Zhao, F, Wu, J, Sun, H et al. (2 more authors) (2016) Population-driven Urban Road Evolution Dynamic Model. Networks and Spatial Economics, 16 (4). pp. 997-1018. ISSN 1566-113X
Abstract
In this paper, we propose a road evolution model by considering the interaction between population distribution and urban road network. In the model, new roads need to be constructed when new zones are built, and existing zones with higher population density have higher probability to connect with new roads. The relative neighborhood graph and a Fermat-Weber location problem are introduced as the connection mechanism to capture the characteristics of road evolution. The simulation experiment is conducted to demonstrate the effects of population on road evolution. Moreover, the topological attributes for the urban road network is evaluated using degree distribution, betweenness centrality, coverage, circuitness and treeness in the experiment. Simulation results show that the distribution of population in the city has a significant influence on the shape of road network, leading to a growing heterogeneous topology.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2015, Springer. This is an author produced version of a paper published in Networks and Spatial Economics. Uploaded in accordance with the publisher's self-archiving policy. The final publication is available at Springer via https://doi.org/10.1007/s11067-015-9308-4 |
Keywords: | Road evolution; Population distribution; Relative neighborhood; Fermat-Webber location problem |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Spatial Modelling and Dynamics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 28 Aug 2015 10:01 |
Last Modified: | 11 Apr 2017 13:58 |
Published Version: | https://doi.org/10.1007/s11067-015-9308-4 |
Status: | Published |
Publisher: | Springer Verlag |
Identification Number: | 10.1007/s11067-015-9308-4 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:89294 |