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International audience; Utility-rich (e.g., more attractive or safer) route planning on city-scale road networks is a common yet time-consuming task. Although both travel time and utility on edges are time-dependent concurrently in real cases, they are overlooked in most prior work. In this paper, we focus on the route planning over two-fold time-dependent road networks, i.e., both travel time and utility on edges are varying over time. We aim to find a route from an origin to a destination by maximizing the accumulated utility score within a time budget. Moreover, to satisfy users' real-time requests, the fast response is usually mandatory. Here, we propose a novel two-phase framework called , i.e., anaging ffline data for nline route lanning, to discover the near-optimal driving routes efficiently. Specifically, in the offline phase, we construct the auxiliary data structure, i.e., the edge table, to manage the time-dependent information about edges. In the following online phase, the route is generated sequentially by an iterative edge table visiting process. We evaluate the proposed thoroughly based on synthetic road networks and two real-world road networks in the city of Chengdu (4,819 nodes and 6,385 edges) and the city of Chongqing (5,056 nodes and 7,355 edges) in China. Results show that: (i) our framework can work adaptively for different time-varying utility patterns; (ii) the edge table is economic yet effective; (iii) our route planning algorithm outperforms other baselines in obtaining the highest utility value while costing the least running time.

Сьогодні існує відмінність європейського та вітчизняного підходів до функціонування та організації вулично-дорожньої мережі, міської мобільності, а також ефективного використання простору урбанізованих територій. Основними факторами були: історичний розвиток, науково-технологічний прогрес, адміністративна складова, у формуванні фінансових потоків для розвитку міських систем, рельєф місцевості, процес урбанізації територій та утворення міських агломерацій. Ці фактори прямо вплинули на формування сучасного стану вулично-дорожньої мережі. Процес інтеграції інтелектуальних транспортних систем у систему українських міст потребує комплексних підходів, зокрема врахування параметричної структури елементів, застосування комунікаторів не тільки для контролю транспортних потоків ззовні, а й всередині, що дозволить пришвидшити обмін інформацією в системі. Одним із елементів поєднання морфологічних елементів міського середовища є практичне застосування критерію оцінки взаємодії вуличної та дорожньої інфраструктури та поняття профіль безпека руху. Це результат поєднання усіх морфологічних ознак між собою та варіанти їх конфігурації. У сучасних умовах для визначення критеріїв і факторів стійкого розвитку транспортних систем потрібний новий підхід у дослідженнях, що дає змогу оперативно враховувати зміни зовнішнього середовища, адекватно реагувати на поведінку конкурентів надання послуг і споживачів, яка змінюється, та ефективно впливати на попит і пропозицію транспортних послуг. Поняття ефективності необхідно розглядати щодо транспортної системи загалом, так і до окремих її елементів. Впровадження прогресивних методів системного управління транспортними потоками забезпечує в умовах швидкої автомобілізації та збільшення площ урбанізованих територій отримання найбільшого ефекту в стислі терміни і дає змогу максимально використовувати можливості міських дорожніх мереж. Nowadays, there is a difference between European and domestic approaches to the functioning and organization of road networks, urban mobility, and effective use of the space of urbanized territories. The main factors were historical development, scientific-technical progress, an administrative component in the formation of financial flows to developing urban systems, terrain, the process of territories` urbanization, and the formation of urban agglomerations. These factors had a direct impact on the shape of the modern state of the road network. The process of Intelligent transport systems integration into the system of domestic cities requires complex approaches, in particular, consideration of the parametric structure of elements, application of communicators not only for the control of traffic flows from the outside but also from the inside, which will allow speeding up the information change in the system. One of the elements of the combination of morphologic elements of the urban environment is the practical application of the criterion of street and road infrastructure interaction and the concept of traffic safety profile. This is a result of a combination of all morphological features and variants of their configuration. In current conditions, a new approach in research is necessary to determine criteria and factors of sustainable development of transport systems. This approach allows operatively considering the changes of the external environment, reacting adequately to the changing behaviour of competitors providing services and consumers, and effectively impacting the demand and supply of transport services. A concept of effectiveness is required to consider both the transport system in general and its separate elements. Implementation of progressive methods of system control of transport flows provides, in conditions of rapid motorization and increasing the urbanized territories areas, obtaining the most significant effect in short terms and allows maximal using the possibilities of urban transport networks.

Urban streets are an integral part of the public realm. Streets are commonly planned following normative design principles focused on the connectivity of road networks and urban morphology. Beyond their function as mobility infrastructure, streetscapes’ aesthetic, social, and cultural qualities also have an important impact on the experience of the overall urban environment and human well-being. This study explores how urban design and planning can facilitate the design, management, and use of streetscapes that consider their role as social infrastructure. A paradigmatic case study of Hornsbergs Strand in the City of Stockholm is performed, incorporating spatial and temporal aspects. The case study area is chosen because it is both an attractive and “overcrowded” public space frequently discussed in the Swedish media. Data sources for the study include reviews of public documents such as Stockholm’s city planning strategies, local media reports, a report from a resident workgroup, as well as walk-through observations and semi-structured expert interviews. The results highlight the potential of urban design strategies to develop streetscapes as social infrastructure through both permanent design measures and temporary design interventions. The tendency of the change in people’s perception and attitude toward the place over time illustrates that design interventions are a continual process. The implications for public policy, urban development and investment in social infrastructure employing place strategies and design interventions are discussed.

Due to the wide variety of urban passenger transport; the terms, types and capacity of buses are the main parameters that will be denoted in this study, the question here arises as to whether this diversity affects the throughput of bus stop point capacity. The studies of the traffic intensity of urban passenger transport, at fifteen stopping points, made it possible to give an idea of: The number of fixed-path minibus changes over time and not obeying the movement regularity with other types of urban passenger transport. Where that indicates the influence of an economic factor associated only to make a profit. The intensity of urban passenger transport through the bus stopping point shows the dominance of route minibus on it, and it that consider the main cause of congestion at the stop points; the movement of various types of urban passenger transport through the stopping point is carried out in a random order, it also causes congestion, too. Purpose. Analysis of factors affecting the capacity of a bus stop point for urban passenger transport. Methodology in the article, economic-mathematical methods, and also statistical methods of the analysis were used. Results. The most important parameters showing some aspects of carrying out the analysis of public transport movement operations at stop points are received. Practical implications. The results obtained should be considered while planning and manage the movement of urban passenger transport.

Internet of things (IoT), which is considerably innovating and generating a large volume of processes in every field worldwide, is one of the recent and next disruptive technologies. As a result, IoT devices and others are increasing network connections in the relevant field. It is essential to maximize and process these kinds of resources. The effective usage of resources is one of the most important and very difficult to manage the resource in the dynamic environments. Many studies are performed in the effective usage of resource in the static and dynamic environments. However, the dynamic environments have still different issues and have to solve different dynamic networking issues. In this work, present a mechanism for managing different connecting devices in the dynamic environments. Especially this system is concentrating on road network device management in dynamic environments. The proposed system called dynamic road sensing (DyRSen) connectivity is support to different continuous connectivity. The DyRSen provides: i) continuous connectivity using available resources and provide virtual environment for computing, ii) temporary data storage in dynamic environment for effective resource sharing, and iii) reduce the energy utilization and network overhead and the effective resource management is compared to the other works.

Geographic information technologies and data are widely used to identify a variety of spatial relationships. The paper is devoted to the study of the mutual location between the road network (as exemplified by the public roads network) and cellular coverage of the Russian telecom operators on the territory of Russia. Transport researches are characterized with an emphasis of GIS projects. Then, an overview of modern web services, Open Data and Open Source developments in transport projects is made. The data, geodata services and web projects of cellular coverage for the territory of Russia are described by the examples of Russian-language sources. The practical part of the study shows the global transport accessibility raster datasets for the test region of Russia (Irkutsk Region, Siberian Federal District). An analysis of spatial relationships between roads and cellular coverages provided by VimpelCom/ Beeline, Megafon and MTS is based on the Open Data in the Open Source GIS application QGIS. Coverage varies between 63% (VimpelCom for the buffer zone of 2.5 km) and 94% (Megafon for the zone of 10 km), where 100% is the total number of cells (polygons) within the network of a respective operator in the region. We have noted that Open Data on the public road network and cellular communication for the territory of Russia differ by region, the studied communication datasets and data services do not contain significant attributive information, they consist of polygon geometry only. Frequency of their updates depends on the operating companies. The operators then provide the data for the publication to the Russian ministries and regional administrations.

The object of research is the processes of road network management. The main hypothesis of the study is the application of optimization methods to the road asset management program, which allows to implement a road maintenance strategy, which includes a set of measures involved in ensuring and maintaining roads at the appropriate operational level. In general, the sequence of asset management begins with the definition of objectives, policy of road administrations and the available budget. According to this starting point, data collection, performance monitoring, analysis of options and optimization programs, selection and implementation of a set of projects are performed. The goals and objectives of road project management depending on the category are considered. The model of strategic planning of the program on management of a network of highways is offered and the modern architecture of model is constructed. The main approaches to the optimization of the road asset management program are identified. The target function for the optimization model is proposed, which is to minimize the cost of maintenance of the road network and defines the goals to be achieved in the optimization process. The optimization model is a mathematical description designed to compare alternative strategies and identify the relative benefits of each strategy according to the assigned decision criteria, such as safety, cost, environment and others. The main idea and goal of road network management projects is to improve maintenance practices and policies and thus improve the condition of the network, or maintain it at the current level, taking into account resource constraints. The results of program optimization have practical value and can be used to manage road repair and operation projects depending on: –defined project goals and plans, including scheduling, budgeting, planning, established efficiency requirements and selection of project participants; –maximizing the efficient use of resources; –implementation of functions of coordination and control, planning, design, evaluation, conclusion of contracts and implementation of projects under contracts.

Transportation is a driving force behind economic development and well-being of all people around the world. An urban transport system is one of the most critical infrastructures for urban development. Impacts of a poor urban transport are manifested in terms of congestion, delays, pollution, accidents, high-energy consumption, low productivity of resources, community severances and inadequate access to the service. In urban areas, despite the construction of flyovers and roads, the roads continue to face traffic congestion, environmental pollution and lack of mass transportation facility resulting in heavy shift of commuters to intermediate and private vehicle ownership. Therefore, it is necessary to make transport system attractive and user friendly in terms of safety, reliability, travel time and comfort, which can be achieved using intelligent transportation system (ITS). This study has been intended to develop a methodology for development and operation of intelligent transportation system namely Presto ITS mobile application. The Android application, Presto ITS, developed works along with the Urban Traffic Data Management Centre to help reduce the congestion on the road networks by allowing the users to make informed decisions about route choices. This helps in reducing further inflow of vehicles in an already congested road network and thus allowing distribution of vehicles among the different routes resulting in lesser overall congestion. This system when installed on an overall city wide basis will drastically help in reducing the congestion and evenly distributed traffic.

This study proposes and implements an intelligent transportation system (ITS)-based system that collects road event information via a vehicle’s on-board unit (OBU) and roadside unit (RSU), integrates and processes information based on the database and the road network, and provides information to vehicles. This system enables the collection of road unit information without calculating the exact location of event information recognized by the vehicle and facilitates duplicate processing of information recognized from multiple sources. This information can then be provided to other vehicles or road operators via apps or the web, enabling immediate response to emergency situations or changes in road conditions. To verify the practical applicability of this system, we developed a prototype and validated its functions through experiments. Using this system and methods, general drivers, autonomous vehicles, and infrastructure can cooperate in an ITS environment to recognize and propagate various road situations, contributing to the creation of safer and more efficient roads.

The structural characteristics of an urban road network directly affect the urban road network’s overall function and service level. Because the hierarchical division and layout form of an urban road network has self-similarity and scale invariance, the urban traffic network has certain time-space fractal characteristics, and fractal theory has become a powerful tool for evaluating traffic networks. This paper calculates and compares five fractal dimensions (FD) of nine districts in Harbin. Meanwhile, each calculated FD is linearly regressed with the area, population, built-up area, building area, the total number and length of roads, and the number of buildings in the region. The results show that the fractal dimensions of the five types are between 1 and 2. In the same district, the values of the FD perimeter and FD ruler are lower compared to the FD box, FD information, and FD mass, whereas those of the FD box and FD information are higher. Compared to the FD box and FD information, the value of FD mass shows unevenly. Based on the current research results, this study discusses the feasibility of using relevant indicators in the fractal process to evaluate the layout of the urban road network and guide its optimization and adjustment.

Linear feature networks are the roads, trails, pipelines, and seismic lines developed throughout many commercial boreal forests. These linear features, while providing access for industrial, recreational, silvicultural, and fire management operations, also have environmental implications which involve both the active and non-active portions of the network. Management of the existing linear feature networks across boreal forests would lead to the optimization of maintenance and construction costs as well as the minimization of the cumulative environmental effects of the anthropogenic linear footprint. Remote sensing data and predictive modelling are valuable support tools for the multi-level management of this network by providing accurate and detailed quantitative information aiming to assess linear feature conditions (e.g., deterioration and vegetation characteristic dynamics). However, the potential of remote sensing datasets to improve knowledge of fine-scale vegetation characteristic dynamics within forest roads has not been fully explored. This study investigated the use of high-spatial resolution (1 m), airborne LiDAR, terrain, climatic, and field survey data, aiming to provide information on vegetation characteristic dynamics within forest roads by (i) developing a predictive model for the characterization of the LiDAR-CHM vegetation cover dynamic (response metric) and (ii) investigating causal factors driving the vegetation cover dynamic using LiDAR (topography: slope, TWI, hillshade, and orientation), Sentinel-2 optical imagery (NDVI), climate databases (sunlight and wind speed), and field inventory (clearing width and years post-clearing). For these purposes, we evaluated and compared the performance of ordinary least squares (OLS) and machine learning (ML) regression approaches commonly used in ecological modelling—multiple linear regression (mlr), multivariate adaptive regression splines (mars), generalized additive model (gam), k-nearest neighbors (knn), gradient boosting machines (gbm), and random forests (rf). We validated our models’ results using an error metric—root mean square error (RMSE)—and a goodness-of-fit metric—coefficient of determination (R2). The predictions were tested using stratified cross-validation and were validated against an independent dataset. Our findings revealed that the rf model showed the most accurate results (cross-validation: R2 = 0.69, RMSE = 18.69%, validation against an independent dataset: R2 = 0.62, RMSE = 20.29%). The most informative factors were clearing width, which had the strongest negative effect, suggesting the underlying influence of disturbance legacies, and years post-clearing, which had a positive effect on the vegetation cover dynamic. Our long-term predictions suggest that a timeframe of no less than 20 years is expected for both wide- and narrow-width roads to exhibit ~50% and ~80% vegetation cover, respectively. This study has improved our understanding of fine-scale vegetation dynamics around forest roads, both qualitatively and quantitatively. The information from the predictive model is useful for both the short- and long-term management of the existing network. Furthermore, the study demonstrates that spatially explicit models using LiDAR data are reliable tools for assessing vegetation dynamics around forest roads. It provides avenues for further research and the potential to integrate this quantitative approach with other linear feature studies. An improved knowledge of vegetation dynamic patterns on linear features can help support sustainable forest management.

A sustainable transportation system is possible only through an efficient evaluation of transportation network performance. The efficiency of the transport network structure is analyzed in terms of its connectivity, accessibility, network development, and spatial pattern. This study primarily aims to propose a methodology for modeling the accessibility based on the structural parameters of the urban road network. Accessibility depends on the arrangement of the urban road network structure. The influence of the structural parameters on the accessibility is modeled using Multiple Linear Regression (MLR) analysis. The study attempts to introduce two methods of Artificial Intelligence (AI) namely Artificial Neural Networks (ANN) and Adaptive network-based neuro-fuzzy inference system (ANFIS) in modeling the urban road network accessibility. The study also focuses on comparing the results obtained from MLR, ANN and ANFIS modeling techniques in predicting the accessibility. The results of the study present that the structural parameters of the road network have a considerable impact on accessibility. ANFIS method has shown the best performance in modeling the road network accessibility with a MAPE value of 0.287%. The present study adopted Geographical Information Systems (GIS) to quantify, extract and analyze different features of the urban transportation network structure. The combination of GIS, ANN, and ANFIS help in improved decision-making. The results of the study may be used by transportation planning authorities to implement better planning practices in order to improve accessibility.

When forming industrial and economic relations, there is a need for purposeful planning and development of urban agglomerations. The most urgent problem of spatial development of regions is due to the existing differences in the standard of living, conditions, as well as the scheme of the street and road network, namely, peripheral points. An important role in ensuring a high level of development of all the territories of the region is played by "group" forms of highly concentrated settlement, such as urban agglomerations. The development of urban agglomeration makes it possible to distribute industrial production, as well as rationally arrange them in relation to residential development, which will further improve economic and environmental indicators in large cities. In addition, an urban agglomeration that has significantly more opportunities for development is an environment that has properties favorable for inertial processes [6]. The article discusses the features of the formation of the urban agglomeration of the city of Belgorod. The territorial and functional structure of the urban agglomeration is presented. Priorities for the development of the urban agglomeration are outlined. The influence of the agglomeration effect on the economic growth of the region is revealed.

The article is devoted to the problem of the impact of street parking on delays and the average speed of traffic flow. The sections with different ways of putting vehicles near the roadway in the central part of Lviv city with the most saturated flow were exposed to scientific scrutiny. For this purpose, the program software PTV Vissim is used. The causes of the impact of street parking on traffic flow speed and roadway capacity are analyzed. Simulation model was created, with the use of which the operation of the street section where parking is allowed and without parking, and also the impact of the parking duration on the average speed of traffic flow and its delays were investigated. It is clarified that the least values the average traffic delay has with the parking duration of 900 and 1800 sec, and the biggest values it has with the duration of 300 sec. It is determined that during the street parking design parallel to the sidewalk it is necessary to implement the restriction of the parking duration to increase the road network capacity and traffic flow speed.

The article is devoted to the methodology and research results of traffic flow parameters on the arterial streets, where different regimes of prioritizing urban public transport operate. The regularities of changes of such parameters make it possible to identify and differentiate the sections of transport network in terms of service efficiency, with the aim to implement various regulatory measures that would help to minimize delays in traffic flow. Quantitative and qualitative criteria for ensuring priority transit of urban public transport on different sections of transport network depending on the intensity, speed and composition of traffic, as well as the roadway parameters are defined and substantiated. According to the research outcomes, scientifically based approaches are recommended for the implementation of different schemes of traffic flows control on the sections of the transport network, which differ in planning parameters and of traffic conditions and provide rational transport service based on the criterion of time loss for movement of residents. These results are adequate for large and very large cities with dense construction area

The article deals with the modified Dijkstra’s algorithm of searching the shortest routes between all transport nodes of the road-transport network, which allows presenting the transport problem in the classical matrix form. This makes it possible to apply each of the known methods of optimal transport plans to solve it. The object of study is the transport process of freight transportation on the transport network by routes of international transport corridors. The purpose of the work is to improve the methods of solving the problems of finding the shortest routes on the transport network, including sections of international transport corridors. The research method is the analysis and modeling of freight transportation on road networks. The modified Dijkstra’s method of finding the shortest paths between all nodes of the road-transport network was work out, which allows to represent the transport problem in the classical matrix form, i.e. in the form of a table of connections. This makes it possible to apply each of the known methods of constructing optimal plans of cargo transportation in the table of connections. The software complex based on the developed algorithm was designed in the algorithmic language Delphi, which was tested on the example of a transport problem set in the form of a road network, as well as complex testing and debugging of a computer system to support decision-making on the optimization of freight traffic on Ukrainian and Western Europe transport systems.

Road network control is challenging but critical in enhancing urban traffic. This paper proposes a management method for a road network with non-signalized intersections in the connected-vehicle environment, which coordinates connected and automated vehicles' movements to make the non-signalized intersections conflict-free and efficient. Firstly, the proposed method projects vehicles in road networks into virtual platoons and builds the road-network-wide conflict-free geometric topology considering the vehicles' conflicting relationships, which describes the geometry car-following relationship in virtual platoons. Then, a distributed linear controller is designed considering vehicle dynamics and communication topology to organize vehicles' movements with the desired geometric topology. Finally, simulations are conducted to verify the proposed method with different traffic demands. Simulation results show the proposed method can significantly improve traffic efficiency, as well as traffic safety.

Colocation mining is useful for understanding the interactions or dependencies that occur among geographic phenomena. Most colocation mining methods are based on planar space. However, in urban spaces, many human-related activities are constrained by a road network. Planar colocation mining methods are not suitable for studying the concerning geographic phenomena in an urban space. In this paper, we propose a visualization method to discover colocation patterns constrained by a road network. The method consists of two major components: network kernel density estimation and network colocation rule map construction. In the colocation rule map construction component, spatial interactions among spatial network geographic phenomena are modeled based on the idea of color mixing. We use simulated datasets with different spatial patterns, different sample sizes, and different maximum distances between road network events to test our method. The results show that our method is effective for mining colocation patterns in different situations. We also change the resolution of the network colocation rule maps, and the results show that the resolution has little influence on the results. In the case study, we apply our method to explore the spatial association between crimes and city facilities in the Loop and the Near North Side districts of Chicago.

How to effectively utilize caching technology to support high-performance shortest path queries on road networks has become an important research problem since the popularization of location-based services. Most of the existing methods design a statistical model to construct the cache with the shortest paths, and mainly consider the related query frequency obtained from the historical query logs. As a result, the paths in the cache may be concentrated in a few hot-spot areas of the road network, such as the prosperous areas of a city. Additionally, queries from remote areas may never be hit in the cache, which results in the cache hit ratio is not fully optimized. To address this problem, we define an effective model to quantify the effect of cached shortest paths; the model not only considers the related query frequency in the log but also the coverage of the paths on the road network. Then, we propose an efficient cache construction method to select the cached shortest paths from the query log. Furthermore, we design a hybrid index for the shortest paths in the cache, so that the efficiency of shortest path querying is significantly improved. Finally, we conduct comprehensive experimental studies on different datasets to verify that the cache hit ratio is greatly improved by using the proposed cache construction approaches.

Ushbu maqolada shahar transport turlari bo���yicha mikroavtobuslarning harakatlanish xususiyatlari keltirilgan. Shahar yo���lovchi transporti harakatlanishiga salbiy ta���sir ko���rsatayotgan muammolarni hal qilish maqsadida Jizzax shahrining markaziy ko���chalarida transport vositalarining imtiyozli harakatlanishini tahlil qilindi., This article describes the properties of the movement of urban minibuses on routes. In order to solve problems that negatively affect the movement of urban passenger traffic, an analysis was made of the priority movement of public transport on the central streets of Jizzakh.

Ushbu maqolada kuzatish usuli orqali Jizzax shahrining magistral ko���chalarida avtomobillar va jamoat transporti aralash harakatlanadigan, hamda shaharning hozirgi kunda asosiy magistral ko���chalarida olib borilgan tadqiqot natijalari shuni ko���rsatdiki, ushbu ko���chalarda harakat miqdori yo���lning ahamiyatiga, transport vositalarining tarkibiga, holatiga va shunga o���xshash bir qancha omillarga bog���liq bo���lib, birbiridan farq qilishini ko���rish mumkin. Harakat miqdori va tarkibining o���zgarishi xarakat tezligi va yo���l -transport xodisalarining o���zgarishiga ta���sir qilishi tahlil qilindi., In this article, the results of a study conducted on the main streets of Jizzakh, which are a mixture of cars and public transport on the main streets of Jizzakh, show that the intensity of traffic on these streets depends on the importance of the road, traffic .. it can be seen that they differ from each other depending on a number of factors such as composition, condition, and so on. The influence of changes in the volume and composition of traffic on changes in the speed of movement and the number of traffic accidents is analyzed.

Road networks are vulnerable to natural disasters such as floods, earthquakes and forest fires which can adversely affect the travel on the network. However, not all road links equally affect the travel conditions in a given network; typically some links are more critical to the network functioning than the others. The first stage of study involves the investigation of geological conditions. Image classification used for extracting information classes from ‘Geological Map of Istanbul area’ image file. The resulting raster layer used to create thematic map. A reclassification was performed for lithologic types. The second stage involves analyzing topological situation. A slope map prepared and classified according to percentage of slope values. The third phase is the analysis and interpretation of the accumulated data to establish suitable and applicable road vulnerability scores. The information in the source data for each vulnerability factor are classified into three different vulnerability scores: +2 (considerably increases vulnerability), +1 (increases vulnerability) and 0 (does not increase vulnerability) by using a vulnerability score table. The study area was categorized into three different traffic analysis zones as: (1) least favorable area; (2) favorable area; (3) most favorable area. Vulnerability values obtained to measure serviceability of critical links in dense urban road networks and applies them to the case of ‘Beyoğlu’ region. Thematic layers were prepared using the Geographic Information System (GIS), and they were then combined to produce the serviceability of road links in the ‘Beyoğlu’ region. Consequently, A site specific vulnerability index is proposed, considering the serviceability of road links. A conceptual flowchart of the GIS processing steps taken to obtain the vulnerability index is illustrated.

The large-scale provision of defenses around small towns in Roman Britain during the 2nd c. CE is without parallel in the Roman Empire. Although the relationship between defended small towns and the Roman road network has been noted previously, provincial-level patterns remain to be explored. Using network analysis and spatial inference methods, this paper shows that defended small towns in the 2nd c. are on average better integrated within the road network – and located on road segments important for controlling the flow of information – than small towns at random. This research suggests that the fortification of small towns in the 2nd c. was structured by the connectivity of the Roman road network and associated with the functioning of the cursus publicus.

Ushbu maqolada avtomobillar harakat sharoitining turli xil bo��lishi, aynan bir xil sharoitdagi hududlarni aniqlash va ularni tumanlarga ajratish zaruratini borligi, harakat sharoiti bo��yicha tumanlashtirish va buning asosiy maqsadi avtomobillarning qulay va xavsiz harakat xavfsizligi sharoiti ta��minlanmagan hududlarni aniqlash hamda bu hudud yo��llaridan samarali foydalanish bo��yicha tavsiyalar keltirilgan, This article discusses different types of traffic conditions, the need to identify areas with the same conditions and divide them into areas, zoning according to traffic conditions, the main purpose of this is to identify areas where safe and comfortable traffic is not ensured, as well as recommendations for the effective use roads in these areas.

Ushbu maqolada kuzatish usuli orqali Jizzax shahrining magistral ko���chalarida avtomobillar va jamoat transporti aralash harakatlanadigan, hamda shaharning hozirgi kunda asosiy magistral ko���chalarida olib borilgan tadqiqot natijalari shuni ko���rsatdiki, ushbu ko���chalarda harakat miqdori yo���lning ahamiyatiga, transport vositalarining tarkibiga, holatiga va shunga o���xshash bir qancha omillarga bog���liq bo���lib, birbiridan farq qilishini ko���rish mumkin. Harakat miqdori va tarkibining o���zgarishi xarakat tezligi va yo���l -transport xodisalarining o���zgarishiga ta���sir qilishi tahlil qilindi., In this article, the results of a study conducted by the method of observation on the main main streets of the city of Jizzakh, where there is mixed traffic of cars and public transport, show that the intensity of traffic on these streets varies depending on the importance of the road, the composition and condition of vehicles and a number of other factors . The results of the analyzes show that changes in the number and composition of the traffic flow affect the speed of movement and changes in the number of traffic accidents.

The widespread use of mobile devices has resulted in the generation of vast amounts of spatial data. The availability of such large-scale spatial data facilitates the development of data-driven approaches to address real-life problems. This paper introduces the max coverage region (MCR) problem in road networks and provides efficient solutions. Given a set of spatial objects and a coverage radius, the MCR problem aims to identify a location from the road network, so that we can reach as many spatial objects as possible within the given coverage radius from the location. This problem is fundamental to supporting many real-world applications. Given a road network and a set of sensors, this problem can be used to find the best location for a sensor maintenance station. This problem can also be applied in medical research, such as in a protein–protein interaction network, where the nodes represent proteins, the edges represent their interactions, and the weight of an edge represents confidence. We can use the MCR problem to find the set of interacting proteins with a confidence budget. We propose an efficient exact solution to solve the problem, where we reduce the MCR problem to an equivalent problem named the most overlapped interval and design an edge-level upper bound estimation method to reduce the search space. Furthermore, we propose two approximate solutions that sacrifice a little accuracy for much better efficiency. Our experimental study on real-road network datasets demonstrates the effectiveness and superiority of the proposed approaches.

An intelligent, accurate, and powerful object detection system is required for automated driving systems to keep these vehicles aware of their surrounding objects. Thus, vehicles adapt their speed and operations to avoid crashing with the existing objects and follow the driving rules around the existence of emergency vehicles and installed traffic signs. The objects considered in this work are summarized by regular vehicles, big trucks, emergency vehicles, pedestrians, bicycles, traffic lights, and traffic signs on the roadside. Autonomous vehicles are equipped with high-quality sensors and cameras, LiDAR, radars, and GPS tracking systems that help to detect existing objects, identify them, and determine their exact locations. However, these tools are costly and require regular maintenance. This work aims to develop an intelligent object classification mechanism for autonomous vehicles. The proposed mechanism uses machine learning technology to predict the existence of investigated objects over the road network early. We use different datasets to evaluate the performance of the proposed mechanism. Accuracy, Precision, F1-Score, G-Mean, and Recall are the measures considered in the experiments. Moreover, the proposed object classification mechanism is compared to other selected previous techniques in this field. The results show that grouping the dataset based on their mobility nature before applying the classification task improved the results for most of the algorithms, especially for vehicle detection.

Over the past decades, China has built a large number of superblocks and gated residential areas, which have contributed to increased congestion on urban road traffic. Although some studies have found a correlation between residential environments and travel convenience, there is little quantitative evidence to explain which factors influence the connectivity of road networks. This paper aims to clarify the indicators of built environments in Chinese residential areas that affect travel accessibility and their correlation proportions through a more quantitative method and to provide a basis for planning and design decisions. To this end, this study took 204 residential areas in the three districts of Nanjing, China as a sample and calculated 16 built-environment indicators. The path distance (D) and pedestrian route directness (PRD) from the center of these residential areas to the nearest urban intersection were measured by GIS as outcome variables. First, correlation analysis was used to screen for significant variables, and multiple linear regression models were used to examine the significant influencing factors of D and PRD. Then, a binary logistic regression analysis was performed to provide a model that could determine whether the built environment of the residential area met the requirements for convenient travel. The results revealed that the length of the long side, the area size, and the total road length of the residential area were significantly related to D, and the number of entrances and exits, the intersection density, and the X ratio were significantly related to PRD. The indicators that were positively correlated with D were the size, network complexity, and the boundary shape of the residential area according to the degree of correlation. Meanwhile, other indicators such as the density and connectivity of the residential road network were negatively correlated with D.

Nobody in this world wants to be held hostage in a traffic jam for hours and hours. The need to have efficient traffic flow in our roads cannot be overemphasized. It is in this understanding that this paper delves into the study and implementation of a suitable algorithm for traffic routing. The implementation is based on graph theory, where a road network map is first converted to a graph with nodes and edges where the edges represent the roads and the nodes represent the various road intersections. The roads are given various weights depending on their distance and traffic density, and the time a motorist would take to move from one point to another is estimated. A suitable routing algorithm, which in this case is the Dijkstra’s algorithm is applied on the weighted graph.

Urban planners have been long interested in understanding how urban structure and activities are mutually influenced. Human mobility and economic activities naturally drive the formation of road network structure and the accessibility of the latter shapes the patterns of movement flow across urban space. In this paper, we perform an exploratory study on the relationship between the street network structure and the intensity of human movement in urban areas. We focus on two cities and we utilize a dataset of geo-tagged tweets that can form a proxy to urban mobility and the corresponding street networks as obtained from OpenStreetMap. We apply three network centrality measures, including closeness, betweenness and straightness centrality, calculated at a global or local scale, as well as under mixed or individual transportation mode (e.g., driving, biking and walking) with its directional accessibility, to uncover the structural properties of urban street networks. We further design an urban area transition network and apply PageRank to capture the intensity of human mobility. Our correlation analysis indicates different centrality metrics have different levels of correlation with the intensity of human movement. The closeness centrality consistently shows the highest correlation (with a coefficient around 0.6) with human movement intensity when calculated at a global scale, while straightness centrality often shows no correlation at the global scale or weaker correlation ρ≈0.4 at the local scale. The correlation levels further depend on the type of directional accessibility and of various types of transportation modes. Hence, the directionality and transportation mode, largely ignored in the analysis of road networks, are crucial. Furthermore, the strength of the correlation varies in the two cities examined, indicating potential differences in urban spatial structure and human mobility patterns.

Electric vehicles (EVs) have attracted considerable attention because of their clean and high-energy efficiency. Reasonably planning a charging station network has become a vital issue for the popularization of EVs. Current research on optimizing charging station networks focuses on the role of stations in a local scope. However, spatial features between charging stations are not considered. This paper proposes a charging station selection method based on the graph convolutional network (GCN) and establishes a charging station selection method considering traffic information and investment cost. The method uses the GCN to extract charging stations. The charging demand of each candidate station is calculated through the traffic flow information to optimize the location of charging stations. Finally, the cost of the charging station network is evaluated. A case study on charging station selection shows that the method can solve the EV charging station location problem.

Investigating the correlation between urban mobility patterns and the built environment is crucial to support an integrated approach to transportation and land-use planning in modern cities. In this study, we aim to conduct a data-driven analysis of these two interrelated parts of the urban environment through the estimation of a set of metrics to assist city planners in making well-informed strategic decisions. Metrics are computed by aggregating and correlating different types of data sources. Floating Car Data (FCD) are used to compute metrics on mobility demand and traffic patterns. The built environment metrics are mainly derived from population and housing census data, as well as by investigating the topology and the functional classification adopted in the OpenStreetMap Repository to describe the importance and the role of each street in the overall network. Thanks to this set of metrics, accessibility indexes are then estimated to capture and explain the interaction between traffic patterns and the built environment in three Italian cities: Brescia, Catania, and Salerno. The results confirm that the proposed data-driven approach can extract valuable information to support decisions leading to more sustainable urban mobility volumes and patterns. More specifically, the application results show how the physical shape of each city and the related street network characteristics affect the accessibility profiles of different city zones and, consequently, the associated traffic patterns and travel delays. In particular, the combined analysis of city layouts, street network distributions, and floating car profiles suggests that cities such as Brescia, which is characterized by a homogeneously distributed radial street system, exhibit a more balanced spread of activities and efficient mobility behaviors.

El siguiente trabajo contiene el proceso y las actividades desarrolladas en la práctica académica de la Universidad Santo Tomas seccional Tunja como opción de grado para la facultad de ingeniería civil. Esta se llevó a cabo en la empresa mpj ingeniería s.a.s del municipio de Duitama Boyacá. Donde por parte de la alcaldía se diseña y se da a lugar a la ejecución del contrato número COP- 20200006 el cual tiene como objeto el mejoramiento y rehabilitación de la malla vial del municipio de Duitama. En este libro se muestran las actividades que se ejecutaron hasta el momento de finalización de dicha práctica universitaria. The following work contains the process and activities developed in the academic practice of the Universidad Santo Tomas Tunja sectional as a degree option for the faculty of civil engineering. This was carried out in the company mpj ingenieria s.a.s of the municipality of Duitama Boyacá. Where the mayor's office designed and gave rise to the execution of contract number COP-20200006, whose purpose is the improvement and rehabilitation of the road network of the municipality of Duitama. This book shows the contractual activities that were executed until the time of completion of this university practice. Pregrado

Within the transport sector, road transport is the largest source of Carbon Dioxide (CO2) emissions. Greater use of vehicles that run on clean alternative fuels can contribute to reduce CO2 emissions. This paper gives special attention to the Compressed Natural Gas (CNG) buses and their comparison with conventional diesel buses, which in countries such as Serbia have a dominant share. Justification of using CNG buses in order to mitigate climate changes is measured by realised annual and average external costs of CO2 emissions. These external costs provide a basis for future use of economic instruments by which negative impacts of transport on the environment can be limited. Research of CO2 emissions and external costs of CO2 emissions in intercity bus service was conducted for three technical-technological concepts of CNG buses in comparison to the two types of conventional diesel buses. Analysis was carried out according to four various scenarios that define different operating conditions on the road network of the Serbia. Obtained results show that CNG buses reduce annual external costs of CO2 emissions by 2…24% compared to conventional diesel buses. Obtained average external costs of CO2 emissions per 100 bus-kms show to what extent their changes are a result of changes of external costs of CO2 emissions and to what extent they are due to changes of operating conditions on the road network.

Road networks are one of the useful indicators through which sustainability of urban sprawl for an existing urban area and for a proposed new urban development area can be measured. Therefore, it is necessary for transportation engineers and urban planners to conduct various studies in this regard. In this paper, road networks are modelled and assessed using a method called “Integrated Graph of Natural Road Network (IGNRN)” in which the road networks are evaluated and patterned considering the importance of both nodes and road segments, simultaneously. However, the primal graph and the dual graph, by contrast, considers the importance of junctions and road segments, respectively, which are not sufficiently effective ways as far as all the aspects are concerned. For this study, a GIS-based method has been established. The method contains three major steps; 1) Data preparation 2) Modelling/Generation of IGNRN, and; 3) Measuring three classes of centrality, namely, closeness, betweenness and straightness. Finally, for validation and evaluation of methodology the case study of Kandahar City road network is carried out. The outcome of the results show that the method is accurate, helpful, and worth applying to get useful findings. Keywords: Road Network, Modelling, Integrated Graph, Primal Graph, Centrality, GIS

The paper assesses the development of land use and a road network from 1836 to 2016 in the Hodonín region (Czech Republic). The aim of the article is to verify relationship between the road construction and land use changes in their vicinity. The intensity of land use change processes between adjacent periods was calculated at various distances from roads. ESRI’s geographic information systems and geostatistics were used. This helped in assessing significance of impact of road vicinity on land use changes. The time interval of periods for comparison varied between 25 and 80 years due to availability of historical sources. In each period about 20% of the region was affected by land use changes. After the roads were built, there was an increase in the intensity of land use changes in their vicinity. It has been proofed that presence of a road can be considered one of the driving forces of long-term land use changes in this region. This so-called technological driving force impacted mainly urbanisation and other anthropogenic processes, agricultural intensification and grassing. Its significance is gradually increasing due to urbanisation, industrialisation, motorization and the rising mobility. Our results from the Hodonín region indicate that urbanisation and other anthropogenic processes have the closest relationship with the distance from major roads.

Extracting road network information including lane boundaries, lane centerlines, junctions and their relationship from AIS data plays an important role in location based services, urban computing and intelligent transportation systems, etc. However, AIS data are large scale, high noisy, the density and quality are very uneven in different areas, extracting a whole, continuous and smooth maritime road network with rich information from such data is a challenging problem. To address these issues, this paper proposes an adaptive maritime road network extraction approach that can extract both lane boundaries and centerlines for a large sea area from AIS data. Based on a road network definition including nodes, segments and segment curves, the approach designs parallel grid merging and filtering algorithms to determine if a grided area is inside lane or not. Lane boundaries are smoothed through jagged edge filtering and Simple Moving Average algorithms before centerline extraction. We evaluate our method based on real world AIS data in various area across the world's seas. Experimental results show the advantage of our method beyond the close related work.

In the road network, mix-zone is usually considered as an efficient application that provides a balance between privacy protection and service quality. At the same time, the mix-zone can also resist the attack of tracking without any affection in the quality of feedback result of navigation. However, just as the old adage goes, nobody is perfect, the mix-zone also has two non-negligible deficiencies. The first one is that the mix-zone is difficult to cloak or generalize all types of the attributes emitted by the user. The other one is that the mix-zone is difficult to resist the attack initials by the disguiser who participates in the process of constructing the anonymous group. In order to cope with above-mentioned two problems, this paper provides an uncorrelated mix-zone based on the conception of attribute generalization and homomorphic encryption. In this algorithm, the process of attribute generalization is executed by an agency who is the winner in the private bidding, and the value of generalized attributes value is calculated by the secure multi-party computation under the principle of homomorphic encryption. Accordingly, the private information of the user in the mix-zone is preserved and any entities, no matter the agency or other participants, are prevented from any information about the user as there is no information been exposed. Furthermore, as the attribute of each user is generalized, for the mix-zone leavers, their attributes emitted are similar to each other; it will be difficult for the adversary to correlate any user with the attribute grasped before the user enter the mix-zone. Therefore, the potential hazard of adversary tracking the user with attribute comparison is solved. At last, in order to demonstrate the performance of our proposed algorithm in theoretical and practical fields, several analyses of security and simulation experiments are proposed, and the verification of security as well as the results of simulations and comparisons can further demonstrate the priority.

GPS trajectories collected from automotive telematics for insurance purposes go beyond being a collection of points on the map. They are in fact a powerful data source that we can use to extract map and road network properties. While the location of road junctions is readily available, the information about the traffic control element regulating the intersection is typically unknown. However, this information would be helpful, e.g., for contextualizing a driver’s behavior. Our focus is to use a map-matched GPS OBD-dongle dataset provided by a Canadian insurance company to classify intersections into three classes according to the type of traffic control element present: traffic light, stop sign, or no sign. We design a convolutional neural network (CNN) for classifying intersections. The network takes as entries, for a defined number of trips, the speed and the acceleration profiles over each segment of one meter on a window around the intersection. Our method outperforms two other competing approaches, achieving 99% overall accuracy. Furthermore, our CNN model can infer the three classes even with as few as 25 trips.

The main purpose of the paper is to present a methodical approach to differences in changes in intra-national potential accessibility. Research concerns level of accessibility and its dispersion, both for freight and passenger transport regarding four transport modes. The main added value of the paper is an indication of how to monitor changes in the accessibility of many modes of transport at the municipal level, as a result of investment processes, while taking into account the available data sources, both on the land use data and travel times, with the support of regional and central offices. We focus on the intensive development of transport infrastructure after Poland’s accession to the EU. We conclude that outcomes of reducing territorial differences in accessibility are diverse depending on the transport mode: from a generally positive effect in passenger transport to varied effects in freight transport, including particularly highly polarising effects in rail transport. The research method provides the possibility of analysing multimodal changes in accessibility concerning numerous transport modes for any large country or group of countries. Certain development opportunities of the model to be implemented in the future are discussed.

Invasive alien plant species have impacts on nature conservation, ecosystem services and agricultural production. To identify environmental and human-related drivers of the invasion of Solanum elaeagnifolium (Solanaceae)—one of the worst alien invasive plants worldwide—we conducted an extensive drive-by survey across the Greek territory (presence/absence data, all national major multilane highways, 12–25% of the remaining road network, driven 3–5 times during 2000–2020). These data were linked in GIS with (i) physical environmental attributes (elevation, climate, soil properties) and (ii) type and intensity of human-related activities (land uses, settlements and road type). Compared to previous records, our survey showed that the range of S. elaeagnifolium increased by 1750% during the last decades, doubling its main distribution centers and reaching higher elevations. Our study revealed that the presence of S. elaeagnifolium is associated with (i) higher maximum temperatures and precipitation in summer and low precipitation in winter, as well as with (ii) soil disturbance related to agricultural activities, settlements and road networks, thus facilitating its spread mainly at low altitudes. Our study elucidates the current invasion pattern of S. elaeagnifolium and highlights the urgent need for its widespread monitoring, at least in the noninvaded areas in Greece that have been surveyed in this study. Preventative measures and integrative initiatives should be implemented quickly, and urgently incorporated into current agricultural, road network and conservation-management regimes.

This paper analyses the relationship between road infrastructure improvements and investment in capital assets. Using aggregate data at a provincial level for 1977-2008, an equation for machinery and equipment investment is estimated applying Panel Corrected Standard Errors. The results indicate that the long-term elasticities of investment in relation to market potential, GDP and average years of schooling are 0.90, 0.75 and 0.80, respectively. Additionally, the long run impact of a road infrastructure investment policy is assessed. We find that the elasticities of investment in machinery and equipment, capital stock and GDP in relation to travel time are 1.18, 0.33 and 0.11, respectively

Máster en Ingeniería de Caminos, Canales y Puertos (Plan 2020)

International audience; Road construction is expanding worldwide, exacerbating both direct mortality by road-kills and habitat fragmentation, especially for mobile vertebrates such as bats. Understanding how road density affects bat communities in mosaic landscapes of various compositions and configurations is therefore critical. We acoustically sampled bat communities in 172 landscapes of southern France to: (i) disentangle the relative and interacting effects of road density and forest fragmentation by farmland on the activity of bat communities; (ii) investigate how road density affects different aspects of bat diversity (taxonomic, functional and phylogenetic) and species activity according to their life-history traits; and (iii) assess whether road density effects on bats change with the level of forest fragmentation. Forest amount and patchiness were more important than road density for all components of bat diversity, except for functional evenness. Bat diversity peaked in landscapes with intermediate levels of forest fragmentation, while road density had negative effects on functional and phylogenetic diversity.The effect of road density on the activity of R. ferrumequinum, R. hipposideros, N. leisleri and P. pipistrellus was only negative in landscapes with either a low forest amount or a low number of forest patches. By better understanding interactions between forest fragmentation and road density, our study will contribute to a more adequate landscape planning that will improve the resilience of bat communities to both road expansion and forest fragmentation. Moreover, the complex landscape-level interactions between habitat fragmentation and matrix quality on bats advocate for the use of a more holistic view in future fragmentation studies.; La construction de routes se développe dans le monde entier, exacerbant à la fois la mortalité routière directe et la fragmentation de l'habitat, en particulier pour les vertébrés mobiles comme les chauves-souris. Il est donc essentiel de comprendre comment la densité routière affecte les communautés de chauves-souris dans des paysages en mosaïque de compositions et de configurations diverses. Nous avons échantillonné acoustiquement les communautés de chauves-souris dans 172 paysages du sud de la France pour : (i) démêler les effets relatifs et interactifs de la densité routière et de la fragmentation forestière. (ii) étudier comment la densité routière affecte différents aspects de la diversité des chauves-souris (taxonomique, fonctionnelle et phylogénétique) et l'activité des espèces en fonction de leurs traits d'histoire de vie ; et (iii) évaluer si les effets de la densité routière sur les chauves-souris sont liés au niveau de fragmentation des forêts. La quantité et la fragmentation des forêts étaient plus importantes que la densité des routes pour toutes les composantes de la diversité des chauves-souris, à l'exception de l'équitabilité fonctionnelle. La diversité des chauves-souris atteint son maximum dans les paysages présentant un niveau intermédiaire de fragmentation forestière, tandis que la densité routière a eu un effet négatif sur la diversité fonctionnelle et phylogénétique.L'effet de la densité routière sur l'activité de R. ferrumequinum, R. hipposideros, N. leisleri et P. pipistrellus n'était négatif que dans les paysages présentant un faible niveau de fragmentation forestière ou un faible nombre de parcelles forestières. En comprenant mieux les interactions entre la fragmentation des forêts et la densité des routes, notre étude contribuera à une planification du paysage plus appropriée qui améliorera la résilience des communautés de chauves-souris à l'expansion des routes et à la fragmentation des forêts. En outre, les interactions complexes au niveau du paysage entre la fragmentation de l'habitat et la qualité de la matrice sur les chauves-souris plaident pour l'utilisation d'une vision plus holistique dans les futures études sur la fragmentation.