scholarly journals Optimizing The Functional Performance of Road Network using Vulnerability Assessment to Cope with Unforeseen Road Incidents

2021 ◽  
pp. 67-80
Author(s):  
Mukhammad Rizka Fahmi Amrozi ◽  
Raihan Pasha Isheka
Keyword(s):  
Road Network ◽  
Functional Performance ◽  
Road Networks ◽  
Travel Speed ◽  
Vulnerability Index ◽  
Urban Road ◽  
The Road ◽  
Road Performance ◽  
Criticality Index ◽  
The Impact

An Urban Road network is often used for multipurpose trips, due to their transportation functions, such as attractiveness and orientation, as well as social, ecological, and economic features. In Indonesia, road incidents have reportedly increased during the last decade because of a higher frequency of natural hazards, accidents, and on-street mass demonstrations. These incidents are found to degrade or terminate road access, forcing users to utilize alternative routes and decreasing the service performance in adjacent directions. Due to the unexpected occurrences at any location and time, there is a need to investigate the impact of random incidents on road performances. Several accessibility indexes have also been used to evaluate the vulnerability of road networks. However, this is less practical in Indonesia, with the road authority using functional performances as the indicator. This indicates the need for an index to be developed based on road performance parameters. Therefore, this study aims to develop a road performance-based vulnerability index known as the RCI (Road Criticality Index). Combined with a traffic simulation tool, this system is used as an alternative index to assess vulnerabilities, by identifying the road(s) providing worse consequences due to unforeseen incidents. This simulation was conducted by using the PTV Visum, assuming a road section is closed due to the worst incident scenarios. The result showed that the RCI offered a more comprehensive assessment than the existing indicator (volume capacity ratio). The RCI included travel speed and mobility components for evaluating both local and global road performances. With the knowledge of the most vulnerable locations and their consequences, road authorities can prioritize maintenance and development strategies based on the criticality index. Also, preventive measures should be conducted to mitigate risk under a constrained budget. This methodology can be applied to sustainably enhance the resilience of urban road networks.

scholarly journals Impact of Road Network Topology on Public Transportation Development

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Minzhi Chen ◽  
Fan Wu ◽  
Min Yin ◽  
Jiangang Xu
Keyword(s):  
Public Transportation ◽  
Road Network ◽  
Road Networks ◽  
Urban Road Network ◽  
Urban Road ◽  
The Road ◽  
Layout Structure ◽  
Per Capita ◽  
Transportation Development ◽  
The Impact

Planning of road networks is fundamental for public transportation. The impact of road network density on public transportation has been extensively studied, but few studies in this regard involved evaluation indicators for connectivity and layout of road networks. With 29 cities in China as the study cases, this paper quantifies the layout structure of the road network based on the network’s betweenness centralization and establishes a multivariate linear regression model to perform regression of the logarithm of the frequency of per capita public transportation on betweenness centralization. It is found in the present work that there is a significant correlation between the layout structure of an urban road network and the residents’ utilization degree of public transportation. A greater betweenness centralization of the urban road network, namely a more centralized road network, means a higher frequency of per capita public transportation of urban residents and a higher degree of the residents’ utilization of public transportation. In the development of public transportation, centralized and axial-shaped layout structures of road networks can be promoted to improve the utilization of public transportation.

Influence Models of Urban Road Network Operation Performance Base on Spatial Autocorrelation Theory

2012 ◽  
Vol 253-255 ◽  
pp. 1922-1929
Author(s):  
Jian Cheng Weng ◽  
Wen Jie Zou ◽  
Jian Rong
Keyword(s):  
Spatial Autocorrelation ◽  
Road Network ◽  
Road Networks ◽  
Operation Performance ◽  
Urban Road Network ◽  
Spatial Characteristics ◽  
Urban Road ◽  
The Road ◽  
Network Operation ◽  
The Impact

In order to better identify the spatial influence between adjacent parts of road networks, the paper introduces the spatial autocorrelation theory in evaluating the operation performance of urban road networks. The research proposes several spatial correlation validation indicators to verify the spatial characteristics among the road networks. Based on the analysis of spatial characteristics, the relationship between operation performance and influencing factors under the impact of spatial effect is examined. Furthermore, a spatial autocorrelation based influence models at three traffic flow levels is developed by using the data from a partial urban road network in Beijing. The model analysis shows that the spatial autocorrelation model is more effective in analyzing the urban road network operation performance under the influence of various factors. This model will be beneficial in identifying traffic network problems and improving traffic operations of the urban road network.

scholarly journals Urban Road Network Emergency: An Integrative Vulnerability Identification Method

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Huaikun Xiang
Keyword(s):  
Network Traffic ◽  
Road Network ◽  
Road Networks ◽  
Likelihood Method ◽  
Survey Method ◽  
Urban Road Network ◽  
Urban Road ◽  
The Road ◽  
Identification Method ◽  
The Impact

The vulnerability of an urban road network is affected by many factors, such as internal road network layout, network structure strength, and external destructive events, which have great uncertainty and complexity. Thus, there is still no unified and definite vulnerability analysis scheme available to cities. This paper proposes an integrative vulnerability identification method for urban road networks, which mainly relates to the vulnerability connotation and characteristics analysis of urban road networks during emergency, and vulnerability comprehensive evaluation indices design based on urban road network connectivity, traffic efficiency and performance, and an empirical study on a vulnerability identification method of an urban road network. In the empirical case, a real road network and traffic operation data were used from Science and Technology Park of Shenzhen City, China. In the context of one certain emergency scenario, the stated preference survey method and maximum likelihood method are used to solve the road users’ random travel choice behavior parameters; subsequently, based on the traffic equilibrium distribution prediction, the traffic vulnerability identification methods of the road network in this region were verified before and after the emergency. The method presented here not only considers the impact of network topology changes on road network traffic function during emergency but also considers the impact of dynamic changes in road network traffic demand on vulnerability; therefore, it is closer to the actual distribution of urban road network traffic vulnerability.

scholarly journals Mining Topological Dependencies of Recurrent Congestion in Road Networks

2021 ◽  
Vol 10 (4) ◽  
pp. 248
Author(s):  
Nicolas Tempelmeier ◽  
Udo Feuerhake ◽  
Oskar Wage ◽  
Elena Demidova
Keyword(s):  
Network Topology ◽  
Real World ◽  
Public Transportation ◽  
Road Network ◽  
Road Networks ◽  
Traffic Load ◽  
Data Mining Algorithm ◽  
Urban Road ◽  
The Road ◽  
Spatio Temporal

The discovery of spatio-temporal dependencies within urban road networks that cause Recurrent Congestion (RC) patterns is crucial for numerous real-world applications, including urban planning and the scheduling of public transportation services. While most existing studies investigate temporal patterns of RC phenomena, the influence of the road network topology on RC is often overlooked. This article proposes the ST-Discovery algorithm, a novel unsupervised spatio-temporal data mining algorithm that facilitates effective data-driven discovery of RC dependencies induced by the road network topology using real-world traffic data. We factor out regularly reoccurring traffic phenomena, such as rush hours, mainly induced by the daytime, by modelling and systematically exploiting temporal traffic load outliers. We present an algorithm that first constructs connected subgraphs of the road network based on the traffic speed outliers. Second, the algorithm identifies pairs of subgraphs that indicate spatio-temporal correlations in their traffic load behaviour to identify topological dependencies within the road network. Finally, we rank the identified subgraph pairs based on the dependency score determined by our algorithm. Our experimental results demonstrate that ST-Discovery can effectively reveal topological dependencies in urban road networks.

scholarly journals Critical Segments Identification for Link Travel Speed Prediction in Urban Road Network

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Xiaolei Ru ◽  
Xiangdong Xu ◽  
Yang Zhou ◽  
Chao Yang
Keyword(s):  
Information Acquisition ◽  
Prediction Accuracy ◽  
Road Network ◽  
Large Scale ◽  
Road Networks ◽  
Route Planning ◽  
Travel Speed ◽  
Traffic Information ◽  
Operational Conditions ◽  
The Road

Predicting traffic operational condition is crucial to urban transportation planning and management. A large variety of algorithms were proposed to improve the prediction accuracy. However, these studies were mainly based on complete data and did not discuss the vulnerability of massive data missing. And applications of these algorithms were in high-cost under the constraints of high quality of traffic data collecting in real-time on the large-scale road networks. This paper aims to deduce the traffic operational conditions of the road network with a small number of critical segments based on taxi GPS data in Xi’an city of China. To identify these critical segments, we assume that the states of floating cars within different road segments are correlative and mutually representative and design a heuristic algorithm utilizing the attention mechanism embedding in the graph neural network (GNN). The results show that the designed model achieves a high accuracy compared to the conventional method using only two critical segments which account for 2.7% in the road networks. The proposed method is cost-efficient which generates the critical segments scheme that reduces the cost of traffic information collection greatly and is more sensible without the demand for extremely high prediction accuracy. Our research has a guiding significance on cost saving of various information acquisition techniques such as route planning of floating car or sensors layout.

scholarly journals Role of Traffic Emission on Temporal and Spatial Characteristics of Pollutant Concentration on Urban Road Network: A Case of Beijing

2020 ◽  
Vol 2020 ◽  
pp. 1-21
Author(s):  
Zirui Wang ◽  
Huixin Zhou ◽  
Yang Si ◽  
Yahui Li
Keyword(s):  
Road Network ◽  
External Input ◽  
Traffic Emission ◽  
Urban Road ◽  
The Road ◽  
Temporal And Spatial ◽  
On The Road ◽  
Temporal And Spatial Characteristics ◽  
The Impact ◽  
Pm2.5 Concentration

This research aims to calculate PM2.5 concentration on the road network by considering the network-wide traffic status, which can be used to support research about the impact of urban road network pollution concentration on health. The increase in the use and number of vehicles has brought about a large amount of vehicle exhaust emissions and increased urban air pollutants. This is also one of the important reasons why this issue is worth studying. In this research, traffic emission was an estimate based on network-wide traffic status which was calculated from vehicle trajectories and spatial variance-covariance matrix. An identification method of external input pollutants is proposed to determine the occurrence of external pollutants imported into the urban area. To calculate the impact of multiple influencing factors on the pollution concentration of the entire road network, a multivariate linear model was adopted to calculate a variety of influencing factors and calibrate the model parameters by collecting real data. The results show that traffic emissions, external input pollution, and wind impact are the main factors affecting the PM2.5 concentration on urban road networks. Combined with real-time traffic data, we can obtain the temporal and spatial characteristics of the pollutant concentration of the road network. For policymakers, our research can provide a method for calculating the PM2.5 concentration on the road network, which is useful for establishing a health assessment framework in the future.

scholarly journals Research on Urban Ecological Network Under the Threat of Road Networks—A Case Study of Wuhan

2019 ◽  
Vol 8 (8) ◽  
pp. 342 ◽  
Author(s):  
Miao ◽  
Pan ◽  
Wang ◽  
Chen ◽  
Yan ◽  
...  
Keyword(s):  
Road Network ◽  
Road Networks ◽  
Spatial Pattern Analysis ◽  
Analysis Method ◽  
Ecological Network ◽  
Ecological Processes ◽  
The Road ◽  
Type Assignment ◽  
Ecological Habitat ◽  
The Impact

The creation of a road network can lead to the fragmentation and reduction of the connectivity of the ecological habitat. The study of urban ecological networks under threat from rapidly developing road networks is of great significance in understanding the changes in urban ecological processes and in constructing a reasonable ecological network. Spatial syntax is a linear space analysis method based on graph theory. Taking Wuhan city as an example and adopting spatial syntax to quantify road network threat factors, two resistance surfaces are established based on land use type assignment and overlapping road network threat factor assignment. The ecological environment under two scenarios is constructed by combining the MSPA (Morphological Spatial Pattern Analysis) method and MCR (Minimal Cumulative Resistance) model to comprehensively evaluate the network. Results demonstrate that spatial syntax can effectively describe the spatial characteristics of the road network. The average resistance value of the study area increases by 15.94%, the length of corridor increases by 37.9 km, the energy consumption of biological and material exchanges increases, and the resistance increases. To a certain extent, the model reflects the impact of road network threats on ecological processes. The results are useful in identifying the impact of human activities on ecological processes and provide a reference point for the construction of urban ecological security patterns.

scholarly journals A modified multilevel k-way partitioning algorithm for trip-based road networks

2019 ◽  
Vol 272 ◽  
pp. 01038
Author(s):  
C Withanage ◽  
D Lakmal ◽  
M Hansini ◽  
K Kankanamge ◽  
Y Witharanage ◽  
...  
Keyword(s):  
Urban Areas ◽  
Road Network ◽  
Road Networks ◽  
Optimal Number ◽  
Network Partitioning ◽  
Network Graph ◽  
Urban Road ◽  
The Road ◽  
Partitioning Algorithm ◽  
Traffic Systems

In today’s world, the traffic volume on urban road networks is multiplying rapidly due to the heavy usage of vehicles and mobility on demand services. Migration of people towards urban areas result in increasing size and complexity of urban road networks. When handling such complex traffic systems, partitioning the road network into multiple sub-regions and managing the identified sub regions is a popular approach. In this paper, we propose an algorithm to identify sub-regions of a road network that exhibit homogeneous traffic flow patterns. In a stage wise manner, we model the road network graph by using taxi-trip data obtained on the selected region. Then, we apply the proposed modified multilevel kway partitioning algorithm to obtain optimal number of partitions from the developed road graph. An interesting feature of this algorithm is, resulting partitions are geographically connected and consists minimal interpartition trip flow. Our results show that the proposed algorithm outperforms state-of-the-art multilevel partitioning algorithms for tripbased road networks. By this research, we demonstrate the ability of road network partitioning using trip data while preserving the partition homogeneity and connectivity.

scholarly journals The Evolution and Growth Patterns of the Road Network in a Medium-Sized Developing City: A Historical Investigation of Changchun, China, from 1912 to 2017

2019 ◽  
Vol 11 (19) ◽  
pp. 5307 ◽  
Author(s):  
Shiguang Wang ◽  
Dexin Yu ◽  
Mei-Po Kwan ◽  
Huxing Zhou ◽  
Yongxing Li ◽  
...  
Keyword(s):  
Road Network ◽  
Temporal Evolution ◽  
Road Networks ◽  
Small World ◽  
Growth Patterns ◽  
Data Availability ◽  
Urban Road ◽  
The Road ◽  
And Function ◽  
Over Time

Understanding the evolution and growth patterns of urban road networks helps to design an efficient and sustainable transport network. The paper proposed a general study framework and analytical workflow based on network theory that could be applied to almost any city to analyze the temporal evolution of road networks. The main tasks follow three steps: vector road network drawing, topology graph generation, and measure classification. Considering data availability and the limitations of existing studies, we took Changchun, China, a middle-sized developing city that is seldom reported in existing studies, as the study area. The research results of Changchun (1912–2017) show the road networks sprawled and densified over time, and the evolution patterns depend on the historical periods and urban planning modes. The evolution of network scales exhibits significant correlation; the population in the city is well correlated with the total road length and car ownership. Each network index also presents specific rules. All road networks are small-world networks, and the arterial roads have been consistent over time; however, the core area changes within the adjacent range but is generally far from the old city. More importantly, we found the correlation between structure and function of the urban road networks in terms of the temporal evolution. However, the temporal evolution pattern shows the correlation varies over time or planning modes, which had not been reported

scholarly journals Examining the Road Networks and Locations of Firefighting Teams by Using GIS Techniques

2020 ◽  
pp. 173-180
Author(s):  
Taş İnanç ◽  
Akay Abdullah E.
Keyword(s):  
Response Time ◽  
Forest Fires ◽  
Road Network ◽  
Road Networks ◽  
Travel Speed ◽  
Effective Response ◽  
Critical Response ◽  
The Road ◽  
Gis Techniques ◽  
Optimum Route

For effective response to forest fires, the period of time necessary for the firefighting team to reach the fire site should not exceed the critical response time, where the fire is more likely to be taken under control. For this reason, the optimum route that allows the team to reach the fire site by a fire truck within the shortest time possible should be determined. Computer-aided methods such as the road network analysis are widely used in the solution of such transportation problems that require the shortest path analysis. In this study, the locations of the existing road networks and firefighting team were examined using GIS techniques in order to determine the optimum route that will provide the promptest access to the fire site. The study was carried out in the Adana Forest Enterprise Directorate, where first degree fire-sensitive forests are located. There are three firefighting teams located in the boundaries of the study area. The sites in the study area where previously occurred forest fires (15), which burned 1 ha or more forest areas, were evaluated as potential fire sites. The analysis results showed that 64,12% of the forest areas in the study area was reached by the firefighting teams within 20 minutes, which is the critical response time for first degree fire sensitive forests. It was found that the teams could reach 12 potential fire sites within the critical response time. This result revealed the necessity to establish new firefighting teams in the study area. In addition, it is thought that improving the road network density in the study area by building new roads or increasing the truck travel speed by improving the conditions of existing roads will help to solve the problem.

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