Reinforcement Learning Ramp Metering Based on Traffic Simulation Model with Desired Speed

Since generation of the traffic congestion in a highway brings about an efficiency fall of road operation as well as an increase in energy consumption and environmental pollution, various kinds of traffic control have been considered for easing traffic congestion until now. In this paper, reinforcement learning is introduced. By combining this model with a simulation model for describing the traffic flow behavior in the merging sections in highways, a novel reinforcement learning ramp metering is proposed. By numerical simulation experiments, this model showed that the effect of the proposed control measure is large in the highway.

Language

  • English

Media Info

  • Media Type: Web
  • Features: Figures; References; Tables;
  • Pagination: pp 3184-3189
  • Monograph Title: International Conference on Transportation Engineering 2009

Subject/Index Terms

Filing Info

  • Accession Number: 01534545
  • Record Type: Publication
  • ISBN: 9780784410394
  • Files: TRIS, ASCE
  • Created Date: Nov 12 2013 1:43PM