INTELLIGENT TRAFFIC MONITORING SYSTEM BASED ON NEURAL NETWORK THEORY AND IMAGE PROCESSING

To offer drivers a safe and comfortable environment and to ensure smooth traffic conditions, various monitoring equipment is used on roads. Easy access to information by operators in a central monitoring and control location is gained from image data via video technology distributed in a wide area. However, for operators to monitor numerous screens simultaneously and make precise judgments is difficult. Operator load is increased and complex emergency events can be missed. To solve these problems, the authors developed and applied a neural network to a traffic monitoring system with monitoring capabilities equal to operators and with greater ability to monitor a wide area in real time than operators. The system can judge traffic congestion in a manner equivalent to operators and can detect vehicles operating in the pre-determined speed range. This paper introduces the system and analyzes the results of actual working data.

  • Supplemental Notes:
    • Five volumes of papers and one volume of abstracts comprise the published set of conference materials.
  • Corporate Authors:

    VERTIS

    TORANOMOM 34 MORI BUILDING 1-25-5
    TORANOMON, MINATOKU, TOKYO 105  Japan 
  • Authors:
    • Arai, M
    • Otuki, A
    • Nakamura, K
    • Inoue, H
    • Satoh, Y
    • Kitamura, T
    • Kobayashi, Y
  • Conference:
  • Publication Date: 1995-11

Language

  • English

Media Info

  • Pagination: p. 170

Subject/Index Terms

Filing Info

  • Accession Number: 00719259
  • Record Type: Publication
  • Report/Paper Numbers: Volume 1
  • Files: TRIS
  • Created Date: Mar 5 1996 12:00AM