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.
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Supplemental Notes:
- Publication Date: 2001. Pergamon, Oxford
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Corporate Authors:
Universitat Stuttgart. Institut fur Strassen und Verkehrswesen
,Volkswagenwerk
,Technische Universitat Branuschweig
,Universitat der Bundeswehr Munchen
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Authors:
- Ou, Haitao
- Yang, Yupu
- Zhang, Wenyuan
- Xu, Xiaoming
- Publication Date: 2001
Language
- English
Media Info
- Pagination: p. 567-572
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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