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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Apinya Ngaosai | en_US |
dc.contributor.author | Jakarin Chawachat | en_US |
dc.date.accessioned | 2019-03-18T02:22:08Z | - |
dc.date.available | 2019-03-18T02:22:08Z | - |
dc.date.issued | 2019-01-18 | en_US |
dc.identifier.other | 2-s2.0-85062228273 | en_US |
dc.identifier.other | 10.1109/ECTICon.2018.8620034 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85062228273&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/63624 | - |
dc.description.abstract | © 2018 IEEE Urban streets are characterized by continuous intersections. When there are traffic jams, wide areas are affected. Among many attempts to solve this problem, one is Traffic Signal Management. Our approach focuses on traffic signal control for consecutive intersections. First, we transform intersections to a flow network and modify density of streets to capacity in a flow network. Then, we calculate a maximum flow. After that, we calculate the flow which passes outbound streets of each inbound street and set how long a green light signal turn on at each inbound street. After many experiments, when at least half of inbound streets are high-density, we found that using our approach results in higher traffic flow than fixed-time and video processing approach. | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Engineering | en_US |
dc.subject | Mathematics | en_US |
dc.subject | Physics and Astronomy | en_US |
dc.title | Traffic signal management using maximum flow approach for consecutive intersections | en_US |
dc.type | Conference Proceeding | en_US |
article.title.sourcetitle | ECTI-CON 2018 - 15th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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