Increasing Accuracy of Vehicle Speed Measurement in Congested Traffic over Dual-Loop Sensors

Classified vehicle counts are a critical measure for forecasting the health of the roadway infrastructure and for planning future improvements to the transportation network. Balancing the cost of data collection with the fidelity of the measurements, length-based vehicle classification is one of the most common techniques used to collect classified vehicle counts. Typically the length-based vehicle classification process uses a pair of detectors in a given lane to measure effective vehicle length. While the calculation is simple and seems well defined, this study demonstrates that small changes in the calculations can lead to large differences in performance during challenging conditions. In particular, most conventional calculations assume that acceleration can be ignored, which simply is not the case in congested traffic. As a result of this fact, many operating agencies are reluctant to deploy classification stations on roadways where traffic is frequently congested. This study examines six variations of the conventional vehicle length calculation and develops a seventh that also estimates constant acceleration. It then highlights two of these approaches that work well in extreme conditions on freeways for speeds down to 15 mph. This range should be sufficient for most applications. Then using empirically collected data the authors find that the extreme events were uncommon and even the conventional method did quite well in stop-and-go traffic since the slower traffic moves, the lower the flow during that period. In any event, the key to success is the use of well-tuned detectors.

• Record URL:
  http://www.purdue.edu/discoverypark/nextrans/assets/pdfs/066OY03%20Final%20Report%20and%20Technical%20Summary.pdf
• 
• Supplemental Notes:
  • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  NEXTRANS

  Purdue University
  3000 Kent Avenue
  Lafayette, IN  United States  47906-1075

  Research and Innovative Technology Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Coifman, Benjamin
  • Wu, Lan
  • Wei, Heng
• Publication Date: 2014-9-23

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Figures; References; Tables;
• Pagination: 39p

Subject/Index Terms

• TRT Terms: Acceleration (Mechanics); Data collection; Loop detectors; Traffic congestion; Traffic speed; Traffic speed measurement; Transportation planning; Vehicle classification; Vehicle length
• Subject Areas: Data and Information Technology; Highways; Planning and Forecasting; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01544559
• Record Type: Publication
• Report/Paper Numbers: NEXTRANS Project No. 066OY03
• Contract Numbers: DTRT07-G-005
• Files: UTC, TRIS, RITA, ATRI, USDOT
• Created Date: Nov 24 2014 3:28PM