin and driving behavior of impaired drivers by utilizing a land-use impact assessment (alcohol-serving establishments (ASE) proximity to exit ramps) and analyzing three distinct mathematical models: wrong-way driving events excluding 911 call analysis, wrong-way driving events including 911 call analysis, and 911 calls without wrong-way driving crashes. Data were collected and implemented from Google Maps, the 911 call database, wrong-way crash database, ASE location database, and a video camera database of a recent WWD study. Out of a total 543 exit ramps, 213 exit ramps are associated with approximately 98% of total WWD entries. The hotspots analysis of WWD entrance locations have found four major hotspots locations in Bexar County, Texas study area: 410 Loop near Culebra Road and Jackson Keller Road, 1604 Loop near US-281 highway, and IH-10 near the Medical Drive area. Outcomes of this study include a methodology for determining WWD entry locations of regional highways.

Feasibility of Artificial Slope Hazards Identification in Regional Mountainous Highway Using SBAS-InSAR Technique: A Case Study in Lishui, Zhejiang

Safety status of artificial slopes is significant for the operation and maintenance of highway to mitigate the risk; thus, slope hazard identification is necessary. In order to realize large-area and low-cost application for regional highway, taking the Longqing Highway (length of 55 km) as a case study, the SBAS-InSAR (Small Baseline Subset-Interferometric Synthetic Aperture Radar) technique is adopted to detect the ground deformation and conduct hazard identification based on slope dip, aspect, geological data and historical hazard record. Field survey is carried out to verify the identified potential hazards. Results show that the detected potential hazards are distributed mainly in the areas consisting of granite residual and the Quaternary soil. Six potential hazards identified by the SBAS-InSAR-based method are roughly in accordance with the on-site verification. It is suggested that the SBAS-InSAR technique has the ability to obtain the slope deformation accurately and reveal the safe condition of the slopes. The SBAS-InSAR technique can be suitable for assistance in regional highway slope inspection.

Modernization of the peripheral region's economy in the context of geostrategic priority implementation

Subject. This article examines the transformations taking place during the modernization of the economy of the Amur Oblast. Objectives. The article aims to assess the changes taking place in the transport system of the Amur Oblast. Methods. For the study, we used the methods of comparative and statistical analyses. Results. We found that along with the implementation of major transport projects in the Amur Oblast, significant efforts were made in terms of the construction and reconstruction of regional highways and local roads, and the development of railway, air and water transport facilities. Conclusions. Systemic problems that persist in the transport complex and govern infrastructure constraints in the socio-economic development of the Oblast impede the implementation of transit functions in interregional and international transport.

Urban traffic modeling and pattern detection using online map vendors and self-organizing maps

Typical traffic modeling approaches, such as network-based methods and simulation models, have been shown inadequate for urban-scale studies due to the fidelity issue of models. As a go-around, data-driven models have received increasing attention recently. However, most data-driven methods have been restricted by their data source and cannot be scaled up to manage urban- and regional-scale studies. Regarding this issue, this research proposes a pipeline that collects traffic data from online map vendors to bypass data limitations for large-scale studies. The study consists of two experiments: 1) recognizing the dominant traffic patterns of cities and 2) site-specific predictions of typical traffic or the most probable locations of patterns of interests. The experiments were conducted on 32 Swiss cities using traffic data that were collected for a two-month period. The results show that dominant patterns can be extracted from the temporal traffic data, and similar patterns exist not only in various parts of a city but also in different cities. Moreover, the results reveal that a country-level lockdown decreased traffic congestions in regional highways but increased those connections near the city centers and the country borders.

Application of Landsat Imagery and Vegetation Index Property to Assess the Shoreline Changes Along Cox’s Bazar–Teknaf Coast

Bangladesh is located at the head of the Bay of Bengal. The coast of Bangladesh is known as a zone of vulnerabilities as well as opportunities which involves coast and island boundaries. The eastern coastal zone consists of sandy beaches and hilly areas and is morphologically very dynamic. This shoreline is an important zone which facilitates tourism opportunity, fishing industry, natural resources and regional highway. Cox’s Bazar-Teknaf shoreline has been experiencing severe erosion at a number of places due to wave action. Wave and wind induced motion results in sediment distribution and shaping of nearshore morphology. The study has been performed by using Remote Sensing and GIS techniques. The shoreline shifting analysis has been performed by the process of open source Landsat images from 1980 to 2017. Satellite derived band algebra; Normalized Difference Vegetation Index has been utilized to identify the vegetation cover. The satellite images of an object carry a unique index property. In this study the index property of vegetation cover has been used to delineate more stable shorelines. At different locations, the average change in shoreline goes up to 120 m in erosion and 100 m in deposition. Based on the coastline shifting the erosion behaviour and the vulnerable areas are identified.
 Journal of Engineering Science 12(1), 2021, 21-28

Standard structures of road pavements for highways of the Baikal region

A network of regional highways in the Russian Federation urgently needs good and cost-efficient road constructing materials. Obtaining such materials is possible by strengthening local soils with inorganic binders. For the purpose of efficient application of such materials in the process of structures roads and highways in the Baikal region it is necessary to develop standard structures, which take account of regional characteristics. The regulatory documents in force on the territory of the Russian Federation do not contain standard structures in which materials reinforced with inorganic binders are used. The paper discusses some results of investigation bound up with development of standard structures of road pavement using local soils of the Baikal region, which are reinforced with inorganic binders.

United States fatal pedestrian crash hot spot locations and characteristics

US pedestrian fatalities are at their highest level in nearly three decades and account for an increasing share of total traffic fatalities (16%). To achieve the vision of a future transportation system that produces zero deaths, pedestrian safety must be improved. In this study, we screened the entire US roadway network to identify fatal pedestrian crash “hot spot” corridors: 1,000-meter-long sections of roadway where six or more fatal pedestrian crashes occurred during an eightyear period. We identified 34 hot spot corridors during 2001-2008 and 31 during 2009-2016. While only five corridors were hot spots during both analysis periods, the 60 unique hot spots had remarkably consistent characteristics. Nearly all (97%) were multilane roadways, with 70% requiring pedestrians to cross five or more lanes. More than three-quarters had speed limits of 30 mph or higher, and 62% had traffic volumes exceeding 25,000 vehicles per day. All had adjacent commercial retail and service land uses, 72% had billboards, and three-quarters were bordered by low-income neighborhoods. Corridors with these characteristics clearly have the potential to produce high numbers of pedestrian fatalities. We also used hierarchical clustering to classify the hot spots based on their roadway and surrounding landuse characteristics into three types: regional highways, urban primary arterial roadways, and New York City thoroughfares. Each context may require different safety strategies. Our results support a systemic approach to improve pedestrian safety: Agencies should identify other roadway corridors with similar characteristics throughout the US and take actions to reduce the risk of future pedestrian fatalities.

Development of typical flexible road pavement catalog for regional and intermunicipal highways in Russian Federation (using the example of the Republic of Bashkortostan)

Road pavements in Russia are now working in difficult conditions of ever-growing vehicular traffic intensity. Current methodology for designing flexible road pavements has a number of serious shortcomings, where the best design experience and actual operating conditions of highways are not fully taken into account. In some cases, this leads to ineffective pavement structures design with a short service life. On many roads, rutting and premature wear of road surfaces appear already in the first years of their operation. Drainage systems are silted up in the first years of working. At the same time, geosynthetic materials are sometimes used unreasonably. The service life of roadway surfaces does not comply with the current regulations. In Russia, effective road-building materials are not yet fully used, local road-building materials and industrial waste reinforced with binders are little used. With exception of certain regions of the country, actual experience of operating various road structures with identification of the most optimal solutions is still poorly subject to consideration. Thus, there is an urgent need to develop designs of typical road pavements for various regions of Russia, which will ensure their efficient operation. To develop typical pavement designs, it is necessary to analyze existing ones in real conditions of their operation.

ПОВЫШЕНИЕ БЕЗОПАСНОСТИНА НЕРЕГУЛИРУЕМЫХ ПЕРЕКРЕСТКАХ АВТОМОБИЛЬНЫХ ДОРОГ

The article presents the results of studies of the organization of traffic at the T-shaped intersection of regional highways: highway 60K-245 - highway 60K-12, connecting the village of Kamenolomni with the city of Novocherkassk, Rostov region. The research is based on the conducted field survey of traffic intensity. As a result, a conditional cartogram of the traffic intensity of vehicles was developed, an analysis of conflict points at the intersection was carried out, and traffic light graphs were calculated for the current traffic intensity of traffic flows.

Specifity of the present-day soil temperature regime in a peat plateau (southern part of Bolshezemelskaya tundra) at locations crossed by regional highway.

Specifity of the present-day soil temperature regime in a peat plateau (southern part of Bolshezemelskaya tundra) at locations crossed by regional highway.