scholarly journals A Grade Identification Method of Critical Node in Urban Road Network Based on Multi-Attribute Evaluation Correction

2022 ◽  
Vol 12 (2) ◽  
pp. 813
Author(s):  
Chaofeng Liu ◽  
He Yin ◽  
Yixin Sun ◽  
Ling Wang ◽  
Xiaodong Guo
Keyword(s):  
Spatial Distribution ◽  
Road Network ◽  
Classification Method ◽  
Topsis Method ◽  
Network Nodes ◽  
Evaluation Indexes ◽  
Urban Road ◽  
The Road ◽  
Attribute Evaluation ◽  
Key Nodes

Accurately identifying the key nodes of the road network and focusing on its management and control is an important means to improve the robustness and invulnerability of the road network. In this paper, a classification and identification method of key nodes in urban road networks based on multi-attribute evaluation and modification was proposed. Firstly, the emergency function guarantee grade of road network nodes was divided by comprehensively considering the importance of road network nodes, the consequences of failure, and the degree of difficulty of recovery. The evaluation indexes were selected according to the local attributes, global attributes, and functional attributes of the road network topology. The spatial distribution patterns of the evaluation indexes of the nodes were analyzed. The dynamic classification method was used to cluster the attributes of the road network nodes, and the TOPSIS method was used to comprehensively evaluate the importance ranking of the road network nodes. Attribute clustering of road network nodes by dynamic classification method (DT) and the TOPSIS method was used to comprehensively evaluate the ranking of the importance of road network nodes. Then, combined with the modification of the comprehensive evaluation and ranking of the importance of the road network nodes, the emergency function support classification results of the road network nodes were obtained. Finally, the method was applied to the road network within the second Ring Road of Beijing. It was compared with the clustering method of self-organizing competitive neural networks. The results show that this method can identify the key nodes of the road network more accurately. The first-grade key nodes are all located at the more important intersections on expressways and trunk roads. The spatial distribution pattern shows a “center-edge” pattern, and the important traffic corridors of the road network show a “five vertical and five horizontal” pattern.

Make More Connections: Urban Traffic Flow Forecasting with Spatiotemporal Adaptive Gated Graph Convolution Network

2022 ◽  
Vol 13 (2) ◽  
pp. 1-25
Author(s):  
Bin Lu ◽  
Xiaoying Gan ◽  
Haiming Jin ◽  
Luoyi Fu ◽  
Xinbing Wang ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Road Network ◽  
Large Scale ◽  
Transportation Systems ◽  
Urban Traffic ◽  
Propagation Mechanism ◽  
Urban Road ◽  
The Road ◽  
Traffic Flow Forecasting ◽  
Gating Mechanism

Urban traffic flow forecasting is a critical issue in intelligent transportation systems. Due to the complexity and uncertainty of urban road conditions, how to capture the dynamic spatiotemporal correlation and make accurate predictions is very challenging. In most of existing works, urban road network is often modeled as a fixed graph based on local proximity. However, such modeling is not sufficient to describe the dynamics of the road network and capture the global contextual information. In this paper, we consider constructing the road network as a dynamic weighted graph through attention mechanism. Furthermore, we propose to seek both spatial neighbors and semantic neighbors to make more connections between road nodes. We propose a novel Spatiotemporal Adaptive Gated Graph Convolution Network ( STAG-GCN ) to predict traffic conditions for several time steps ahead. STAG-GCN mainly consists of two major components: (1) multivariate self-attention Temporal Convolution Network ( TCN ) is utilized to capture local and long-range temporal dependencies across recent, daily-periodic and weekly-periodic observations; (2) mix-hop AG-GCN extracts selective spatial and semantic dependencies within multi-layer stacking through adaptive graph gating mechanism and mix-hop propagation mechanism. The output of different components are weighted fused to generate the final prediction results. Extensive experiments on two real-world large scale urban traffic dataset have verified the effectiveness, and the multi-step forecasting performance of our proposed models outperforms the state-of-the-art baselines.

scholarly journals GIS-Based Urban Road Network Accessibility Modeling Using MLR, ANN and ANFIS Methods

2021 ◽  
Vol 22 (1) ◽  
pp. 15-28
Author(s):  
K. Sai Sahitya ◽  
Csrk Prasad
Keyword(s):  
Network Structure ◽  
Road Network ◽  
Structural Parameters ◽  
Transportation Network ◽  
Sustainable Transportation ◽  
Geographical Information ◽  
Urban Road Network ◽  
Inference System ◽  
Urban Road ◽  
The Road

Abstract 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.

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.

Spatial Analysis Based Urban Road Network Partition Method for Macroscopic Evaluation

2011 ◽  
Vol 97-98 ◽  
pp. 512-517
Author(s):  
Wen Jie Zou ◽  
Jian Cheng Weng ◽  
Jian Rong ◽  
Wei Zhou
Keyword(s):  
Spatial Analysis ◽  
Road Network ◽  
Urban Road Network ◽  
Network Partition ◽  
Urban Road ◽  
The Road ◽  
Network Operation ◽  
Partition Method ◽  
Operation Status

In order to improve the reliability of urban road network operation evaluation, the road network regional Partition methods were launched in this paper. The geographic grid was introduced first, and a 4-level road network model was defined. Then, the spatial analysis based urban road network division method was proposed by analyzing the characteristics of road network operation. This method can reflect the influence between adjacent regional units, and improve the reliability of urban road network division. Finally, this research took a certain area in Beijing as a case study, and divided the road network as several regional units. Macroscopic evaluation result shows that it is effective for scientifically describing the road network operation status.

The Application of Gray Relational Analysis Based on the OWA Operator in the Road Network Evaluation of Development Zone

2013 ◽  
Vol 409-410 ◽  
pp. 1287-1291
Author(s):  
De Hua Lin ◽  
Zhen Zhou Yuan
Keyword(s):  
Road Network ◽  
Comprehensive Evaluation ◽  
Evaluation Index System ◽  
Gray Relational Analysis ◽  
Owa Operator ◽  
Development Zone ◽  
Evaluation Indexes ◽  
The Road ◽  
Relational Analysis ◽  
Network Evaluation

The development zone, which consists of freight traffic mostly and a few part of passenger traffic, and which forms of area traffic flow in the internal zone, and which has the significant characteristic of external transport playing an important role, has the different road network evaluation with other general cities. This paper, connecting with the traffic planning characteristics, constructs highway network evaluation indexes of development zone both at the structural performance and the running quality of road network. Moreover, this article, on the basis of the analyses of the comprehensive evaluation methods and the characteristics of evaluation index system, creates the road network evaluation model of development zone that is the gray relational analysis based on the OWA operator to determine the combination weight using the AHP and Entropy as the basis methods. Finally, by the empirical research, it verifies the feasibility and scientific of the evaluation indexes and method.

Traffic Congestion Identification and Analysis of Urban Road Network Based on Granular Computing

2014 ◽  
Vol 641-642 ◽  
pp. 916-922 ◽  
Author(s):  
Chen Yao ◽  
Jiu Chun Gu ◽  
Qi Yang
Keyword(s):  
Rough Set ◽  
Traffic Congestion ◽  
Evaluation System ◽  
Road Network ◽  
Granular Computing ◽  
Rough Set Theory ◽  
Quotient Space ◽  
Urban Road Network ◽  
Evaluation Indexes ◽  
Urban Road

This paper proposes a generalized model based on the granular computing to recognize and analyze the traffic congestion of urban road network. Using the method of quotient space to reduce the attributes associating with traffic congestion, the identification of traffic congestion evaluation system is established including 3 first class indexes and second class indexes of 11. The weight of evaluation indexes are sorted by value in descending order, which are calculated based on rough set theory. In order to improve the efficiency of traffic congestion identification, the appropriate granular is determined by the model parameter μ. When μ is larger, the identification is more effective and the run time of model is longer conversely. Experiments show when the value of μ is between 0.8 and 0.98, the effect of traffic congestion identification is comprehensive optimal.

scholarly journals THE USE OF STATISTICAL MODELING TO ASSESS THE EFFECTIVENESS OF THE APPLICATION OF ADAPTIVE CONTROL AND RECONSTRUCTION OF THE ROAD NETWORK INTERSECTIONS

2021 ◽  
pp. 40-49
Author(s):  
Roman V. Andronov ◽  
◽  
Evgeny E. Leverents ◽  
Keyword(s):  
Statistical Modeling ◽  
Simulation Modeling ◽  
Traffic Management ◽  
Road Network ◽  
Economic Assessment ◽  
Adaptive Regulation ◽  
Network Nodes ◽  
The Road ◽  
Management Measures ◽  
The City

The article discusses the issues and results of the use of statistical modeling (one of the types of simulation modeling, the so-called "Monte Carlo" method), to assess the effectiveness of traffic management on the example of the Timofey Charkov st. and Verkhnetarmanskaya st. intersection, located in the city of Tyumen. The results are based on the length of the vehicle queue and traffic delay time for one car in the scenario of widening the intersection’s carriageway and/or the implementation of the adaptive regulation for traffic flows. The calculations were carried out in the "SmartAdaptive+" program developed by the authors, and designed for a technical and economic assessment of the effectiveness of traffic management measures and the use of adaptive regulation and measures to change the road network nodes configuration.

PEAK HOUR FACTOR AT URBAN ROAD NETWORK SYSTEM WITH FIXED HOURLY INTERVAL AND MOVING HOURLY INTERVAL (A CASE STUDY AT URBAN ROAD IN CIMAHI CITY)

2020 ◽  
Vol 6 (01) ◽  
pp. 29
Author(s):  
Hendra Hendrawan
Keyword(s):  
Urban Areas ◽  
Road Network ◽  
Resource Constraints ◽  
Important Variable ◽  
Network System ◽  
Urban Road Network ◽  
Hourly Interval ◽  
Urban Road ◽  
The Road

The Peak Hour Factor (PHF) is an important variable for determining road capacity. The value of PHF will vary greatly depending on location characteristics and classification of road functions. This study aims to obtain the estimated value of PHF in the urban road network system with variations in the classification of functions and types of roads. In addition this study also aims to obtain a method of approaching the PHF value near to fluctuations in traffic flow which has limited resources for surveys based on the duration specified in the traffic survey guidelines in Indonesia. The method used is descriptive statistical analysis and parametric test using Independent T sample test. The PHF is calculated based on Fixed Hourly Interval and Moving Hourly Interval and their inverse. The results of the study show the value of PHF in the road network system in urban areas for variations function and type of road that is in the range of 0.79 to 0.98 with an average of 0.91. Other findings show that the inverse method of Moving Hourly Interval can be used as an approach to obtain the PHF value under conditions of resource constraints

A MODEL FOR THE STUDY OF TRAFFIC FLOW ON THE UKRAINIAN CITIES ROAD NETWORK

2019 ◽  
pp. 30-33
Author(s):  
Liydmila Nagrebelna
Keyword(s):  
Traffic Flow ◽  
Road Network ◽  
Operating Conditions ◽  
Negative Effects ◽  
Efficient Operation ◽  
Urban Road ◽  
The Road ◽  
Effective Functioning ◽  
Organization And Management ◽  
The City

The problems of efficient functioning of the city road network are outlined. The method by which it is possible to improve the functioning of the street-road network of Ukrainian cities is presented. Improving the efficiency of the urban road network is to use all the resources of this network to create the necessary languages for its reliable and efficient operation and reduce the negative effects of motorization. It is proved that in order to ensure the effective functioning of the road network it is necessary to carry out a set of measures for the organization and management of traffic. The purpose of this article is to identify factors that affect the deterioration of operating conditions; identify the conditions for the effective functioning of the road network; the choice of a model for the effective functioning of the street-road network of Ukrainian cities is grounded. Because the management impact on traffic flow can be estimated on the basis of the developed models. Keywords: road network, efficient operation, methods, conditions.

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