Performance of Smart Sensor Detectors for Stop-Bar Detection at Signalized Intersections

Recent years have seen increasing deployment of radar-based technologies for vehicle detection at signalized intersections in the United States, mainly because they are nonintrusive, accurate, and robust to varying lighting, weather, and environmental conditions. In this paper, a radar-based detection technology is evaluated in the context of various weather and environmental conditions. High-resolution (100-ms sampling interval) data were collected in the field from two representative test sites. The detection errors were correlated with varying weather and environmental conditions using data-mining techniques, such as conditional inference trees and regression models. It shown that false and stuck-on call errors tend to increase under more-adverse weather conditions (e.g., rain and thunderstorms). Visibility, glare, and uneven shadows appear to be irrelevant. The near-side mounting location is associated with reduced missed-call, false-call, and dropped-call errors.

• Record URL:
  https://doi.org/10.1061/JTEPBS.0000045
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/24732907
• Supplemental Notes:
  • © 2017 American Society of Civil Engineers.
• Authors:
  • Yang, Jidong J
  • Zuo, Bashan
• Publication Date: 2017-6

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: 04017020
• Serial:
  • Journal of Transportation Engineering, Part A: Systems
  • Volume: 143
  • Issue Number: 6
  • Publisher: American Society of Civil Engineers
  • ISSN: 2473-2907
  • EISSN: 2473-2893
  • Serial URL: http://ascelibrary.org/journal/jtepbs

Subject/Index Terms

• TRT Terms: Data collection; Data mining; Environmental impacts; Radar; Sensors; Signalized intersections; Vehicle detectors; Weather conditions
• Geographic Terms: United States
• Subject Areas: Data and Information Technology; Environment; Highways; Safety and Human Factors;

Filing Info

• Accession Number: 01627840
• Record Type: Publication
• Files: TRIS, ASCE
• Created Date: Feb 28 2017 9:11AM