Automatic Vehicle Classification for WIM Systems

Automatic weigh-in-motion (WIM) systems require a unique classification of vehicle type and chassis characteristics. In this paper, the author presents a novel method of automatic vehicle classification called ALT (ALTernative). ALT's characteristic feature is its open structure, which allows users to adjust the number of vehicles category according to individual needs. Data fusion methods and fuzzy sets are used by this system, which is compared with other axle-based classification schemes in this study. Test results found ALT's classification to be highly effective while retaining high selectivity of division. The effectiveness of classification of all vehicles was 95% and 100% for goods trucks. One drawback of the ALT method may be that it requires accurate measurement of vehicle axle spacing and length.

Language

  • English

Media Info

  • Media Type: Print
  • Features: Figures; References; Tables;
  • Pagination: pp 22-32
  • Monograph Title: Proceedings of the International Conference on Weigh-In-Motion (ICWIM 6)

Subject/Index Terms

Filing Info

  • Accession Number: 01496971
  • Record Type: Publication
  • ISBN: 9781848214156
  • Files: TRIS
  • Created Date: Oct 18 2013 11:18AM