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Automatic traffic data collection under varying lighting and temperature conditions in multimodal environments: thermal versus visible spectrum video-based systems

Ting Fu, Joshua Stipancic, Sohail Zangenehpour, Luis Miranda-Moreno et Nicolas Saunier

Article de revue (2017)

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Abstract

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.

Sujet(s): 1000 Génie civil > 1000 Génie civil
1000 Génie civil > 1003 Génie du transport
Département: Département des génies civil, géologique et des mines
Organismes subventionnaires: McGill Engineering Doctoral Award, CRSNG/NSERC
URL de PolyPublie: https://publications.polymtl.ca/3532/
Titre de la revue: Journal of Advanced Transportation (vol. 2017)
Maison d'édition: Hindawi
DOI: 10.1155/2017/5142732
URL officielle: https://doi.org/10.1155/2017/5142732
Date du dépôt: 14 déc. 2018 15:59
Dernière modification: 19 oct. 2023 18:26
Citer en APA 7: Fu, T., Stipancic, J., Zangenehpour, S., Miranda-Moreno, L., & Saunier, N. (2017). Automatic traffic data collection under varying lighting and temperature conditions in multimodal environments: thermal versus visible spectrum video-based systems. Journal of Advanced Transportation, 2017, 1-15. https://doi.org/10.1155/2017/5142732

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