Length Of Road Network Research Articles

Spatial characteristics of carbon dioxide emission intensity of urban road traffic and driving factors: Road network and land use

Road traffic is a major contributor to global carbon dioxide emissions. The impact of urban road networks and land use on these emissions remains controversial. This study proposed carbon dioxide emission intensity (CEI) based on road network length, analyzed the spatial distribution characteristics of CEI of passenger and freight traffic in the Southern Kanto region of Japan through spatial autocorrelation analysis, and examined the driving effects of urban road network and land use characteristics through Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models. The results showed that the CEI of passenger traffic demonstrated more significant spatial heterogeneity than freight traffic, exhibiting a spatial pattern of high-value clustering in the center and low-value clustering in the peripheral area. Road network characteristics are the primary driving factor for CEI of passenger traffic. A road network with lower density, rich branching streets does not necessarily promote the reduction of carbon dioxide emissions. The industrial land proportion exerts a stronger and more extensive driving effect on the CEI of freight traffic than road network characteristics. As a specialized study on carbon dioxide emissions from road traffic, this study provides the decision-making criteria for urban planning strategy and urban management to enhance urban sustainable development.

Research on multiscale OpenStreetMap in China: data quality assessment with EWM-TOPSIS and GDP modeling

ABSTRACT OpenStreetMap (OSM) is a voluntary platform designed to provide free and up-to-date geographic data. Since OSM is based on multisource geographic data provided by the public, the quality of the data has become a concern of researchers. In this study, a unified measure for evaluating OSM data quality was constructed, and the entropy weight method (EWM) and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) model were used to evaluate the quality of multiscale OSM data in China from 2014 to 2020. In addition to evaluating the data quality, the use of OSM data quality index factors in economic modeling at different spatial scales in China was explored by using a geographic information system (GIS) analysis method and a geographically and temporally weighted regression (GTWR) model. Four machine learning models, SVM, RF, XGBoost and CatBoost, were used to simulate the grid-scale GDP, and the effectiveness of these simulations was discussed. The results showed that (1) the weights of OSM data quality indicator factors vary across different spatial scales. (2) From 2014 to 2020, the quality of national-scale OSM data first increased, then decreased and then gradually stabilized. In addition, the quality of OSM data at the provincial and municipal scales is significantly different, and the distribution is affected by the population and geographical environment. (3) Over time, the spatial clustering characteristics of OSM data quality at different spatial scales in China has continuously strengthened. In addition, the quality of Chinese OSM data displays obvious local spatial autocorrelation characteristics, which are dominated by H-H clustering and L-L clustering. (4) The GTWR model performs well in predicting and revealing the spatiotemporal correlation characteristics between GDP and OSM data quality indicators at the provincial and municipal scales in China. The correlations increase with decreasing spatial scale (provincial to municipal). Moreover, the GDP modeling ability is better in economically underdeveloped Northwest China and economically developed East China. (5) Four machine learning models coupled with road network length completeness, relative linear density, road name attribute completeness, POI name attribute completeness, road network accuracy, road network update frequency, POI update frequency, topological consistency and directional similarity yielded the best grid-scale GDP simulation values. Notably, the CatBoost model provided the best accuracy, and the results further verified that it is feasible to use the proposed OSM data quality index system to predict the regional economic development level in China.

Integrating Urban Air Mobility into a Public Transit System: A GIS-Based Approach to Identify Candidate Locations for Vertiports

Stakeholders expect emerging urban air mobility (UAM) services that use electric vertical takeoff and landing (eVTOL) aircraft to revolutionize transportation systems. However, to be effective, eVTOL facilities, known as vertiports, must seamlessly integrate with the existing multimodal transportation infrastructure. This research analyzes how to best integrate vertiports with the existing public transit network of a city, with San Francisco in the United States as a case study. This study developed a composite optimization model to identify the locations for an optimum number of vertiports within each of the eleven (11) supervisorial districts of San Francisco that would minimize the network distance to its bus stops. The results revealed that 38 locations for vertiports covered 3245 bus stops with an average walk time close to 10 min. Walking 10 min from each vertiport would cover 41.6% of the total road network length and 49.8% of all bus stop locations. Power-law regressions of the average distances as a function of the number of vertiports will help planners to make informed decisions about the optimal vertiport placements in each district by identifying diminishing returns in travel-time savings, and adjustments that consider income and population as additional demand factors.

Urban Development and Transportation: Investigating Spatial Performance Indicators of 12 European Union Coastal Regions

Urbanization is one of the most dominant economic and social changes of the 20th century. This phenomenon brings about rapid urban development, which is inextricably linked to transport development. In order to understand this relationship, it is important to analyze the spatial spillover effects of the phenomenon in the urban environment. This study analyzes the spatial performance, in terms of urban development, of 12 European Union regions from five European countries with coastal areas by incorporating spatial data such as length of road network, population distribution, land uses, and other factors. Key performance indicators have been developed for evaluating the structural development model of the regions (e.g., dense or sprawl development). In addition, the incorporation of spatial spillover effects in the evaluation of the regions was conducted by the extended spatial data envelopment analysis (SDEA) method. The results of SDEA identified the best and worst-performing regions in terms of urban growth. Finally, this study implements a target-setting approach where under-performing regions can best perform. Based on the target-setting approach, local authorities can set realistic targets for improving the structural model that the regions are following.

Identification of road traffic crashes hotspots on an intercity expressway in India using geospatial techniques

Ascertaining the underlying pattern of road traffic crashes (RTCs) and identifying hotspots is essential for improving safety on the road network. Researchers have employed various statistical modelling and spatial methods to predict crash frequency and identify their hotspots on the road network. In India, the road network length has been increasing, especially the expressway network length. The increase in the network length has also increased RTCs. Hence, it is essential to assess the crash pattern and identify hotspots on the intercity expressways in India. This study aims to identify the fatal crash hotspots on the selected intercity expressway using geospatial methods. First, in this study, hotspot sections were identified using ordinary kriging (OK) and, kernel density estimation (KDE), network kernel density estimation (NKDE) methods. Next, the employed techniques were compared to know their predictive effectiveness in identifying the hotspots. The study used the fatal crash data from August 2012 to October 2018 for the selected 165 km intercity expressway. Outcomes of the geospatial methods revealed some of the common hotspots are identified by both methods. The comparative analysis indicated that the NKDE method is more effective in identifying the hotspots in smaller segments than the other two methods. Consequently, this research's outcomes would facilitate intercity expressway-owning agencies to select a practical and readily applicable hotspot identification methodology in LMICs.

Clustering and pedestrian crashes prediction modelling: Amman case

Pedestrian casualties are a severe domestic as well as international problem. This study analyses the spatial distribution of pedestrian casualties to define contributory factors and delineate the means for their prediction. Three years of crash data were collected along with other factors and analysed using kernel density estimation (KDE), spatial autocorrelation (Moran’s I), cluster K-Means, spatial regression, and general linear regressions (GLM). Kernel density estimate defines a cluster of pedestrian deaths within 1250 meters. According to Moran’s I, 17/22 attributes about casualties, road networks, demographics, and land use have positive values, indicating similar importance clustering. The spatial pattern of pedestrian casualties is random and insignificant and does not change with time. Casualties are negatively related to the surrounding attributes, indicating a tendency towards dispersion. A K-Means analysis of multiple variables revealed that when variables included in the clustering were higher, the variance explanation percentage was lower. In the multi-variable GLM assuming Poisson distribution, the road network length alone or with the house permits combined were the best predictors of casualties. Classic regressions were not significantly enhanced by spatial dimension, and none of the autoregressive coefficients were significant. The predictions from the Poisson-based GLM model are similar to the classic regressions.

Evaluating Urban Streets and Public Transportation in Karbala City Using GIS

Because of the privilege of the city of Karbala with its religious character, this city has become a destination for all visitors from all cities of the world; as a consequence, there are now more people living in Karbala, which has increased the number of vehicles on the road and, consequently, the amount of traffic congestion. In this study, the degrees of public transportation service in the city of Karbala as well as the urban road network, were assessed using GIS. The collected data include the number of nodes, links, and the total length of Karbala's urban road network using a GIS program and traffic composition (bus and minibus). Then, a set of coefficients for evaluating the urban road network was calculated) β- Index, α- Index, γ- Index, η- Index and GTP- Index), After determining the percentage of buses and minibusses, it became clear that public transportation in Karbala is very weak and needs development, as the percentage of buses and minibusses did not exceed 30% of the total traffic volume.

A two-phase clustering approach for traffic accident black spots identification: integrated GIS-based processing and HDBSCAN model

Identifying black spots effectively and accurately is a pivotal and challenging task to improve road traffic safety. A novel black spot identification model is proposed by integrating the GIS-based processing with hierarchical density-based spatial clustering of applications with noise. Additionally, the optimal clustering parameters are determined based on an internal validation indicator called the density-based clustering validation index to minimize the impact of subjectivity in parameter selection. The model is validated by collecting 3536 accident data from 1 August to 31 October 2020 in Hangzhou, China, and eventually identifies 39 black spots. The results show that: (1) The number of accidents contained in black spots account for 75% of all accidents, while the length of network in the black spots only account for 23.26% of the total road network length. (2) Compared with the conventional density-based spatial clustering of applications with noise model and K-means model, the proposed model achieves the best performance with more accidents gathered per unit road length. (3) The sample survey with 6 onsite of the identified black spots indicates that the proposed model has high recognition accuracy and recommend these sites for further investigation.

Development of Landslide Susceptibility Mapping Using GIS Modeling in Jordan's Northern Highlands

The purpose of this study is to develop landslide susceptibility mapping using the GIS Technique of areas at risk of landslides in Jordan's Northern Highlands within the regions of Jerash and Ajloun, using the Analytic Hierarchy Process (AHP), harmonious with GIS layout. The main factors considered in this study were geological structure, slope, flood susceptibility, rain intensity, runoff, aspect, elevation, and land use/land cover, which were reclassified and weighted for mapping the levels of landslide hazards in the study area. Each factor/criterion was weighted and assigned a rank or score by using the Pairwise Comparison method for making a decision about the severity of the landslide. Consequently, landslide risk areas can be categorized into five risk levels namely very high, high, moderate, low, and very low. The landslides risk map obtained for the study area shows that the landslides phenomenon is threatening the road network clearly, the percentage of road network; lengths located within the high and very high landslide risk areas was about 53.8% of the total road network length. Also, the results show that about 44.2%, of these, are high and very high landslide risk areas.

Efficient Water Use and Greenhouse Gas Emission Reduction in Agricultural Land Use—The Aspect of Land Consolidation

Efficient water utilization and greenhouse gas emissions have become the topic of wide scientific interest in the last few decades. In this research, we considered the reduction in the road length and the increase in the irrigation channel length after land consolidation. The efficiency of water use is considered as the function of the distance between the water source and crops. The reduction of greenhouse gases is considered as the function of the reduction in the length of the agricultural mechanized transport. A simple mathematical model was developed for calculating the reduction of the road network transport length. The results showed that land consolidation (LC) reduces the road network length, by itself, and provides conditions for an increase in the irrigation channel length. In the case study area, the road network length was reduced by more than one-third (36.8%) and the irrigation channel length was more than doubled (125.9%).

Determinants and effects of Poland’s road accidents in the context of the 2030 agenda for sustainable development – poviat level analysis for the years 2010-2019

The objective of the research was to assess how selected factors influence road safety in Poland’s poviats. To that end, an analysis was conducted of road accident determinants and effects in the poviats in the years 2010-2019. The time horizon fits in with Goal 3.6. of Agenda 2030 which is to halve the number of global deaths and injuries from road traffic accidents by 2020. The article presents the results of the analysis for the following determinants: the rate of car ownership by poviat, poviat spending on transport and length of road network, and quality of road infrastructure. The research problem was to establish which of the poviats are closest to achieving Goal 3.6. of Agenda 2030 and how likely it is, and, as a consequence, which of the poviats should step up their road safety policies to align them to the targets set out in the Agenda. To identify groups of poviats sharing similar characteristics, they were grouped using the k-means method. Five groups of poviats were identified and analysed for how their road safety indicators changed between 2010 and 2019. The results of the analysis show that the highest fatality reduction (-40%) was achieved by urban poviats with the highest per capita spending on transport. The same poviats, however, have the highest increases in serious injuries (+30%). The analyses show that Polish poviats are still far from achieving Goal 3.6 of Agenda 2030. The research results presented in the article are original for the poviat level.

Integrating criticality concepts into road network disruption assessments for volcanic eruptions

Road networks in volcanically active regions can be exposed to various volcanic hazards from multiple volcanoes. Exposure assessments are often used in these environments to prioritise risk management and mitigation efforts towards volcanoes or hazards that present the greatest threat. Typically, road exposure has been assessed by quantifying the amount of road network affected by different hazards and/or hazard intensity. Whilst this approach is computationally efficient, it largely fails to consider the relative importance of road segments within the network (i.e., road criticality). However, road criticality is an important indicator of the disruption that may be caused by an eruption. In this work, we aim to integrate road criticality concepts to enhance typical volcanic eruption road exposure assessments into road disruption assessments. We use three key components to quantify disruption: a) road criticality, b) impact severity, and c) affected road quantity. Two case study eruptions: Merapi 2010 and Kelud 2014, both in Java, Indonesia, are used to demonstrate the usefulness of integrating road criticality into road disruption assessments from volcanic eruptions. We found that disruption of the road network from the Kelud 2014 case study was an order of magnitude greater than the Merapi 2010 case study. This is primarily driven by the more widely dispersed tephra fall from the Kelud 2014 event, which affected nearly 28% of Java’s road network length, compared to Merapi 2010, which affected 1.5%. We also identified potential disruption hotspots that were affected by both of these case study eruptions. At Merapi, roads that carry traffic directly away from the summit, those that cross major valleys, and the major Yogyakarta-Magelang highway were key disruption hotspots, which has implications for moving large volumes of traffic efficiently, such as in an evacuation. The Kelud case study highlighted the potential impacts of widespread tephra falls on socio-economic activity and connectivity of large urban centres. Our approach has been designed such that it can be applied entirely using open-sourced datasets. Therefore, the approach to integrating road criticality in this paper can be used, applied, and adapted to assess road network disruption at any volcano in the world.

Evaluation of the Effect of RAP and Lime on Geotechnical Properties of Clayey Soil

Abstract: Road network plays a large role in the rapid development of the economy of a country, providing connectivity to remote areas for various transportation activities. India ranks second in the world in terms of length of road network after the United States. The major road network in the urban locality consists of bituminous pavements periodically resurfaced during maintenance. From the milling process, reclaimed asphalt pavement (RAP) is obtained. Additionally, RAP can be used for the utilization of recycled asphalt pavement (RAP) materials in subgrade soil. Reclaimed Asphalt Pavement (RAP) is being used in this case study to stabilize the subgrade soil collected from Crop Research Center (CRC), Govind Ballabh Pant University, Tanda Range, Uttarakhand (29°01'09.7"N, 79°28'55.9"E). To conduct the experimental program, a variable amount of RAP percentages viz., 5, 10, 15, and 20%, and different percentages of lime i.e., 2, 4, 6, and 8% were mixed with natural soil. Based on gradation, Standard Proctor Test (SPT), Unconfined Compressive Strength (UCS), California Bearing Ratio (CBR), and Specific gravity, the characteristics of RAP-soils with added lime were evaluated. For soil mixture including 10% RAP and 4% lime, a maximum MDD of 19.04 and a percentage increase in compaction of 11.93% was observed. OMC value was observed as 11.35%, which further decreased as RAP content increased. Due to RAP containing coarse aggregate, a higher CBR value was obtained due to the harder sample surface. For all soil mixers of 15% RAP and 4% lime, unsoaked CBR and soaked CBR values were found to be 31.39% and 18.69% respectively. Percentage increases in their respective CBR values were 868.83% and 662.86%. for every percentage of lime variation, maximum CBR was obtained at 15% RAP, and maximum CBR value for soaked CBR was obtained for soil with 15% RAP and 2% lime, whereas for unsoaked CBR, it was obtained for soil with 15% RAP and 4% lime. Maximum UCS values of 412.45 kN/m2 , 606.81 kN/m2 and 857.62 kN/m2 were observed on 3rd, 7th and 14th days for soil mix with 15% RAP and 4% lime, with percentage increase of 291.17%, 249.40% and 387.78% respectively. Based on the results of the study, RAP materials can be effectively used in the soil subgrade, sub-base, and base of flexible pavements, reducing the cost of construction. Keywords: Reclaimed Asphalt Pavement (RAP), Lime, CBR, SPT, UCS, OMC, MDD.

Spatiotemporal Analysis of Road Crashes with Animals in Poland

This article describes the issue of the influences of the time factor and wildlife populations on road animal–vehicle crashes. The article presents problems associated with animal–vehicle crashes in Poland. They are the subject of many court disputes. For the purposes of the study, data on animal–vehicle road crashes were obtained from the SEWiK database, as well as data on the numbers of animals in hunting districts from 2016–2020. The relationship between the number of road crashes and time was analysed, and the relationships between the numbers of road crashes and the animal populations, as well as the locations, types, and categories of the hunting districts, were analysed as well. The factors related to changes in the wildlife populations, road crashes in previous years, and the lengths of the road networks were also analysed. The research shows no relationship between the abundance of a particular species and the number of road crashes. Instead, there is a correlation between the number of crashes in previous years and the road network length.

Speed limits and accident rates on highways around the world, is there a correlation?

The objective of this study stands for the investigation and evaluation of accidents that take place on highways, in comparison with speed limits. The main body of this research is based on the collection of highways speed limits from different countries around the globe regarding to years, 2010, 2017 and 2018. Secondly, accident rates are collected from highway authorities, as well as from international literature. Subsequently, a statistical analysis of the collected data is conducted and finally leads to an equation that links and correlates the speed limit values and the number of accidents. The results of this statistical analysis show that speed limit plays a certain and distinctive role in the accident rate value. However, one of the interesting findings, stands for the non-continuously increasing number of accidents in the speed limit range, from the lowest to the highest value, meaning that there is an inflection point in the graph of the correlation equation. To be noted, that in terms of this study, the aforementioned correlation is independent of other factors that could affect the accident rate, such as vehicles condition, technology, road network length and condition.

Women victims of road accidents and public health in India

Road transport is the dominant mode of transport in India, both in terms of traffic share and in terms of contribution to the national economy. To meet the demand for road transport, the number of vehicles and the length of road network have increased over the years. A negative externality associated with expansion in road network, motorization and urbanization in the country is the increase in road accidents and road crash fatalities. Today, road traffic injuries are one of the leading causes of death, disabilities and hospitalization in the country imposing huge socio-economic costs. Road safety is emerging as a major social concern in the country. The number of deaths per year per 10000 motor vehicles in India is 10 to 15 times more than that in advanced countries. According to a survey from WHO, each year road traffic injuries take away lives of 1.2 million men, women, and children around the globe and injure many more. The death toll is on the higher side for the countries where pedestrians, motorcyclists and passengers are vulnerable and vehicles lack the safety norms, like India. This paper through a primary research tries to look at the impact road traffic injuries on women victims and their post trauma care in Delhi.

Scientific-technical progress and transport as essential factors of territorial organization of building-industrial complexes

Industrialization calls significant changes into traditional methods of building and precondition the transfer of some portion of the process of building from building sites to steady-state plant conditions. It is now due to assemblable parts, prefabricated structures and plant production of ready-to-use oversize blocks and parts that that the scope of works on building sites is essentially resuced. The process of building is characteristic for different forms of its organization that manifests itself in specialization, concentration, cooperation and combination. Development of these forms results in deeper specialization of labor, as well as in deepening of sectoral and technological specialization supported by transport means. A scope of building and assembly within specific territory leads to concentration of big number of building organizations. Concentration of building-related companies and organizations predefines the necessity of coordination of their efforts. The speed of construction requires still deeper specialization. The stage-based process of building rooted in by the technologies requires strict organization between inter-unit attachments that produce building materials, parts and constructions, and those that build. The pre-planned organization between the participants of the process of building is reached by way of cooperation. Coordination of the scope of building between the companies and organizations is executed by the general contraction organization that is responsible for the whole construction. Cooperation of contracting and subcontracting general building and special organizations is helpful in such coordination and timely completion of works. It is due to transport that cooperation involves local and remote companies and organizations. In the aspect of territory, these companies and organizations form district inter-district, regional, inter-regional, and international links that make up the basis for the formation of building-industrial complexes. Development of the levels and forms of territorial organization of building-industrial complexes depends on the scope of building, natural and economic specificities of the area, and the level of provision with material-technical and industrial-material bases, etc. Carpathian administrative oblasts are the territories with sufficiently developed material-technical and industrial-material bases. This means that they possess highly qualified staff and may use the systems of special highly productive building machines and mechanisms, implement automation of some technological operations, and, with well-organized transport system, therefore improve territorial forms of the process of building. Transport within the system of productions in building industry has internal and external functions. The internal function of transport lies in provision of technological processes of building (technological transport). The material-technical basis of this kind of transport is predominantly concentrated in building-related companies and organizations. The external function is performed by transport means that provide the process of building with necessary material resources. It is, as a rule, the transport of different companies and organizations that specialize in distant transportations. Their material base has no relation to the same of the building industry. The level of development of internal transport depends on equipment status of building companies and organizations, and building technological achievements on the level of country and some of its regions. The level of development of external transport is provided by the level of development of the whole transport system of the state and its each separate region in particular. In both cases, transport represents an important factor that effects on the formation of building-industrial complexes of every level of development. The division into internal and external transport is conventional, since each of them can perform both functions. The work of the transport system significantly depends on the development of transport network, which is too far in Ukraine from the present-day world standards. However, the transport means themselves used in this country are in the majority of cases the production of known world companies. Geographical disposition and specificities of economic development have predefined the formation of practically all types of transport on the territory of Ukraine. Railway and automobile transport are the leading types in all economic rayons of the country, while pipeline, water and air kinds of transport are well developed in some other rayons. The total length of public road network in Ukraine was 169,5 thousand km in 2019, railway lines – 22,0 thousand km, river navigable waterways – 2,3 thousand km. Automobile roads and railway constitute the basis of the transport network in the Carpathian oblasts. The highest density of roads is found in the Lviv Oblast (over 60 km/1000 km2. The best provision with auto-roads is observed in the Chernivtsi and the Lviv oblasts. It is only natural that mountain regions suffer from worse provision with communications than those in plain and pre-mountain territories. Automobile and railway transport play the key role in provision of the process of building.

Spatiotemporal persistence of bat roadkill hotspots in response to dynamics of habitat suitability and activity patterns

Wildlife roadkill hotspots are frequently used to identify priority locations for implementing mitigation measures. However, understanding the landscape-context and the spatial and temporal dynamics of these hotspots is challenging. Here, we investigate the factors that drive the spatiotemporal variation of bat mortality hotspots on roads along three years. We hypothesize that hotspot locations occur where bat activity is higher and that this activity is related to vegetation density and productivity, probably because this is associated with food availability. Statistically significant clusters of bat-vehicle collisions for each year were identified using the Kernel Density Estimation (KDE) approach. Additionally, we used a spatiotemporal analysis and generalized linear mixed models to evaluate the effect of local spatiotemporal variation of environmental indices and bat activity to predict the variation on roadkill hotspot locations and to asses hotspot strength over time. Between 2009 and 2011 we conducted daily surveys of bat casualties along a 51-km-long transect that incorporates different types of roads in southern Portugal. We found 509 casualties and we identified 86 statistically significant roadkill hotspots, which comprised 12% of the road network length and contained 61% of the casualties. Hotspots tended to be located in areas with higher accumulation of vegetation productivity along the three-year period, high bat activity and low temperature. Furthermore, we found that only 17% of the road network length was consistently classified as hotspots across all years; while 43% of hotspots vanished in consecutive years and 40% of new road segments were classified as hotspots. Thus, non-persistent hotspots were the most frequent category. Spatiotemporal changes in hotspot location are associated with decreasing vegetation production and increasing water stress on road surroundings. This supports our hypothesis that a decline on overall vegetation productivity and increase of roadside water deficit, and the presumed lower abundance of prey, have a significant effect on the decrease of bat roadkills. To our knowledge, this is the first study demonstrating that freely available remote sensing data can be a powerful tool to quantify bat roadkill risk and assess its spatiotemporal dynamics.

Cycling development in Moscow as part of the policy of sustainable development of the metropolis

Bicycle transport is a popular and promising means of transport in the largest cities, as well as the least developed in terms of business travel purposes. The paper substantiates the importance of developing bicycle transport infrastructure in the largest cities through the example of Moscow. The development of bicycle transport is inextricably associated with sustainable urban development and meets the goals of the VizionZero program, leads to the decrease in the use of individual motor transport, increases the physical activity of the population and also has a positive effect on the development of urban environment. The paper highlights the main purposes of the cycling movement of the population and emphasizes the importance of the development of business movement. The characteristics of the development of bicycle-transport network are given. The importance of the integrated approach in the development of a city is substantiated, including the development of a bicycle-transport network with provision of connectivity and safety during its construction. The problems of the development of cycling in Moscow are determined on the example of foreign and Russian cities, as well as strategies for the development of transport infrastructure. The value characterizing the quality of the network development in the city is determined presented by the length of cycle road network per 1 inhabitant. The main problems of the development of cycling transport in the city of Moscow are found and the prospects for the development of the bicycle transport network in Moscow are outlined through the example of the work of Moscow Transport Department and Moscow General Planning Research and Project Institute. The time spent on cycling along the selected routes is analyzed in comparison with car driving during rush hours in road network. As a result it is found that the time spent on cycling is lower compared to traveling by car. In addition, the possibility of developing a bicycle transport network in the red lines of Moscow road network is found. The authors put emphasis on the relevant character of the problem of social perception of cycling transport among the population and determine the directions for increasing the social approval of this type of transport.

Allometric scaling of road accidents using social media crowd-sourced data

Traffic accidents in Lebanon are constantly harvesting lives, dramatically changing others, and traumatizing those of their beloved ones. Due to the lack of statutory authority in charge of collecting and reporting accident related data, the Lebanese Road Accident Platform (LRAP) is proposed in this work as a real-time online platform to collect crash events from social media. LRAP allows for autonomous data collection, classification and visualization without human intervention, and aims to help the authorities in laying down the appropriate measures for traffic accidents prevention. After being in production for the last four years, the data extracted from LRAP was used to study the allometric scaling of accidents with respect to different parameters such as district area, population size per district and road network length. Such approach offers a new perspective on traffic accidents’ scaling and behavior as a living organism as cities grow. A seasonality trend analysis is also provided to analyze temporal clustering patterns in crash occurrence.