A PATTERN RECOGNITION APPROACH TO DATA FUSION IN INTELLIGENT VEHICLE HIGHWAY SYSTEMS

This dissertation explores the use of pattern recognition and artificial intelligence techniques in Intelligent Transportation Systems (ITS). Two areas receive focus: 1) traffic congestion data fusion, and 2) travel time data fusion and estimation. Fuzzy logic is shown to be useful in fusing uncertain traffic congestion data. A counterpropagation neural network is used for travel time data fusion.

• Supplemental Notes:
  • Publication Date: 1995 UMI Company, Ann Arbor MI Remarks: Thesis (Ph. D. in Electrical Engineering and Computer Science)--University of Illinois at Chicago
• Corporate Authors:

  University of Illinois, Chicago

  P.O. Box 4348
  Chicago, IL  United States  60680
• Authors:
  • Palacharla, Prasad V
• Publication Date: 1995

Language

• English

Media Info

• Pagination: xii, 78 p.

Subject/Index Terms

• TRT Terms: Data fusion; Pattern recognition systems
• Subject Areas: Data and Information Technology;

Filing Info

• Accession Number: 00783510
• Record Type: Publication
• Source Agency: UC Berkeley Transportation Library
• Files: PATH
• Created Date: Feb 16 2000 12:00AM