A WAVE Based and Collaboration Driven Framework for Reduced Traffic Congestion in Smart Cities

Soufiene Djahel, Nafaa Jabeur, Farid Nait-Abdesselam, Thomas Wolstencroft

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


The fast emergence of autonomous vehicles promises a drastic change on how road traffic congestion is detected, controlled, and mitigated. To this end, we believe that it is beneficial to explore different ways of collaboration between autonomous vehicles, with the aid of modern road infrastructure, to optimize the commuters' travel time. We, therefore, propose in this paper a novel solution based on a multi-parties collaboration framework and built upon the WAVE standard to optimize the usage of the road network and lower commuters' travel time. Our solution, which is based on a Belief-Desire-Intention architecture, enables autonomous vehicles to opt for selfish or collaborative behaviors depending on their goals and current situations. The results obtained from our preliminary prototype under three representative road maps demonstrate the effectiveness of our approach in dealing with traffic congestion.

Original languageEnglish
Pages (from-to)251-261
Number of pages11
JournalIEEE Intelligent Transportation Systems Magazine
Issue number4
Publication statusPublished - 10 Mar 2020
Externally publishedYes


  • road traffic
  • traffic congestion
  • intelligent vehicles
  • collaboration
  • smart cities

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications


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