Dynamic local vehicular flow optimization using real-time traffic conditions at multiple road intersections

Sookyoung Lee, Mohamed Younis, Aiswarya Murali, Meejeong Lee

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


Dynamic management of vehicular traffic congestion to maximize throughput in urban areas has been drawing increased attention in recent years. For that purpose, a number of adaptive control algorithms have been proposed for individual traffic lights based on the in-flow rate. However, little attention has been given to the traffic throughput maximization problem considering real-time road conditions from multiple intersections. In this paper, we formulate such a problem as maximum integer multi-commodity flow by considering incoming vehicles that have different outgoing directions. Then, we propose a novel adaptive traffic light signal control algorithm which opts to maximize traffic flow through and reduce the waiting time of vehicles at an intersection. The proposed algorithm adjusts traffic light signal phases and durations depending on real-time road condition of local and neighboring intersections. Via SUMO simulation, we demonstrate the effectiveness of the proposed algorithm in terms of traffic throughput and average travel time.

Original languageEnglish
Article number8648386
Pages (from-to)28137-28157
Number of pages21
JournalIEEE Access
StatePublished - 2019

Bibliographical note

Publisher Copyright:
© 2019 IEEE.


  • Adaptive traffic light control
  • dynamic traffic management
  • k-commodity flow problem
  • traffic flow maximization


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