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Publication: IIP Proceedings Year: 2022, Month: November Page No: 278-285, ISSN/ISBN: 978-81-959356-3-5, DOI/Link: https://rsquarel.org/assets/docupload/rsl202313952F861CD01F7.pdf
OPTIMIZATION OF TRAFFIC SIGNALS FOR INTELLIGENT TRAFFIC LIGHT MANAGEMENT SYSTEM
Area/Stream: Computing Technologies and Data Sciences, Authors: Sayantan Kar Keywords: Traffic signals, light management Book Name /series: Futuristic Trends in Computing Technologies and Data Sciences,Volume 2, Book 18, Part 5, Chapter 3Publication: IIP Proceedings Year: 2022, Month: November Page No: 278-285, ISSN/ISBN: 978-81-959356-3-5, DOI/Link: https://rsquarel.org/assets/docupload/rsl202313952F861CD01F7.pdf
Abstract:
The National Highway (N.H) 44 is one of the longest and widest highways in India, where it starts from Srinagar & terminates in Kanyakumari; the highway passes from UT and various states like Punjab, Haryana to Tamil Nadu. Road accidents occur every day, every minute due to heavy traffic congestion. Traffic signals at N.H 44 follow the fixed time signal technique, which have fixed time of red, yellow and green signal on different lanes in a sequential order. Also, no privilege is given to emergency vehicle like fire brigade; ambulance; police vans etc., waiting time will be high. Traffic light controllers are very useful for handling traffic at intersections. But fixed timer controllers are having limitations like even if no vehicle is existing, still green signal remain active on empty path. To automate the task of traffic light controllers, various artificial intelligence-based techniques has been used by different authors like fuzzy logic, genetic algorithms, neural network, reinforcement learning etc. These techniques provide variable timing signals based upon traffic condition. In this paper, a comparative analysis of various green signal optimization techniques has been discussed.
Cite this: Sayantan Kar,"OPTIMIZATION OF TRAFFIC SIGNALS FOR INTELLIGENT TRAFFIC LIGHT MANAGEMENT SYSTEM", Futuristic Trends in Computing Technologies and Data Sciences,Volume 2, Book 18, Part 5, Chapter 3, November, 2022, 278-285, 978-81-959356-3-5, https://rsquarel.org/assets/docupload/rsl202313952F861CD01F7.pdf
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