Integration of Weigh-in-Motion and Inductive Signature Technology for Advanced Truck Monitoring

Trucks have a significant impact on infrastructure, traffic congestion, energy consumption, pollution and quality of life. To better understand truck characteristics, comprehensive high resolution truck data is needed. Higher quality truck data can enable more accurate estimates of greenhouse gases (GHGs) and emissions, allow for better management of infrastructure, provide insight to truck travel behavior, and enhance freight forecasting. Currently, truck traffic data is collected through limited means and with limited detail. Agencies can obtain or estimate truck travel statistics from surveys, inductive loop detectors (ILD) and weigh-in-motion (WIM) stations, or from manual counts, each of which have various limitations. Of these sources, WIM and ILD seem to be the most promising tools for capturing detailed truck information. Axle spacing and weight from existing WIM devices and unique inductive signatures indicative of body type from ILDs equipped with high sampling rate detector cards are complementary data sources that can be integrated to provide a synergistic resource that otherwise does not exist in practice, a resource that is able to overcome the drawbacks of the traditional truck data collection methods by providing data that is detailed, link specific, temporally continuous, up-to-date, and representative of the full truck population. This integrated data resource lends itself very readily toward detailed truck body classification which is presented as a case study. This body classification model is able to predict 35 different trailer body types for Federal Highway Administration class 9 semi-tractors, achieving an 80 percent correct classification rate. In addition to the body classification model, the large data set resulting from the case study is itself a valuable and novel resource for truck studies.

  • Record URL:
  • Supplemental Notes:
    • Submitted to ABJ35 Committee on Highway Traffic Monitoring for publication and presentation at the Transportation Research Board 93rd Annual Meeting and Transportation Research Record.
  • Corporate Authors:

    University of California, Irvine

    Civil and Environmental Engineering
    Institute of Transportation Studies
    Irvine, CA  United States  92697
  • Authors:
    • Hernandez, Sarah
    • Tok, Andre
    • Ritchie, Stephen G
  • Publication Date: 2013-8

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; Maps; Photos; References; Tables;
  • Pagination: 17p

Subject/Index Terms

Filing Info

  • Accession Number: 01491363
  • Record Type: Publication
  • Report/Paper Numbers: UCI-ITS-WP-13-3
  • Files: TRIS
  • Created Date: Aug 20 2013 2:26PM