Road Infrastructure Elements Research Articles

ANALYSIS OF THE IMPACT OF NATURAL HAZARDS ON TOURISM ON THE LEFT BANK OF LAKE IZVORU MUNTELUI (NORTH-EASTERN ROMANIA)

One of the areas with great touristic potential in Romania’s mountains is Izvoru Muntelui Lake (Neamt county) from the western slopes of the Stânișoara Mountains in the Eastern Carpathians. The area is remarkably picturesque in terms of both the natural surroundings and history, including traditions, folklore, and ethnography. Nevertheless, the region is exposed to natural risk phenomena such as floods, landslides, crumbling, etc., which can affect different economic fields, including tourism. The present study aims to analyze the relationship between this zone's natural hazards and tourism activities and their impact. Our approach is based on quantitative and qualitative analysis, interview and questionnaire techniques, but also on literature review, field research, statistics, overlay and spatial mapping of data using GIS techniques and critical interpretation of results through mathematical statistics using Covariance Product of Deviations from the mean and the Bravais-Pearson linear correlation coefficient to measure the intensity of the interdependence between the degree of damage to the road infrastructure and the tourist infrastructure. The results show that the landslides significantly impact the public infrastructures between Poiana Teiului and Bicaz, heavily affecting the national road DN15. A total of 73 impact points were inventoried, representing sections of roads and road infrastructure elements affected by landslides. At the same time, the analysis of the responses to the questionnaire revealed that natural hazards, especially landslides and floods, are perceived as a threat by most tourism operators in the area. The classification of the vulnerability of tourism infrastructure into four categories (low, medium, high, and very high), based on susceptibility maps, has led to the determination of vulnerability to landslides, revealing the following findings: four accommodation units have a medium vulnerability index, two have a high vulnerability index, and one records a very high vulnerability index. It is highlighted that an accurate perception of natural hazards can contribute to increasing the awareness and preparedness of vulnerable people, thus increasing the resilience of present and future generations.

Rekonstrukcja miejsca zdarzenia drogowego w oparciu o dane geoprzestrzenne Geoportalu Krajowego

The purpose of the article is to analyze the potential use of free spatial data available in the National Geoportal to support traffic accident reconstruction. The research focuses on the capabilities and limitations of using LiDAR and orthophotomaps data in the context of reconstructing traffic accident scenes. A comparative methodology was employed, involving the analysis of geospatial data in relation to traditional surveying techniques, exemplified by a real traffic accident analysis using the PC-Crash soft-ware. The main findings of the research indicate high precision of orthophotos and LiDAR data in reproducing the actual topography and elements of road infrastructure. The analysis conducted on a 3D model created from LiDAR data showed that modern measurement techniques allow a more accurate reconstruction of the accident's trajectory and assessment of road visibility conditions. Integrating these data with traditional measurement methods can significantly enhance the standards of forensic experts' work, contributing to an increased accuracy in determining accident scenarios and, more broadly, to a better understanding of accident causes.

AIRBORNE LASER SCANNER AS A DATA SOURCE FOR BUILDING SELECTED ELEMENTS OF AN INTELLIGENT DATABASE FOR TRANSPORTATION

In this study, the main objective was to detect the road network and key road infrastructure elements based on airborne laser scanning data. The study included identification of the road network and determination of its axes using three independent methods, as well as detection of horizontal signs such as pedestrian crossings. The analysis process was based mainly on digital image processing methods, based solely on lidar data, without using information from other sources. The results of the analysis showed that the use of lidar data provides a fast and effective method for continuously updating information on road infrastructure and expanding the transportation database. This potentially opens the door to effectively updating relevant data in the area of transportation infrastructure.

Systematic Testing of Road Markings’ Retroreflectivity to Increase Their Sustainability through Improvement of Properties: Croatia Case Study

Road markings are important elements of road infrastructure, influencing traffic safety. Since they are deteriorating systems, their upkeep through renewals is important. To assure the quality of the renewal jobs, the systematic testing of retroreflectivity, which is the key performance parameter of road markings, was imposed in Croatia. Results from two decades of annual measurements of renewal jobs are provided. For the first decade, the measurements were taken statically, at spot locations, and later dynamically, across the entire road segments. When the evaluation started, only 1 out of 18 tested job sites was exceeding the minimum requirements; only after 8 years of measurements, 100% of the jobs exceeded the minimum demands. A subsequent switch to dynamic testing revealed that, on average, only 71% of the renewed road markings were in satisfactory condition and approximately 1.22% of the analysed line lengths had grossly substandard retroreflectivity. These results demonstrated that the field verification of jobs quality is necessary and simultaneously showed that static localised testing was not adequate. The outcome underlines the need for the strict supervision of road maintenance contracts to maximise the benefits for the society: through the better visibility of road markings, road safety should also improve, and the entire system will become more sustainable.

Methodology of Spatial Data Acquisition and Development of High-Definition Map for Autonomous Vehicles – Case Study from Wrocław, Poland

Autonomous drive systems are a dynamically developed sector of the automotive industry. The key problem in such technological solutions is to provide a reliable navigation system, which is typically based on high-definition (HD) maps supporting the identification of the position of a maneuvering vehicle. HD maps should include possibly up-to-date and detailed information on traffic lanes and on the traffic rules and regulations on such lanes. An effective development of an HD map should be based on the geodetic measurement methods, which ensure efficient and accurate acquisition of spatial data. This article presents the results of an experiment consisting in the manipulation of data obtained with the use of the mobile laser scanning method and further in employing this data in the development of an HD map in an open-source environment. The applied measurement technology and the processing method allowed data of high resolution (frequently above 1000 points per m2) and of high accuracy (3D accuracy down to less than 5 cm). The obtained data were processed in the Vector Map Builder environment (which is accessible from the level of an internet browser) and the final product - HD map was created in the Lanelet2 open-source environment. The above-described experiments allowed two main conclusions. Most importantly, they demonstrate the importance of planning and performing in-field mobile laser scanning measurements. They also point to the important role of the human analyst who needs to manually vectorize the key elements of road infrastructure and to define traffic rules.

Implementasi Konsep Akuntansi Syariah Dalam Pembangunan Infrastruktur Pada Ekonomi Biru Di Indonesia

There are 514 urban areas in the archipelagic nation of Indonesia (Ministry of Home Affairs, 2016). There are many cities in Indonesia that are able to provide a sense of comfort and security for their residents, this of course has an impact on population growth. However, the amount of waste that can be generated and stored is limited by the carrying capacity of the urban environment. Using the idea of ​​a "green city" which consists of nine elements of road infrastructure, traffic, green open space, clean water, noise, energy, housing, clean air and buildings is one way to overcome the above problems. All these qualities need to be utilized immediately with a comprehensive systems approach and in accordance with economic, social and environmental principles in sustainable development. Blue economy approaches can be used to eliminate waste. The “blue economy” is a term that is becoming increasingly popular in today's seas and oceans. The aim of this concept is to combine sea base development opportunities with environmental management and protection. Four conceptual interpretations of the blue economy were determined through research into the dominant discourse in international economic policy documents. How the blue economy works is also examined through an “in practice” analysis of the blue economy and related actors. Next, the scope and focus of the blue economy is explored specifically on the maritime industry, which is included or excluded in various conceptualizations. This analysis reveals areas of agreement and conflict. The consensus range reflects the growing trend towards the commercialization and valuation of nature, delineating and defining maritime boundaries and enhancing the security of the world's oceans. There are several areas of conflict, particularly disputes over the legitimacy of individuals as part of the “blue economy”, highly carbon-intensive industries such as oil and gas and the growing deep sea mining industry. Oceans are becoming increasingly important in terms of potential international trade opportunities through intermediaries and buyers. the behavior of the model supporting such a relationship in the ocean is acceptable from a regular and economic point of view. The relationship between land and sea is increasing in the role and importance of the "blue economy" as the term emerges in the background. . A literature review was conducted to analyze the correct definition of the blue economy. This definition is analyzed based on the minimum requirements that are important for the blue economy. This article also tries to compile various types of activities related to marine services. This is done to determine what can be considered priority areas for blue economic growth. The blue economy concept is based on national economic development. This is comprehensively useful for achieving overall national development. Environmental accounting is stated as a process of reducing negative values ​​and creating positive values ​​in environmental accountability.

МОДЕЛИ РАСПОЗНАВАНИЯ ЭЛЕМЕНТОВ ДОРОЖНОЙ ИНФРАСТРУКТУРЫ

The paper considers the problem of recognising road infrastructure elements (temporary signs, guardrail tapes, traffic cones). To solve it, we propose to use the following types of models: Deep Learning model, Random Forest model, Support Vector Machines model, Directional Gradient Histogram model. The principles of operation of the models presented in the article are considered. Recognizing road infrastructure elements in three of the four models studied requires a significant amount of time. The factors influencing the implementation of road works and object recognition are analyzed. The need for road work often depends on weather conditions (rain, snowfall, blizzard, fog, etc.). Recognition of road infrastructure elements includes the following stages: data capture, data preprocessing, model selection, model training, model testing. The article proposes the choice of a recognition model for road infrastructure elements (temporary barriers, temporary signs, traffic cones) based on the YOLO neural network, which has high detection speed and accuracy. The use of the YOLO neural network model allows for timely recognition of objects in images or video streams, which will further reduce the risks of road accidents. Based on the analysis of recognition models for road infrastructure elements, the use of the YOLO neural network model, which does not require significant financial costs, is proposed. The model was trained in the Google Colab development environment in the Python programming language. The neural network model was trained for 100 epochs in 15 minutes. The accuracy of recognition of road infrastructure elements on the training data set was 90%, and on the test set - 79%. In the future, it is planned to expand new data in the form of images of road infrastructure elements and develop a software package for automatically recognizing these elements and reducing the number of road accidents.

Application of artificial intelligence in road network inventory and network-wide road safety assessment

This research paper examines the application of artificial intelligence (AI) in road network inventory and network-wide road safety assessment. An overview of current research related to this field is presented and various aspects of the use of AI in road infrastructure and safety assessment are analysed. In today’s world, where the road network continues to develop and grow, the use of AI can offer significant advantages in the inventory and assessment of road infrastructure and safety. AI can be used to process large volumes of data collected from various sources such as geographic data, photos, documentation and more. One of the main aspects that the article looks at is the use of AI to automatically process data and create a digital inventory of the road network. AI systems can analyse geographic data and photos to identify and classify roads, road signs, markings, and other elements of road infrastructure. This can facilitate engineers and competent authorities in the process of road inventory and maintenance. Another important aspect discussed in the paper is the use of AI for the general assessment of road safety. AI models can analyse road infrastructure inventory data, as well as traffic data, crashes, and other factors, to provide a comprehensive assessment of road network safety. This allows the competent authorities to identify vulnerable places, carry out preventive measures and plan appropriate interventions aimed at improving road safety. In conclusion, the paper highlights the possibilities and advantages of using artificial intelligence in road network inventory and network-wide road safety assessment. Such an approach can contribute to more efficient management of road infrastructure and improvement of road safety.

AUTOMATED DETECTION AND VECTORIZATION OF ROAD ELEMENTS IN HIGH RESOLUTION ORTHOGRAPHIC IMAGES

Abstract. This paper proposes, describes, and applies an algorithm for the automatic detection of selected elements of road infrastructure, along with the option to determine their spatial information. The principle is based on the evaluation of the color spectrum of the selected object on orthographic images. As a source image used for the processing, output from low-altitude aerial photogrammetry or terrestrial laser scanning can be used, together with the option to implement digital elevation models into the processing. The approach is based on the detection of the color composition of the selected element of the road, followed by clustering of the identified elements within the image and mathematical transformation of the clusters into a spatial vector form. Prior to the processing, the target objects are filtered out based on user input, for which vectorization is performed. The outputs are in the form of contours or the determined basic structure of the object. The main difference compared to existing methods is that the vectorization is only performed on the selected, pre-filtered parts of the raster image with identified target objects, not the whole image. This approach makes it possible to effectively and automatically identify and analyze, e.g., the edge of the road, road markings, or road features. This enables the subsequent implementation of the identified outputs into more complex spatial models of the road or its proximity. Additionally, the processing of the data to create a digital model of the environment can be automated, with a significant saving of time and related costs.

Urban mobility efficiency resulting from interdependencies between elements of road infrastructure: the city of Turin example

In this study, an attempt was made to determine the interdependencies between individual parameters of urban logistic networks. As a result of the literature review, a research gap was identified indicating the lack of precise reference to the dependencies between selected road infrastructure elements. The collected information is of key importance for IT systems supporting the management of urban infrastructure in the area of Intelligent Traffic Systems (ITS). The impact of the number of lanes on average travel speeds broken down into rush hours and off-peak hours has been analysed. The conducted research allowed the authors to determine the degree of influence of the number of lanes on the road capacity and the average speed of vehicles. The results of the analyses can be used to power integrated systems for city traffic management and affect the shape of the new road infrastructure design.

Infrastructure requirements for the safe operation of automated vehicles: Opinions from experts and stakeholders

Infrastructure requirements for the safe operation of automated vehicles: Opinions from experts and stakeholders

Analysis of the end-of-life the front suspension beam of a vehicle

The aim of the article is focused on assessing the degree of end-of-life for the vehicle front suspension beam. The first stage of the problem taken was represented by a road test of the vehicle at distance expressed by 100.000 km. Following the end of the operation tests, the suspension beam was dismantled and subjected to laboratory tests. The tests demonstrated numerous beam top layer plastic deformations, which came into being as a result of the vehicle driving onto an obstacle on the roadway or onto raised road infrastructure elements. At the point of connection of the stabiliser rod to the beam, surface degradation was noted, which consisted in the considerable change of the surface profile, hardness reduction and the grey and dark brown colour. Corrosion regions and fretting wear traces were noted. Corrosion pits, scratches and material build-ups was observed. The analysis of the chemical composition of wear products demonstrated the presence of elements such as iron, oxygen, chlorine and silicon, as an effect of operational conditions.

NEGATIVE IMPACTS FROM DISRUPTION OF ROAD INFRASTRUCTURE ELEMENT PERFORMANCE ON DEPENDENT SUBSYSTEMS: METHODOLOGICAL FRAMEWORK

The critical infrastructure system is determined by subsystems essential for the functioning of the state (such as energy, transport, and emergency services). Disruption to the function of these subsystems would have serious effects on state security, the state economy, and the provisioning of the inhabitants’ basic human needs. Links connect these subsystems (i.e., sectors, subsectors, and elements), and these links ensure that certain subsystems are integrated into each other. Their interactions are derived from the type and intensity of the mutual link. The interlinked subsystems can thus be divided into influencing and dependent ones. The aforementioned mutual links in the critical infrastructure system allow, amongst other things, the spread of impacts of disruptive events amongst the subsystems via cascading effects. Disruptions to the performance of an influencing subsystem may have negative effects on a dependent subsystem, resulting in the spread of cascading effects in the critical infrastructure system. Such effects are often difficult to predict, which reduces the responsiveness of the dependent subsystems. Road transport is one of the most significant influences on critical infrastructure subsystems. For this reason, the article focuses on an indication of the negative effects of disruption of road infrastructure elements on dependent subsystems. The article describes the role of road infrastructure in the context of the critical infrastructure system. Defines the dependent subsystems of road infrastructure, categorises the negative effects, and presents a possible approach to assessing the adverse effects of disruption road infrastructure performance on dependent subsystems.

Analysis of the results of the audit of lighting parameters at pedestrian crossings in Warsaw

The night time, based on many world studies, generates an increased risk of serious accidents (with fatalities and serious injuries). This is especially true for accidents with pedestrians. Pedestrian crossings are very sensitive to the influence of the time of day in terms of pedestrian safety, elements of road infrastructure. This is visible on the example of Poland, where numerous accidents at crosswalks are recorded, characterized by high severity at night. Road infra-structure managers take corrective actions to improve this condition. An example of such work is the Road Safety Audit (RSA), initiated in 2016 by the Municipal Roads Management Board in Warsaw. The analyses carried out by the au-thors, among others, in the years 2016 - 2019, included pedestrian crossings without traffic lights located on roads managed by ZDM (Municipal Roads Authority) in twelve districts: Bemowo, Bielany, Mokotów, Ochota, Praga Połud-nie, Praga Północ, Śródmieście, Targówek, Ursynów, Wawer, Włochy, Żoliborz. The assessment was carried out in terms of the correct lighting of these passages, traffic organization, geometry and environmental impact. The main aim of the article is to present a methodology for evaluating the technical condition of road lighting infrastructure on a large scale (e.g. district, city). The article discusses the general and detailed state of pedestrian safety in Poland against the background of research conducted in Warsaw. The procedure of inspection and assessment of the state of lighting of pedestrian crossings is described and selected results are presented. On the basis of a detailed analysis of the results of individual pedestrian crossings, the general condition of the tested crossings was assessed and recommendations were indicated. An attempt was made to assess the influence of pedestrian crossings lighting on the general state of road safety. A critical evaluation of the obtained effects was made. The utilitarian aim of the article is to apply the described methodology in other cities and to use the results of the conducted analyses to plan and implement road investments in the field of modernization of lighting at pedestrian crossings on a large scale.

Development of a database for information support of virtual digital analysis in design and testing of road infrastructure elements

Ensuring traffic safety on the roads and reducing the number of deaths due to road accidents is a priority task both in Russia and in the global community. Assessment of safety in the event of vehicle crashes, oncoming lane exits, collisions with road barriers and other elements of the road infrastructure (ERI) requires the use of a wide range of modern and innovative information technologies-special environments for automated design of Digital Twins of road infrastructure elements, virtual tests with collision modeling and obtaining results on different input parameters of the simulation, modern automated testing of the road infrastructure elements. All these practical works, research and development are carried out at MADI together with scientific team LLC M&PQ to improve road safety. The article deals with the prospects of development of these works, a natural transition to another level of research. Based on the intellectual technologies in the field of road construction, work has begun on creating a special information environment, the so-called “Virtual Digital Proving Ground”, and, among other things, to provide it, a database (DB) of computer-aided design and virtual testing of digital models ERI, which will improve the efficiency and quality of work. The use of the ERI database will allow to implement the automated control of the developed ERI digital models, to implement tools for designing new innovative structures, to predict the behavior of accident participants, to develop reasonable standards in the field of road barriers of the future, to carry out examination by requests of various organizations.

Prospects for the use of composite and polymer materials in transport construction

The article discusses the prospects for the use of road construction elements made of composite and polymer materials. Currently, the main materials used in the production of road infrastructure elements are metal, concrete and plastic. The use of modern polymeric materials will eliminate the disadvantages of the materials used with the same advantages. The study considers the possibility of replacing steel energy-absorbing elements of frontal road barriers with energy-absorbing elements, which are made of a polymer material based on ultra-high molecular weight polyethylene (UHMWPE). The comparison was carried out on the basis of digital modeling of a vehicle collision with a frontal road barrier according to the energy absorption criterion using the LS-Dyna nonlinear dynamics software package. The developed digital models are validated by bench and field tests. Based on the results of the virtual tests, the dimensions of the energy-absorbing elements of the polymer structure of the frontal road fence were selected, which in their properties is not inferior to the used metal analogue. The results obtained prove the prospects of using modern composite and polymer materials in road safety systems.

Feasibility of a Testing Methodology for Visible Light Communication Systems Applied to Intelligent Transport Systems

This paper presents a methodology for testing and evaluation of Visible Light Communication (VLC) applications in the context of Intelligent Transport Systems (ITS). The methodology was applied in a test bed located in Sao Paulo - Brazil, which allows the evaluation of wireless communication technologies between vehicle and road infrastructure elements and between vehicles, even if traveling in high speed. The evaluated application refers to locating buses in real-time in urban places where the Global Positioning System technology is compromised due to loss of signal (sometimes for relatively long periods), such as tunnels and bus terminals. Through VLC, which uses modulated Light-emitting Diodes (LED) as data transmitters, it would be possible to overcome these drawbacks, taking advantage of the existing public lighting infrastructure as a means of transmission of positioning coordinates. The test results showed the feasibility of the proposed application and, most relevant, of the testing methodology. It opens up a range of VLC testing options related to the various ITS domains expressed in ISO 14813, such as vehicle-to-vehicle (e. g. warning signals in platooning scenarios) and vehicle-to-infrastructure-to-vehicle communication (e. g. half or fullduplex communication between vehicles and traffic signals in crossroads).

IDENTIFYING CRITICAL ELEMENTS OF ROAD INFRASTRUCTURE USING CASCADING IMPACT ASSESSMENT

Road transport is a key means of transporting people and cargo on land. Its particular advantages are speed and operability, which are balanced, however, by dependence on road infrastructure. Road infrastructure reliability is an important factor in its functioning. If some elements of road infrastructure are disrupted or fail, the function of dependent infrastructures, such as the integrated rescue system or industry, are also impaired and may fail. These important elements of road infrastructure should be identified as critical and be given greater attention when identifying weaknesses and implementing subsequent security measures. This article introduces the Identifying Critical Elements of Road Infrastructure (ICERI) method, which was designed to make use of Cascading Impact Assessments (CIA). The use of CIA allows critical elements to be identified through impact escalation analysis. These impacts can therefore be monitored not only in road transport infrastructure but also across the entire critical infrastructure system.

Neural network application for detection of road accidents

Subject of Research. The paper considers the issues of neural network application for detection and prediction of road accidents. The overtaking process of cars with crossing into oncoming traffic is analyzed. The potential possibility of road accident reduction while overtaking is shown owing to intellectual assessment of road situation dynamics development. Method. We proposed to use a two-class classifier based on a neural network. Road situations while overtaking with crossing into oncoming traffic were the objects of classification. The data on them was transmitted to the neural network input in the form of the frame set, that is, a graphical representation of discrete states of the “group of vehicles — section of the road” system. Frame formation was expected to be carried out as a result of information exchange between detectors and vehicle-mounted sensors, and road infrastructure, which is developed within the framework of the “smart city” paradigm. Main Results. The road situation is classified as “Dangerous” in case of high vehicle collision probability while overtaking and “Safe”, otherwise. If the situation is considered as “Dangerous”, the vehicle central processor generates an appropriate effect on the vehicle control elements to prevent an accident. Results of situation simulation implemented on Tensor Flow open software library for machine learning are obtained. They showed high prediction accuracy (0.96) on artificial data set. Practical Relevance. The results of the work can be used in promising unmanned and manned vehicles having radio communication with road infrastructure elements within the “smart city” concept to prevent road accidents caused by dangerous overtaking.

Usage of Microscopic Simulation to Estimate the Environmental Impact of Road Transport

Abstract The purpose of the transport system is providing access to goods, jobs and services. However, the increase in the level of transport services provision is accompanied by negative consequences. Within the concept of sustainable development of urban transport systems, it is necessary to ensure a safe environmental load for people. Therefore, the purpose of this study is the search and testing of methods to correctly estimate the degree of environmental impact by road transport, reducing the environmental burden, and substantiating the rationality of the implementation of the proposed measures for greening transport. As research methods were used: the theory of traffic flows, simulation, computer experiment, methods of direct measurement of environmental emissions on the road segment under study. The use of simulation allows to find an acceptable solution for the volume of exhaust gases and noise pollution, by varying the parameters of the transport system objects (the configuration of the road network, the characteristics and modes of operation of the road infrastructure elements). It is shown that micromodelling is an effective approach, in which the unit of modeling is a separate vehicle. It makes possible to take into account the individual characteristics of the vehicle (current mileage, engine type, environmental safety class), which allows an estimation of the environmental impact of the vehicle fleet operating in the area. Examples of using this approach are given, computer experiments on specific sections of the road network are conducted (in particular at intersections of multi-lane roads with traffic lights, as well as locations of road service facilities, such as gas stations, car parks, etc., which increase the negative environmental impact on the adjacent territory).