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:
  Accuracy Algorithms Automatic Vehicle Classification Data Collection Errors
• 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.
  
  
• Format:
  PDF
• Funding:
  ODOT SP&R Item Number 2250
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha256:159f569ae47e2bd9de6022f132d85c8fb5e4ed9536925ad771ddba89d1bbf143
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/29303/dot_29303_DS1.pdf
• File Type:
  [PDF - 2.68 MB ]