Reinforcement learning agents for traffic signal control in oversaturated networks

Juan C. Medina, Rahim F. Benekohal

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

An application for traffic signal control using reinforcement learning agents was implemented for small traffic networks with volumes close to saturation. The state observed by the agents and the rewards included information from the intersection being controlled and also from adjacent intersections. Communication between neighboring agents resulted in emergent coordination between agents and ultimately in better handling of traffic. Lower average, maximum and minimum delay values were found for the two tested networks compared to optimal pre-timed settings. Trends indicate that if the minor intersecting streets are one way, increased organization and coordination of traffic are expected as the network size increases. There is potential for reinforcement learning agents in traffic control applications as they can provide control in real time with flexible timing settings. Further research is being conducted with variable volume, bigger networks, and adjusting the agents' parameters.

Original languageEnglish (US)
Title of host publicationT and DI Congress 2011
Subtitle of host publicationIntegrated Transportation and Development for a Better Tomorrow - Proceedings of the 1st Congress of the Transportation and Development Institute of ASCE
Pages132-141
Number of pages10
DOIs
StatePublished - May 2 2011
Event1st Congress of the Transportation and Development Institute of ASCE - Chicago, IL, United States
Duration: Mar 13 2011Mar 16 2011

Publication series

NameT and DI Congress 2011: Integrated Transportation and Development for a Better Tomorrow - Proceedings of the 1st Congress of the Transportation and Development Institute of ASCE

Other

Other1st Congress of the Transportation and Development Institute of ASCE
CountryUnited States
CityChicago, IL
Period3/13/113/16/11

Keywords

  • Traffic management
  • Traffic signals
  • Traffic volume

ASJC Scopus subject areas

  • Transportation
  • Geography, Planning and Development

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