Real-time traffic signal control for intersections based on dynamic O–D estimation and multi-objective optimisation: combined model and algorithm
Detectors are challenged in providing stable and accurate information of the dynamic origin–destination (O–D) flows for real-time adaptive traffic signal timing operation. However, the dynamic O–D estimation technique is capable of providing a short-term turn-flow data for the signal-timing adjustme...
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| Veröffentlicht in: | IET intelligent transport systems Jg. 12; H. 7; S. 619 - 630 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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The Institution of Engineering and Technology
01.09.2018
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| ISSN: | 1751-956X, 1751-9578 |
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| Abstract | Detectors are challenged in providing stable and accurate information of the dynamic origin–destination (O–D) flows for real-time adaptive traffic signal timing operation. However, the dynamic O–D estimation technique is capable of providing a short-term turn-flow data for the signal-timing adjustment. Meanwhile, the real-time signal timing variations will affect the dynamic O–D flows in an actual network. Therefore, the dynamic O–D estimation and the real-time signal control closely interact with each. A combined model is proposed to dynamically calculate the signal adjustment answering the variation of the real-time O–D flows by minimising the accumulative queues in entering approaches. A case study was conducted to validate the proposed model and algorithms, and the result showed the traffic efficiency of the case study intersection was improved. |
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| AbstractList | Detectors are challenged in providing stable and accurate information of the dynamic origin–destination (O–D) flows for real-time adaptive traffic signal timing operation. However, the dynamic O–D estimation technique is capable of providing a short-term turn-flow data for the signal-timing adjustment. Meanwhile, the real-time signal timing variations will affect the dynamic O–D flows in an actual network. Therefore, the dynamic O–D estimation and the real-time signal control closely interact with each. A combined model is proposed to dynamically calculate the signal adjustment answering the variation of the real-time O–D flows by minimising the accumulative queues in entering approaches. A case study was conducted to validate the proposed model and algorithms, and the result showed the traffic efficiency of the case study intersection was improved. |
| Author | Li, Dongyue Guo, Han Hou, Zenghao Li, Ruimin Jiao, Pengpeng Sun, Tuo |
| Author_xml | – sequence: 1 givenname: Pengpeng surname: Jiao fullname: Jiao, Pengpeng organization: 1Beijing Collaborative Innovation Center for Metropolitan Transportation, Beijing University of Civil Engineering and Architecture, Beijing 100044, People's Republic of China – sequence: 2 givenname: Tuo surname: Sun fullname: Sun, Tuo organization: 2Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, People's Republic of China – sequence: 3 givenname: Dongyue surname: Li fullname: Li, Dongyue organization: 3Beijing Urban Transportation Infrastructure Engineering Technology Research Center, Beijing University of Civil Engineering and Architecture, Beijing 100044, People's Republic of China – sequence: 4 givenname: Han surname: Guo fullname: Guo, Han organization: 3Beijing Urban Transportation Infrastructure Engineering Technology Research Center, Beijing University of Civil Engineering and Architecture, Beijing 100044, People's Republic of China – sequence: 5 givenname: Ruimin surname: Li fullname: Li, Ruimin email: lrmin@tsinghua.edu.cn organization: 4Institute of Transportation Engineering, Tsinghua University, Beijing 100084, People's Republic of China – sequence: 6 givenname: Zenghao surname: Hou fullname: Hou, Zenghao organization: 5Parsons Transportation Group, 100 Broadway, New York City 10005, USA |
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| CitedBy_id | crossref_primary_10_1016_j_trc_2025_105017 crossref_primary_10_1016_j_trc_2022_104007 crossref_primary_10_1049_itr2_12049 crossref_primary_10_1155_2021_6693636 crossref_primary_10_1049_iet_its_2018_5469 |
| Cites_doi | 10.1016/S0191-2615(98)00032-0 10.1016/j.trc.2009.06.005 10.1002/atr.1292 10.1016/j.trb.2008.03.005 10.3141/2128-11 10.1016/S0191-2615(96)00012-4 10.1016/0191-2615(87)90023-3 10.1002/atr.5670280305 10.1016/j.trc.2015.01.007 10.1016/0191-2615(87)90013-0 10.1016/0191-2615(93)90003-S 10.1061/41123(383)24 10.1016/j.trc.2015.09.003 10.3141/2080-13 10.1080/15568310802091053 10.1109/ITSC.2011.6083114 10.1016/j.trpro.2015.09.070 10.1080/18128602.2011.619587 10.1287/trsc.23.2.77 |
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| Keywords | signal adjustment dynamic calculation real-time traffic signal control queueing theory dynamic O-D flows road traffic control signal processing dynamic O-D estimation technique traffic efficiency short-term turn-flow data real-time signal timing variations dynamic origin-destination flows accumulative queues minimisation minimisation multiobjective optimisation real-time adaptive traffic signal timing operation |
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| Snippet | Detectors are challenged in providing stable and accurate information of the dynamic origin–destination (O–D) flows for real-time adaptive traffic signal... Detectors are challenged in providing stable and accurate information of the dynamic origin–destination (O–D) flows for real‐time adaptive traffic signal... |
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| StartPage | 619 |
| SubjectTerms | accumulative queues minimisation dynamic origin‐destination flows dynamic O‐D estimation technique dynamic O‐D flows minimisation multiobjective optimisation queueing theory real‐time adaptive traffic signal timing operation real‐time signal timing variations real‐time traffic signal control road traffic control short‐term turn‐flow data signal adjustment dynamic calculation signal processing Special Section: Big Traffic Data Analysis and Mining traffic efficiency |
| Title | Real-time traffic signal control for intersections based on dynamic O–D estimation and multi-objective optimisation: combined model and algorithm |
| URI | http://digital-library.theiet.org/content/journals/10.1049/iet-its.2018.5308 https://onlinelibrary.wiley.com/doi/abs/10.1049%2Fiet-its.2018.5308 |
| Volume | 12 |
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