Sun, H., Qiao, F., Wang, Z. et al. (1 more author) (2020) A two-level identification model for selecting the coordination strategy for the urban arterial road based on fuzzy logic. International Journal of Simulation and Process Modelling, 14 (6). pp. 478-487. ISSN 1740-2123
Abstract
A novel model for identifying the traffic condition of urban arterial roadways is proposed in this paper to improve the operational efficiency and safety of the urban traffic arterial road system. During the identification process, fuzzy analytic hierarchy process and fuzzy integrated evaluation are employed to identify the traffic condition on the arterial road; according to the fuzzy logic scheme, a proper coordination strategy is then generated based on the resulting identification of each way of the artery. To verify the effectiveness of the proposed method, a numerical experiment is carried out by using the microscopic traffic simulation software VISSIM, where a traffic flow simulation system is generated according to the real-time traffic data. The comparison results show that the proposed model works well to fit with the actual operating condition of the arterial traffic and the proposed coordination strategy can provide a better performance for the traffic management.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 Inderscience. This is an author-produced version of a paper subsequently published in International Journal of Simulation and Process Modelling. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | traffic condition identification; coordination strategy; urban arterial road; fuzzy logic |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 17 Jun 2019 10:28 |
Last Modified: | 26 Mar 2021 01:38 |
Status: | Published |
Publisher: | Inderscience |
Refereed: | Yes |
Identification Number: | 10.1504/IJSPM.2019.106154 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:146922 |