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Vehicular traffic optimisation and even distribution using ant colony in smart city environment

  • Abdul Rehman
  • , Muhammad Mazhar Rathore
  • , Anand Paul
  • , Faisal Saeed
  • , Raja Wasim Ahmad
  • Kyungpook National University
  • COMSATS University Islamabad

Research output: Contribution to journalArticlepeer-review

47 Scopus citations

Abstract

For a few years, route optimisation and efficient traffic flow are a big challenge, especially in a current situation when 54.5% population is living in the urban environment all over the world. At peak hours, the traffic jams in urban areas are frequent. Lots of works have been done in finding the shortest path to optimise the route to the destination in minimum time. However, moving vehicles toward the shorter paths causes a severe traffic jam in the city. Therefore, in this study, the authors proposed a framework to enhance the efficiency of the ant colony optimisation (ACO) algorithm to optimise the vehicular traffic, i.e. named as smart traffic distribution ACO. It helps to optimise the route and city traffic efficiently while avoiding congestion in all circumstances using up-to-date city traffic data. Their proposed framework finds the optimal path in such a way that the traffic flow on each road remains normal. The detection of congestion on the road at an early stage and even distribution of traffic on all roads helps to achieve maximum flow, speed, and optimum density of the roads.

Original languageEnglish
Pages (from-to)594-601
Number of pages8
JournalIET Intelligent Transport Systems
Volume12
Issue number7
DOIs
StatePublished - 1 Sep 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

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