Evolvable traffic signal control for intersection congestion alleviation with enhanced particle swarm optimisation
Urban congestion in major cities of Malaysia is getting severe over decades with increasing active vehicles and travelling time on the road. Part of Intelligent Transportation Systems development involves advanced computation in traffic management to cope for the projecting congestion trend. This wo...
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| Format: | Proceedings |
| Language: | en en |
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IEEE
2017
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| Online Access: | https://eprints.ums.edu.my/id/eprint/31484/1/Evolvable%20traffic%20signal%20control%20for%20intersection%20congestion%20alleviation%20with%20enhanced%20particle%20swarm%20optimisation-ABSTRACT.pdf https://eprints.ums.edu.my/id/eprint/31484/2/Evolvable%20traffic%20signal%20control%20for%20intersection%20congestion%20alleviation%20with%20enhanced%20particle%20swarm%20optimisation.pdf https://eprints.ums.edu.my/id/eprint/31484/ https://ieeexplore.ieee.org/document/8239039 |
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| _version_ | 1831794613575221248 |
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| author | Helen Sin Ee Chuo Min Keng Tan Alex Chee Hoe Chong Renee Ka Yin Chin Kenneth Tze Kin Teo |
| author_facet | Helen Sin Ee Chuo Min Keng Tan Alex Chee Hoe Chong Renee Ka Yin Chin Kenneth Tze Kin Teo |
| author_sort | Helen Sin Ee Chuo |
| building | UMS Library |
| collection | Institutional Repository |
| content_provider | Universiti Malaysia Sabah |
| content_source | UMS Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Urban congestion in major cities of Malaysia is getting severe over decades with increasing active vehicles and travelling time on the road. Part of Intelligent Transportation Systems development involves advanced computation in traffic management to cope for the projecting congestion trend. This work simulates traffic system and develop an optimising algorithm to instruct the traffic signal timing plan. A multiple=intersection traffic system has been developed using probability and statistical model based on the real case traffic data collected from local traffic intersection. Enhanced particle swarm optimisation algorithm is developed to ensure result consistency with smaller variation. As a result, the algorithm suggested signal timing increases the average waiting time of non-congested directions by approximately 4.17% but reduces the queue length at congested junction significantly in order to even up the flow at intersections. |
| format | Proceedings |
| id | my.ums.eprints-31484 |
| institution | Universiti Malaysia Sabah |
| language | en en |
| publishDate | 2017 |
| publisher | IEEE |
| record_format | eprints |
| spelling | my.ums.eprints-314842021-12-22T07:12:44Z https://eprints.ums.edu.my/id/eprint/31484/ Evolvable traffic signal control for intersection congestion alleviation with enhanced particle swarm optimisation Helen Sin Ee Chuo Min Keng Tan Alex Chee Hoe Chong Renee Ka Yin Chin Kenneth Tze Kin Teo HE331-380 Traffic engineering. Roads and highways. Streets Urban congestion in major cities of Malaysia is getting severe over decades with increasing active vehicles and travelling time on the road. Part of Intelligent Transportation Systems development involves advanced computation in traffic management to cope for the projecting congestion trend. This work simulates traffic system and develop an optimising algorithm to instruct the traffic signal timing plan. A multiple=intersection traffic system has been developed using probability and statistical model based on the real case traffic data collected from local traffic intersection. Enhanced particle swarm optimisation algorithm is developed to ensure result consistency with smaller variation. As a result, the algorithm suggested signal timing increases the average waiting time of non-congested directions by approximately 4.17% but reduces the queue length at congested junction significantly in order to even up the flow at intersections. IEEE 2017-12-22 Proceedings PeerReviewed text en https://eprints.ums.edu.my/id/eprint/31484/1/Evolvable%20traffic%20signal%20control%20for%20intersection%20congestion%20alleviation%20with%20enhanced%20particle%20swarm%20optimisation-ABSTRACT.pdf text en https://eprints.ums.edu.my/id/eprint/31484/2/Evolvable%20traffic%20signal%20control%20for%20intersection%20congestion%20alleviation%20with%20enhanced%20particle%20swarm%20optimisation.pdf Helen Sin Ee Chuo and Min Keng Tan and Alex Chee Hoe Chong and Renee Ka Yin Chin and Kenneth Tze Kin Teo (2017) Evolvable traffic signal control for intersection congestion alleviation with enhanced particle swarm optimisation. https://ieeexplore.ieee.org/document/8239039 |
| spellingShingle | HE331-380 Traffic engineering. Roads and highways. Streets Helen Sin Ee Chuo Min Keng Tan Alex Chee Hoe Chong Renee Ka Yin Chin Kenneth Tze Kin Teo Evolvable traffic signal control for intersection congestion alleviation with enhanced particle swarm optimisation |
| title | Evolvable traffic signal control for intersection congestion alleviation with enhanced particle swarm optimisation |
| title_full | Evolvable traffic signal control for intersection congestion alleviation with enhanced particle swarm optimisation |
| title_fullStr | Evolvable traffic signal control for intersection congestion alleviation with enhanced particle swarm optimisation |
| title_full_unstemmed | Evolvable traffic signal control for intersection congestion alleviation with enhanced particle swarm optimisation |
| title_short | Evolvable traffic signal control for intersection congestion alleviation with enhanced particle swarm optimisation |
| title_sort | evolvable traffic signal control for intersection congestion alleviation with enhanced particle swarm optimisation |
| topic | HE331-380 Traffic engineering. Roads and highways. Streets |
| url | https://eprints.ums.edu.my/id/eprint/31484/1/Evolvable%20traffic%20signal%20control%20for%20intersection%20congestion%20alleviation%20with%20enhanced%20particle%20swarm%20optimisation-ABSTRACT.pdf https://eprints.ums.edu.my/id/eprint/31484/2/Evolvable%20traffic%20signal%20control%20for%20intersection%20congestion%20alleviation%20with%20enhanced%20particle%20swarm%20optimisation.pdf https://eprints.ums.edu.my/id/eprint/31484/ https://ieeexplore.ieee.org/document/8239039 |
| url_provider | http://eprints.ums.edu.my/ |