Road Network Analysis Research Articles

Road traffic bottleneck analysis for expressway for safety under disaster events using blockchain machine learning

To analyze the largest capacity of expressway network, the concept of road network bottleneck and its analyzing method are presented. Based on the bottleneck theory in Graphics, road network bottleneck is defined, and Ford-Fulkerson method and super origin-destination, short for OD, method are adopted for analysis of single OD and multiple OD road networks respectively. With Beijing-Hongkong-Macau expressway in Anyang-Xinxiang road network, Henan province, as a case study, application of road network bottleneck was investigated in aspects of network entrance management, network congestion points analysis and traffic assignment. For overall analysis of the congestion points in road network, the concept of bottlenecks chain corridor was presented. Bottlenecks chain corridors are key corridors for traffic diversion under disastrous events, which have major impact on the operation of road network. The case study indicates that road network bottleneck and bottlenecks chain corridor have significant value in expressway network operation management.

The morphology and circuity of walkable, bikeable, and drivable street networks in Phnom Penh, Cambodia

Street network analysis is a growing area in sustainable transportation research. Most academic papers on the topic have, so far, been concentrated in Europe and America, with less attention paid to rapidly growing cities in low income nations. This is problematic because transportation networks are rapidly evolving in developing countries and the impacts of misguided transportation policies (including air pollution and road traffic casualties) are particularly acute. Metrics on the performance of street networks could help inform policy. This paper uses the Python package OSMnx to analyze and evaluate street networks in 12 districts of Phnom Penh from OpenStreetMap. Results suggest that topological and geometric characteristics of street networks are more conducive to walking and biking in the central districts than in the peripheral districts. The central districts are also better connected to core network corridors. To promote sustainable urban mobility, new developments and street renewals should be incorporated facilities, services, and safety of walking and biking. Some policy implications are suggested for future designs of the Phnom Penh’s street networks to increase livability and sustainability.

Urban Settlements and Road Network Analysis on the Surrounding Area of the Almirante Alvaro Alberto Nuclear Complex, Angra dos Reis, Brazil

Nuclear power plants accidents should be seen as very complex issues, once they encompass environmental and social aspects that must be integrated to sustain appropriate management measures in a potential disaster event. Therefore, emergency plans require sounds spatial information knowledge and the interactions of their environments. The herein study aims to contribute to the emergency plans, especially to the possible evacuation routes identification for a Nuclear Power Plant located in Angra dos Reis, Brazil. The study was conducted within 120 km radius around the power plant. Results indicate that evacuation plans should be elaborated for the urban cores with low roads availability, or even for high population density areas, that in spite of being well served by alternative routes, exhibit increased road traffic and population flow. These results present important information to provide support to local emergency management actions and guidelines, playing a key role to assist on the evacuation planning.

Traffic performance analysis of road network based on congestion patterns

Traffic performance analysis of road network based on congestion patterns

Discovery of Critical Nodes in Road Networks Through Mining From Vehicle Trajectories

A major problem in road network analysis is discovery of important crossroads, which can provide useful information for transport planning. However, none of existing approaches addresses the problem of identifying network-wide important crossroads in real road network. In this paper, we propose a novel data-driven based approach named CRRank to rank important crossroads. Our key innovation is that we model the trip network reflecting real travel demands with a tripartite graph, instead of solely analysis on the topology of road network. To compute the importance scores of crossroads accurately, we propose a HITS-like ranking algorithm, in which a procedure of score propagation on our tripartite graph is performed. We conduct experiments on CRRank using a real-world dataset of taxi trajectories. Experiments verify the utility of CRRank.

Coupling Natural Hazard Estimates with Road Network Analysis to Assess Vulnerability and Risk: Case Study of Freetown (Sierra Leone)

Many of the world’s most disaster-prone cities are also the most difficult to model and plan. Their high vulnerability to natural hazards is often defined by low levels of economic resources, data scarcity, and limited professional expertise. As the frequency and severity of natural disasters threaten to increase with climate change, and as cities sprawl and densify in hazardous areas, better decision-making tools are needed to mitigate the effects of near- and long-term extreme events. We use mostly public data from landslide and flooding events in 2017 in Freetown, Sierra Leone to simulate the events’ impact on transportation infrastructure and continue to simulate alternative high-risk disasters. From this, we propose a replicable framework that combines natural hazard estimates with road network vulnerability analysis for data-scarce environments. Freetown’s most central road intersections and transects are identified, particularly those that are both prone to serviceability loss due to natural hazard and whose disruption would cause the most severe immediate consequences on the entire road supply in terms of connectivity. Variations in possible road use are also tested in areas with potential road improvements, pointing to opportunities to harden infrastructure or reinforce redundancy in strategic transects of the road network. This method furthers network science’s contributions to transportation resilience under hydrometeorological hazard and climate change threats with the goal of informing investments and improving decision-making on transportation infrastructure in data-scarce environments.

Angular and Metric Distance in Road Network Analysis: A nationwide correlation study

There is an epistemological divide in the field of road network analysis, concerning the way network distance should be conceptualized. On one hand, the generality of studies in the field adopt metric distance as a self-evident choice. On the other, space syntax studies adopt a different distance concept, namely that of angular distance, which ignores actual physical lengths. Theoretically, these two distance concepts imply quite different assumptions. Analytically, they produce also different results.In this paper we assess the differences between these two network distance concepts, using a model of the UK's complete road network (2,031,971 nodes) and a very large dataset of vehicular movement counts (20,752 locations). We describe the statistical associations between observed vehicular flows and the betweenness centrality of the road-network nodes where such flows were measured, the latter calculated with metric and angular distance functions, across a number of increasing radii. Relations to road capacity are also discussed in principal roads where this is known.The geographical comprehensiveness of our model and the size of our movement sample allow us to state, with unprecedented statistical validity, the clear outperformance of angular distance over metric distance, in what concerns the strength of the studied correlations. This is true for all types of roads (urban and non-urban) and for all motorized vehicles, representing 99.05% of the total traffic; the remaining 0.95% correspond to pedal cycles, which yielded inconclusive results. We also demonstrate the existence of two distinct regimes of association between movement and centrality, conspicuous in cities but altogether absent in non-urban areas, which represent new evidence supporting space syntax's dual model of urban form.

ANALISIS KELAYAKAN PERENCANAAN PEMBANGUNAN JALAN PENGHUBUNG (MISSING LINK) ANTARA DESA SIKUR SAMPAI DESA PAOKMOTONG KABUPATEN LOMBOK TIMUR

In 2017, the Government of East Lombok plans to improve their public services, especially in the transportation sector related to the activation of the Paokmotong s new market. Thus government plans to build a connecting road in this national road. At the moment, the plan shows the highest v / c ratio at 0.51 and the busiest intersections with saturation degree at 0.76, which in the year of the plan would be arise as a new problem of transportation. This study includes road network analysis performance before and after the implementation of the road plan scenario. VISSIM software is used to support the trip assignment stage. By using this software, amount of technical aspects are examined include: the average speed of the network, travel time, trip distance, and average delay network. While in the Path Trace analysis also includes horizontal alignment, vertical alignment and layer of pavement plan. One more addition, is about economic factor. Economic development feasibility is done by comparing road construction costs and travel cost efficiencies through the project year which include: Net Present Value (NPV), Benefit Cost Ratio (BCR) and Internal Rate Return (IRR).

Reliability analysis of road networks in disaster waste management

The condition of road networks which connect disaster affected areas and final disposal sites has a critical role in the management of disaster waste. In this paper, we present a two-stage framework to estimate the overall reliability and failure modes of a disaster waste management system considering the reliability of each route involved in the road network. In the first stage, first order reliability method and Ditlevsen bounds are applied to estimate system reliability. In the second stage, an event tree approach is implemented to analyse the failure modes of the system. The methodology is demonstrated with an artificial case study considering three different scales of disasters. The results obtained from the case study can provide information to decision makers regarding the priority of the routes in the system and the most likely failure mode.

Network-scape metric analysis: a new approach for the pattern analysis of urban road networks

ABSTRACTThe spatial patterns of road networks reflect the morphological and structural characteristics of cities. Previous studies have focused mainly on seeking universal laws in road networks rather than explaining their differences. A new approach for road network pattern analysis is proposed that has been inspired by landscape metric analysis. The utility of this approach is illustrated through (but is not limited to) the extraction of the main factors in network landscapes, or network-scapes for short. Twenty-four metrics were calculated for network-scapes of 100 cities worldwide, before an exploratory analysis is performed to detect the main factors. Four main factors were revealed and may be regarded as the characteristic indicators of road networks, which were identified to be evenness, richness-density, shape irregularity, and size and shape variation. The meanings of these factors are explained, and their spatial distributions are illustrated. Compared to existing road network analytics, these factors depict better the characteristic differences of road networks. The proposed approach provides a new framework for road network pattern analysis from a cellular perspective.

Planarity and street network representation in urban form analysis

Models of street networks underlie research in urban travel behavior, accessibility, design patterns, and morphology. These models are commonly defined as planar, meaning they can be represented in two dimensions without any underpasses or overpasses. However, real-world urban street networks exist in three-dimensional space and frequently feature grade separation such as bridges and tunnels: planar simplifications can be useful but they also impact the results of real-world street network analysis. This study measures the nonplanarity of drivable and walkable street networks in the centers of 50 cities worldwide and then examines the variation of nonplanarity across a single city. It develops two new indicators—the Spatial Planarity Ratio and the Edge Length Ratio—to measure planarity and describe infrastructure and urbanization. While some street networks are approximately planar, we empirically quantify how planar models can inconsistently but drastically misrepresent intersection density, street lengths, routing, and connectivity.

A spatial design network analysis of street networks and the locations of leisure entertainment activities: A case study of Wuhan, China

This paper examines the spatially stratified association between various urban leisure entertainment activities and street configurations via a spatial design network analysis and attempts to provide insightful implications for the sustainable development of a city by using a typical inland city of China, Wuhan, as an example. The street network is characterized by performing a spatial network analysis of the closeness, betweenness, severance and efficiency parameters. The kernel density estimation (KDE) method is employed to measure the proximities of every place to various types of leisure entertainment facilities. The two sets of densities are then analyzed to determine whether spatially stratified correlations exist and whether various leisure entertainment facilities are more spatially correlated with specific street features. The results indicate that a good street network design can be measured not only by closeness or betweenness but also by severance and efficiency. Four street network metrics are spatially correlated with the locations of leisure entertainment activities. Various types of leisure entertainment activities have distinct locational preferences for street networks (e.g., chess and card rooms favor closeness). The conclusions of this paper can help urban planners and policy-makers spatially optimize street networks and leisure venues to develop a sustainable city.

A GRASS ROOT ORIENTED URBAN PLANNING APPROACH TO UPLIFT THE SOCIO-ECONOMIC FACET OF A CITY USING 2D AND 3D GIS: CASE STUDY ON MEHMEDABAD CITY, INDIA

Abstract. Being a developing nation, India is facing an array of problems owing to the huge population shift from rural to urban areas, thereby leading to an increasing urbanisation trend since the 1980s. As a result, the process of urban planning in India is extremely tedious and requires lots of manual intervention. Although the recent developments in GIS have immensely helped urban planners, extensive ground survey is still a big challenge in the context of Indian cities. In this work, the study area has been chosen as Mehmedabad which is a Tier-3 city in the state of Gujarat. A rigorous grass root oriented ground survey involving each and every household of Mehmedabad has been utilised for both requirement elicitation and site-suitability purposes. With the aid of both 2D and 3D GIS, a city development plan has been proposed for the year 2031. The planning process incorporated population projection, water supply demand, sewage discharge and road network analysis for building robust development control regulations which were essential to improve the socio-economic aspects of Mehmedabad. Additionally, cost estimations for each of the proposed sectors have been carried out so as to maintain an appropriate budget for uplifting the existing infrastructures of the city.

Does the regional deprivation impact the spatial accessibility to dental care services?

The aim of the present study was to assess the regional deprivation and individual factors that influence how far a person will travel to access dental care. Using data from the Korea Health Panel (2008 to 2011), we selected a group of 4,256 subjects and geocoded their homes and dental hospitals/clinics. Using the road network analysis, we calculated the distance traveled by the subjects for dental care. We used the generalized estimating equation (GEE) for repeated data analysis and included an interaction term between regional deprivation and individual income to determine the effects of the two factors on the choice of a dental hospital/clinic. When the regional deprivation index was divided into three quarters (high, middle, and low), urban areas had higher”high” and “low" levels of deprivation, and rural areas had relatively higher middle level of deprivation. GEE regression showed that the level of education, regional deprivation level, and income all affected the distance traveled to dental clinics. The regional deprivation level had a higher association than income with the travel distance. At the same income level, subjects who lived in the least deprived areas were more likely to travel longer distances than subjects living in the most deprived areas. Regarding the distribution of dental hospitals/clinics, incentive based dental polices for either dental providers or patients are needed that will assure the delivery of dental care despite spatial inequality.

A multi-scale analysis of 27,000 urban street networks: Every US city, town, urbanized area, and Zillow neighborhood

OpenStreetMap offers a valuable source of worldwide geospatial data useful to urban researchers. This study uses the OSMnx software to automatically download and analyze 27,000 US street networks from OpenStreetMap at metropolitan, municipal, and neighborhood scales—namely, every US city and town, census urbanized area, and Zillow-defined neighborhood. It presents empirical findings on US urban form and street network characteristics, emphasizing measures relevant to graph theory, transportation, urban design, and morphology such as structure, connectedness, density, centrality, and resilience. In the past, street network data acquisition and processing have been challenging and ad hoc. This study illustrates the use of OSMnx and OpenStreetMap to consistently conduct street network analysis with extremely large sample sizes, with clearly defined network definitions and extents for reproducibility, and using nonplanar, directed graphs. These street networks and measures data have been shared in a public repository for other researchers to use.

From the betweenness centrality in street networks to structural invariants in random planar graphs

The betweenness centrality, a path-based global measure of flow, is a static predictor of congestion and load on networks. Here we demonstrate that its statistical distribution is invariant for planar networks, that are used to model many infrastructural and biological systems. Empirical analysis of street networks from 97 cities worldwide, along with simulations of random planar graph models, indicates the observed invariance to be a consequence of a bimodal regime consisting of an underlying tree structure for high betweenness nodes, and a low betweenness regime corresponding to loops providing local path alternatives. Furthermore, the high betweenness nodes display a non-trivial spatial clustering with increasing spatial correlation as a function of the edge-density. Our results suggest that the spatial distribution of betweenness is a more accurate discriminator than its statistics for comparing static congestion patterns and its evolution across cities as demonstrated by analyzing 200 years of street data for Paris.

Reconciling certification and intact forest landscape conservation.

In 2014, the Forest Stewardship Council (FSC) added a new criterion to its principles that requires protection of intact forest landscapes (IFLs). An IFL is an extensive area of forest that lacks roads and other signs of human activity as detected through remote sensing. In the Congo basin, our analysis of road networks in formally approved concessionary logging areas revealed greater loss of IFL in certified than in noncertified concessions. In areas of informal (i.e., nonregulated) extraction, road networks are known to be less detectable by remote sensing. Under the current definition of IFL, companies certified under FSC standards are likely to be penalized relative to the noncertified as well as the informal logging sector on account of their planned road networks, despite an otherwise better standard of forest management. This could ultimately undermine certification and its wider adoption, with implications for the future of sustainable forest management.

A Big-Data based and process-oriented decision support system for traffic management

Data analysis and monitoring of road networks in terms of reliability and performance are valuable but hard to achieve, especially when the analytical information has to be available to decision makers on time. The gathering and analysis of the observable facts can be used to infer knowledge about traffic congestion over time and gain insights into the roads safety. However, the continuous monitoring of live traffic information produces a vast amount of data that makes it difficult for business intelligence (BI) tools to generate metrics and key performance indicators (KPI) in nearly real-time. In order to overcome these limitations, we propose the application of a big-data based and process-centric approach that integrates with operational traffic information systems to give insights into the road network's efficiency. This paper demonstrates how the adoption of an existent process-oriented DSS solution with big-data support can be leveraged to monitor and analyse live traffic data on an acceptable response time basis.

Planarity and Street Network Representation in Urban Form Analysis

Models of street networks underlie research in urban travel behavior, accessibility, design patterns, and morphology. These models are commonly defined as planar, meaning they can be represented in two dimensions without any underpasses or overpasses. However, real-world urban street networks exist in three-dimensional space and frequently feature grade separation such as bridges and tunnels: planar simplifications can be useful but they also impact the results of real-world street network analysis. This study measures the nonplanarity of drivable and walkable street networks in the centers of 50 cities worldwide, then examines the variation of nonplanarity across a single city. It develops two new indicators - the Spatial Planarity Ratio and the Edge Length Ratio - to measure planarity and describe infrastructure and urbanization. While some street networks are approximately planar, we empirically quantify how planar models can inconsistently but drastically misrepresent intersection density, street lengths, routing, and connectivity.

WATERSHED ROAD NETWORK ANALYSIS WITH AN EMPHASIS ON FIRE FIGHTING MANAGEMENT

The aim of this study is fire hazard zoning the Chehel-Chay watershed and analysis of road network in order to fire-fighting management. Using effective factors on fire occurrence, the fire hazard map of the study area produced by support vector machine algorithm and then was divided into four hazard classes. The road length and type were investigated in the each fire hazard classes. The results showed that most of occurred fires are located in the close distances of roads and forest areas. The results showed that road types and land cover are important in fire occurrences and suppression. In high dangerous zone, the roads pass through forestlands, but in low dangerous zone, the roads are passing from farmlands. The roads do not cover the half of area and do not pass at two third of high hazard class zones. Therefore, appreciate road network planning is necessary according to fire-fighting management.