Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/92558
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Electrical Engineering | - |
dc.creator | Shirke, C | - |
dc.creator | Sabar, N | - |
dc.creator | Chung, E | - |
dc.creator | Bhaskar, A | - |
dc.date.accessioned | 2022-04-26T06:00:39Z | - |
dc.date.available | 2022-04-26T06:00:39Z | - |
dc.identifier.issn | 1547-2450 | - |
dc.identifier.uri | http://hdl.handle.net/10397/92558 | - |
dc.language.iso | en | en_US |
dc.publisher | Taylor & Francis | en_US |
dc.rights | © 2021 Taylor & Francis Group, LLC | en_US |
dc.rights | This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Intelligent Transportation Systems: Technology, Planning, and Operations on 3 Feb 2021 (Published online), available online: http://www.tandfonline.com/10.1080/15472450.2021.1878892 | en_US |
dc.subject | Day to day variation | en_US |
dc.subject | Fixed time traffic signals | en_US |
dc.subject | Metaheuristic approach | en_US |
dc.subject | Robust traffic signal | en_US |
dc.subject | Varying traffic demand | en_US |
dc.title | Metaheuristic approach for designing robust traffic signal timings to effectively serve varying traffic demand | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 343 | - |
dc.identifier.epage | 355 | - |
dc.identifier.volume | 26 | - |
dc.identifier.issue | 3 | - |
dc.identifier.doi | 10.1080/15472450.2021.1878892 | - |
dcterms.abstract | Traffic demands at intersections vary across various periods of a day and from day to day. Generally, fixed time traffic signals are designed considering the average traffic flows across multiple days over a predetermined time interval. This approach overlooks the day to day variability in traffic demand, leading to inefficient and unreliable signal control performance. A signal plan should be robust such that it is less sensitive to demand variations and can maintain near-optimal performance during varying traffic demand. To address this need, the paper presents a new offline scenario-based framework, named Metaheuristic Robust plan Approach (MHRA), that identifies a robust plan for fixed time signals. MHRA includes a heuristic that considers optimum signal plan for various demand scenarios and corresponding costs to find a robust solution. The numerical experiments are performed using realistic traffic demand scenarios on an arterial corridor to verify the MHRA framework. The outcomes concluded that the framework produces a robust signal plan that outperforms a nominal signal plan based on average traffic demand and maintains stable performance under varying demand. Benchmarking MHRA with other scenario-based approaches proposed in the literature such as mean-variance optimization and conditional value at risk minimization confirms better efficiency for MHRA. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Journal of intelligent transportation systems : technology, planning, and operations, 2022, v. 26, no. 3, p. 343-355 | - |
dcterms.isPartOf | Journal of intelligent transportation systems : technology, planning, and operations | - |
dcterms.issued | 2022 | - |
dc.identifier.scopus | 2-s2.0-85100576771 | - |
dc.identifier.eissn | 1547-2442 | - |
dc.description.validate | 202204 bcrc | - |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | a1265 | en_US |
dc.identifier.SubFormID | 44401 | en_US |
dc.description.fundingSource | Self-funded | en_US |
dc.description.pubStatus | Published | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Shirke_Metaheuristic_Robust_Traffic.pdf | Pre-Published version | 1.3 MB | Adobe PDF | View/Open |
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