Traffic Signal Coordination using Termite Spatial Correlation Optimization for Oversaturated Signals

Vishu Gupta, Avinash Sharma, Srikanth Reddy K, Rajesh Kumar, Bk Panigrahi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This article proposes a novel method for solving traffic signal coordination problem under over-saturated conditions. This problem is a large combinatorial optimization problem formulated as a dynamic optimization problem. The algorithm derives optimal green times for a network consisting of 20 interconnected signals using termite spatial correlation optimization (TSCO) algorithm. The algorithm tries to do so by incorporating proper queue dissipation along with maximizing number of vehicles precessed by the network in the congestion period. The resulted green times and fitness values have been compared with those derived using Genetic Algorithm (GA) and Ant Colony Optimization (ACO). TSCO is shown to outperform GA and ACO in terms of fitness value as well as overall function evaluations.

Original languageEnglish
Title of host publicationWIECON-ECE 2017 - IEEE International WIE Conference on Electrical and Computer Engineering 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages153-156
Number of pages4
ISBN (Electronic)9781538626214
DOIs
Publication statusPublished - 2 Jul 2017
Externally publishedYes
Event2017 IEEE International WIE Conference on Electrical and Computer Engineering, WIECON-ECE 2017 - Dehradun, India
Duration: 18 Dec 201719 Dec 2017

Publication series

NameWIECON-ECE 2017 - IEEE International WIE Conference on Electrical and Computer Engineering 2017

Conference

Conference2017 IEEE International WIE Conference on Electrical and Computer Engineering, WIECON-ECE 2017
Country/TerritoryIndia
CityDehradun
Period18/12/1719/12/17

Keywords

  • Ant Colony Optimization
  • Genetic Algorithm
  • Signal Coordination
  • Termite Spatial Correlation Algorithm

ASJC Scopus subject areas

  • Computer Science Applications
  • Hardware and Architecture
  • Electrical and Electronic Engineering
  • Computer Vision and Pattern Recognition
  • Signal Processing

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