The study of vehicle classification equipment with solutions to improve accuracy in Oklahoma.

Details

• Creators:
  Refai, Hazem ; Bitar, Naim ; Schettler, Jesse ; Kalaa, Omar Al
• Corporate Creators:
  University of Oklahoma. School of Electrical and Computer Engineering
• Corporate Contributors:
  United States. Federal Highway Administration
• Subject/TRT Terms:
  • Data collection
  • Algorithms
  • Errors
  • Automatic vehicle classification
  • Accuracy
• Publication/ Report Number:
  FHWA-OK-14-17
• Resource Type:
  Tech Report
• Geographical Coverage:
  Oklahoma
• Corporate Publisher:
  Oklahoma. Dept. of Transportation. Materials and Research Division
• Abstract:
  The accuracy of vehicle counting and classification data is vital for appropriate future highway and road ; design, including determining pavement characteristics, eliminating traffic jams, and improving safety. ; Organizations relying on vehicle classifiers for data collection should be aware that systems can be ; affected by hardware and sensor malfunction, as well as the equipment’s implementation of classification ; scheme (i.e., algorithm). This report presents outcomes from an extensive statewide examination of ; vehicle misclassification at Oklahoma Department of Transportation (ODOT) AVC stations employing ; the PEEK Traffic ‘FHWA-USA’ classification algorithm. A ground truth system utilizing continuous ; video recordings was developed and utilized. Results from the rigorous investigation are reported herein. ; Also detailed in this report is a novel method for an improved classification algorithm designed to reduce ; the number of classification errors. Thirteen Gaussian distributions were employed to model axle spacing ; for each of the 13 FHWA vehicle types. Classifications obtained from video recordings and PEEK Traffic ; axle spacing measurements for a sample of 20,000 vehicles were recorded and analyzed to obtain 13 ; good-fit Gaussian distributions that correspond with each vehicle class. An optimization algorithm was ; then implemented to develop axle spacing thresholds for vehicles currently traveling Oklahoma’s ; highways and to minimize vehicle misclassification. The new scheme was then implemented in the PEEK ; Traffic automatic data record equipment and experimentally evaluated for accuracy. Results demonstrated ; its effectiveness in improving vehicle classifications and reducing persistent overall system errors ; characteristic of the ‘FHWA-USA’ Scheme. Analysis methodology detailed in this report will benefit ; organizations interested in improving vehicle classification and overall system accuracy.
  More +
• Format:
  PDF
• Funding:
  ODOT SP&R Item Number 2250
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/29303/dot_29303_DS1.pdf
• File Type:
  [PDF - 2.68 MB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha256:159f569ae47e2bd9de6022f132d85c8fb5e4ed9536925ad771ddba89d1bbf143