Automatic Traffic Data Collection under Varying Lighting and Temperature Conditions in Multimodal Environments: Thermal Versus Visible Spectrum Video-Based Systems

Vision-based monitoring systems using visible spectrum (regular) video cameras can complement or substitute conventional sensors and provide rich positional and classification data. Although new camera technologies, including thermal video sensors, may improve the performance of digital video-based sensors, their performance under various conditions has rarely been evaluated at multimodal facilities. The purpose of this research is to integrate existing computer vision methods for automated data collection and evaluate the detection, classification, and speed measurement performance of thermal video sensors under varying lighting and temperature conditions. Thermal and regular video data was collected simultaneously under different conditions across multiple sites. Although the regular video sensor narrowly outperformed the thermal sensor during daytime, the performance of the thermal sensor is significantly better for low visibility and shadow conditions, particularly for pedestrians and cyclists. Retraining the algorithm on thermal data yielded an improvement in the global accuracy of 48%. Thermal speed measurements were consistently more accurate than for the regular video at daytime and nighttime. Thermal video is insensitive to lighting interference and pavement temperature, solves issues associated with visible light cameras for traffic data collection, and offers other benefits such as privacy, insensitivity to glare, storage space, and lower processing requirements.

• Record URL:
  https://doi.org/10.1155/2017/5142732
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/5121625
• Supplemental Notes:
  • © 2016 Ting Fu et al.
• Authors:
  • Fu, T
  • Stipancic, J
  • Zangenehpour, S
  • Miranda-Moreno, L
  • Saunier, N
• Publication Date: 2017

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Serial:
  • Journal of Advanced Transportation
  • Volume: 2017
  • Issue Number: Article ID 5142732
  • Publisher: John Wiley & Sons, Incorporated
  • ISSN: 0197-6729
  • EISSN: 2042-3195
  • Serial URL: http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2042-3195
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Automatic data collection systems; Automatic vehicle monitoring; Data collection; Temperature sensors; Thermal imagery; Traffic data; Vehicle mix; Video cameras
• Subject Areas: Data and Information Technology; Highways;

Filing Info

• Accession Number: 01647087
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 27 2017 10:20AM