Statistical Characteristics and Community Analysis of Urban Road Networks

Urban road networks are typical complex systems, which are crucial to our society and economy. In this study, topological characteristics of a number of urban road networks purely based on physical roads rather than routes of vehicles or buses are investigated in order to discover underlying unique structural features, particularly compared to other types of transport networks. Based on these topological indices, correlations between topological indices and small-worldness of urban road networks are also explored. The finding shows that there is no significant small-worldness for urban road networks, which is apparently different from other transport networks. Following this, community detection of urban road networks is conducted. The results reveal that communities and hierarchy of urban road networks tend to follow a general nature rule.

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Spectral Bisection Community Detection Method for Urban Road Networks

10.23919/ccc52363.2021.9550318 ◽

2021 ◽

Author(s):

Lu Guo ◽

Ying Cui ◽

Haili Liang ◽

Zhao Zhou

Keyword(s):

Community Detection ◽

Detection Method ◽

Road Networks ◽

Urban Road

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Robustness Analysis of Urban Road Networks from Topological and Operational Perspectives

Mathematical Problems in Engineering ◽

10.1155/2020/5875803 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12 ◽

Cited By ~ 2

Author(s):

Wen-Long Shang ◽

Yanyan Chen ◽

Chengcheng Song ◽

Washington Y. Ochieng

Keyword(s):

Travel Demand ◽

Price Of Anarchy ◽

Robustness Analysis ◽

Road Networks ◽

User Equilibrium ◽

Topological Indices ◽

Complex Network Theory ◽

Urban Road ◽

The Relationship ◽

Important Nodes

This study comprehensively analyses the robustness of urban road networks through topological indices based on the complex network theory and operational indices based on traffic assignment theory: User Equilibrium (UE), System Optimum (SO), and Price of Anarchy (POA). Analysing topological indices may pin down the most important nodes for URNs from the perspective of connectivity, while more sophisticated operational indices are helpful to examine the importance of nodes for URNs by taking into account link capacity, travel demand, and drivers’ behaviour. The previous way is calculated in a static way, which reduces the computation times and increases the efficiency for quick assessment of the robustness of URNs, while the latter is in a dynamic way, namely, calculating is based on removal of individual nodes, although this way is more likely to capture realistic meanings but consumes huge amount of time. The efforts made in this study try to find the relationship between topological and operational indices so as to assist the assessment of robustness of URNs to local disruptions. Seven realistic urban road networks such as Sioux Falls and Anaheim are used as network examples, and results show that different indices reflect robustness characteristics of urban road networks from different ways, and rank correlations between any two indices are poor although small network such as Sioux Falls have better correlations than others.

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Model-based Identification, Estimation, and Control for Large-scale Urban Road Networks

2020 European Control Conference (ECC) ◽

10.23919/ecc51009.2020.9143995 ◽

2020 ◽

Author(s):

Isik Ilber Sirmatel ◽

Nikolas Geroliminis

Keyword(s):

Large Scale ◽

Road Networks ◽

Urban Road ◽

Model Based ◽

Estimation And Control ◽

And Control

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Exploring the Structural Fractality of Urban Road Networks by Different Representations

The Professional Geographer ◽

10.1080/00330124.2021.1871765 ◽

2021 ◽

pp. 1-15

Author(s):

Hong Zhang ◽

Peichao Gao ◽

Tian Lan ◽

Chengliang Liu

Keyword(s):

Road Networks ◽

Urban Road

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Zero Watermarking Algorithm for Vector Geographic Data Based on the Number of Neighboring Features

Symmetry ◽

10.3390/sym13020208 ◽

2021 ◽

Vol 13 (2) ◽

pp. 208

Author(s):

Qifei Zhou ◽

Changqing Zhu ◽

Na Ren ◽

Weitong Chen ◽

Weiteng Gong

Keyword(s):

Second Order ◽

Superior Performance ◽

Statistical Characteristics ◽

First Order ◽

Geographic Data ◽

Simulation Results ◽

Topological Characteristics ◽

Zero Watermarking ◽

Critical Challenge

Zero watermarking is an important part of copyright protection of vector geographic data. However, how to improve the robustness of zero watermarking is still a critical challenge, especially in resisting attacks with significant distortion. We proposed a zero watermarking method for vector geographic data based on the number of neighboring features. The method makes full use of spatial characteristics of vector geographic data, including topological characteristics and statistical characteristics. First, the number of first-order neighboring features (NFNF) and the number of second-order neighboring features (NSNF) of every feature in vector geographic data are counted. Then, the watermark bit is determined by the NFNF value, and the watermark index is determined by the NSNF value. Finally, combine the watermark bits and the watermark indices to construct a watermark. Experiments verify the theoretical achievements and good robustness of this method. Simulation results also demonstrate that the normalized coefficient of the method is always kept at 1.00 under the attacks that distort data significantly, which has the superior performance in comparison to other methods.

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