Application of Complex Networks Theory in Urban Traffic Network Researches

Ding, Rui; Ujang, Norsidah; Hamid, Hussain; Manan, Mohd Shahrudin Abd; Li, Rong; Albadareen, Safwan Subhi Mousa; Nochian, Ashkan; Wu, Jianjun

doi:10.1007/s11067-019-09466-5

Cited by 101 publications

(57 citation statements)

References 182 publications

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“…The rudimentary concepts and content of complex network theory have already been thoroughly introduced in some previous articles [10,94], and its related applications in urban traffic have been fully discussed [15]. From these experiences and cognitions, we can clearly see that the applications of complex network theory in land-use and transport interaction have certain phases and characteristics ( Figure 1), and they were taken from graph theory and applied to land-use by Urban and Keitt [95].…”

Section: The Complex Network Theory-based Urban Land-use and Transpormentioning

confidence: 97%

“…In these reviews, the theoretical contexts for conceptual and existing empirical research of land-use and transportation have been discussed thoroughly, and most of the land-use and transport interaction (LUTI) models have been addressed. The complex network development processes, related theory, and research on urban traffic networks have been summarized by Ding, Ujang et al [15]. Hence, this article will emphasize and further discuss complex network theory in the context of land-use and transport interaction studies and applications.…”

Section: Introductionmentioning

confidence: 95%

“…For now, complex network theory concentrates on the following aspects: the empirical research of network characteristics [8]; network hub node detection [9]; network dynamics and spreading processes [10]; detection of communities and groups [11]; robustness and vulnerability [10,12]; and multiplex network theory and applications [13]. Research into complex networks provides us with a novel way to analyse complex urban systems [14,15]. The viewpoints of the small-world network and scale-free network changed the thinking of urban traffic networks: before these two models were proposed, traffic networks were normally approached as regular networks and ER random networks [16], as inherited from the definitions of graph theory.…”

Section: Introductionmentioning

confidence: 99%

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The Complex Network Theory‐Based Urban Land‐Use and Transport Interaction Studies

Ding

2019

Complexity

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The research on complex networks offers novel insight into the analysis of complex urban systems. The objective of this article is to provide a review of complex network theory in urban land-use and transport studies to date. Some traditional integrated studies of urban land-use and traffic networks are summarized and analysed; related research gaps were proposed. Then, this paper reviewed the application of complex network theory in urban land-use and transport research and practice. It shows that the node importance identification method is critical for network protection or attack studies; the multiple centrality assessment and kernel density estimation approaches can be used to represent the intuitionistic connections of urban traffic networks and surrounding land-uses; it can be used to verify the changing trend and variation of landscape connectivity; also it can be applied to the identification of key changed land-use types in land-use cover change; the coevolution process can be treated as an integrated way to discuss the relationships between urban traffic network growth and land-use change, and the multilayer networks based analysis is a novel method to measure their interactions. This paper is essential in establishing apparent research interests and points out the further potential application of complex network theory in urban traffic network and land-use related studies.

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Section: The Complex Network Theory-based Urban Land-use and Transpormentioning

confidence: 97%

Section: Introductionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

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The Complex Network Theory‐Based Urban Land‐Use and Transport Interaction Studies

Ding

2019

Complexity

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“…With the obtained estimates for β , they demonstrated that the estimated interaction flows coincide reasonably well with observed interaction flows, which argues for the effectiveness of the gravity model in determining spatial interactions of freight movements. Recently, Ding et al 33 reviewed the applications of complex network theory in urban traffic studies. Our study differs from theirs in terms of the activity space (i.e.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Regional Economic Development Indicator from Transportation Network Analytics

Gao

Liang

et al. 2020

Sci Rep

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With the booming economy in China, many researches have pointed out that the improvement of regional transportation infrastructure among other factors had an important effect on economic growth. Utilizing a large-scale dataset which includes 3.5 billion entry and exit records of vehicles along highways generated from toll collection systems, we attempt to establish the relevance of mid-distance land transport patterns to regional economic status through transportation network analyses. We apply standard measurements of complex networks to analyze the highway transportation networks. A set of traffic flow features are computed and correlated to the regional economic development indicator. The multi-linear regression models explain about 89% to 96% of the variation of cities' GDP across three provinces in China. We then fit gravity models using annual traffic volumes of cars, buses, and freight trucks between pairs of cities for each province separately as well as for the whole dataset. We find the temporal changes of distance-decay effects on spatial interactions between cities in transportation networks, which link to the economic development patterns of each province. We conclude that transportation big data reveal the status of regional economic development and contain valuable information of human mobility, production linkages, and logistics for regional management and planning. Our research offers insights into the investigation of regional economic development status using highway transportation big data. * This is a pre-print of an article submitted to Scientific Reports. The final authenticated version is available online at: https://doi.

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“…With the critical role of urban tra c networks in the urban economy, the characteristics and properties of urban tra c network topology have recently gained increasing attention [1][2][3][4][5][6][7][8][9][10][11][12]. Scholars have presented in-depth discussions of the process of tra c planning and design from the perspectives of network topology, tra c ow, tra c congestion, network evolution, cascade failure, and network optimization [13][14][15][16][17][18][19][20]. Nevertheless, few studies on optimal network topology consider which network structure can bear more tra c ow, how to achieve a more e cient network structure, or which network can have the greatest anticongestion ability.…”

Section: Introductionmentioning

confidence: 99%

Optimal Topology of Multilayer Urban Traffic Networks

et al. 2019

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Previous urban traffic network-based studies have been based mostly on single-layer networks. Based on their shortcomings, starting from the perspective of a multilayer urban traffic network, this paper takes the different anticongestion abilities and network characteristics of various network structures under the condition of traffic congestion as the research object. Then, a comparative experiment is performed via simulation, and the optimal multilayer urban traffic network topology is obtained under different conditions. It is found that these scale-free related multilayer networks have relatively strong ability to support more traffic flows and have higher anticongestion abilities, regardless of whether it is a lower-layer or upper-layer network. The research results are helpful to deepen our understanding of the characteristics of traffic network structures, help scholars further cognize the structural properties of multilayer urban traffic networks, practically help urban traffic network planners to further optimize the urban traffic network, and broaden the study of multilayer traffic networks.

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Application of Complex Networks Theory in Urban Traffic Network Researches

Cited by 101 publications

References 182 publications

The Complex Network Theory‐Based Urban Land‐Use and Transport Interaction Studies

The Complex Network Theory‐Based Urban Land‐Use and Transport Interaction Studies

Estimation of Regional Economic Development Indicator from Transportation Network Analytics

Optimal Topology of Multilayer Urban Traffic Networks

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