AN URBAN FLOW MODEL INTEGRATING NEURAL NETWORKS

This paper presents a cooperation-based neural network traffic flow model. The model is built upon a cooperation of local neural networks, with each neural net being in charge of modeling the traffic flow on one single signalized link. Exchanges of information are established between each local neural net to yield traffic flow modeling on a junction. The model meets the requirements for being integrated into a real time adaptive urban traffic control system.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/0968090X
• Supplemental Notes:
  • Publication Date: October 1997
• Authors:
  • Ledoux, Corinne
• Publication Date: 1997

Language

• English

Media Info

• Pagination: p. 287-300
• Serial:
  • Transportation Research Part C: Emerging Technologies
  • Volume: 5
  • Issue Number: 5
  • Publisher: Elsevier
  • ISSN: 0968-090X
  • Serial URL: http://www.sciencedirect.com/science/journal/0968090X

Subject/Index Terms

• TRT Terms: Adaptive control; Neural networks; Traffic flow
• Subject Areas: Operations and Traffic Management;

Filing Info

• Accession Number: 00775910
• Record Type: Publication
• Source Agency: UC Berkeley Transportation Library
• Files: PATH
• Created Date: Nov 17 1999 12:00AM