URBAN INTELLIGENT TRAFFIC SYSTEM BASED ON MULTI-AGENT

This paper describes multi-agent coordination in urban traffic control, focusing on coordinating the signal of adjacent intersections in order to minimize the waiting vehicle's queue in the network. With multi-agent coordination, the Recursive Modeling Method (RMM) is used to select rational actions by examining the decision of other agents in making a distributed multi-agent environment. The paper describes how decision making using RMM and Bayesian learning can be applied to urban traffic control.

• Supplemental Notes:
  • Publication Date: 2001. Pergamon, Oxford
• Corporate Authors:

  Universitat Stuttgart. Institut fur Strassen und Verkehrswesen

  ,    

  Volkswagenwerk

  ,    

  Technische Universitat Branuschweig

  ,    

  Universitat der Bundeswehr Munchen

  ,    
• Authors:
  • Ou, Haitao
  • Yang, Yupu
  • Zhang, Wenyuan
  • Xu, Xiaoming
• Publication Date: 2001

Language

• English

Media Info

• Pagination: p. 567-572
• Serial:
  • Control in transportation systems 2000 : a proceedings volume from the 9th IFAC Symposium, Braunschweig, Germany, 13-15 June 2000. Vol. 2
  • Publisher: Universitat Stuttgart. Institut fur Strassen und Verkehrswesen

Subject/Index Terms

• TRT Terms: Artificial intelligence; Traffic control; Traffic signals
• Subject Areas: Operations and Traffic Management;

Filing Info

• Accession Number: 00961211
• Record Type: Publication
• Source Agency: UC Berkeley Transportation Library
• Files: PATH
• Created Date: Aug 4 2003 12:00AM