Multiple Intersections Traffic Signal Timing Optimization with Genetic Algorithm

Simple item page
dc.contributor.authorY.K. Chin
dc.contributor.authorK.C. Yong
dc.contributor.authorN. Bolong
dc.contributor.authorS.S. Yang
dc.contributor.authorK.T.K. Teo
dc.date.accessioned2023-06-06T06:44:47Z
dc.date.available2023-06-06T06:44:47Z
dc.date.issued2011
dc.descriptionModelling, Simulation and Computing Laboratory School of Engineering and Information Technology Universiti Malaysia Sabah Kota Kinabalu, Malaysia msclab@ums.edu.my, ktkteo@ieee.org Keywords – Traffic Flow Control; Traffic Signal Timing Plan; Genetic Algorithm
dc.description.abstractTraffic congestion in the urban area occurs more frequent than the past due to rapidly increasing on road vehicle usage rates. It could seriously hinder the development of urban area if a well management system has not being established. These scenarios necessitate the development of advance traffic management systems to increase the performance of signalized intersection. Traffic signal timing management (TSTM) system which comprise of genetic algorithm based optimization is proposed. Using a proper TSTM system, network traffic flow can be improved with considerably less cost than other infrastructural improvements. The proposed genetic algorithm based optimization approach allows signal timing parameters such as offset, cycle time, green split and phase sequence to be optimized with objective of minimum delay and better traffic fluency. The proposed GATSTM system has the ability to handle and manage the dynamic changes of the traffic networks condition by calibrating the system parameters accordingly.
dc.identifier.urihttps://digitallibrary.peninsulacollege.edu.my/handle/123456789/331
dc.language.isoen
dc.titleMultiple Intersections Traffic Signal Timing Optimization with Genetic Algorithm
dc.typeArticle
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Chin Yit Kwong - Multiple Intersections Traffic Signal Timing Optimization with Genetic Algorithm.pdf
Size:
470.67 KB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
738 B
Format:
Item-specific license agreed to upon submission
Description:
Download
Collections
Article Writing