Using an intelligent vision system for obstacle detection in winter condition

Ziadia, M., Kelouwani, S., Amamou, A., Dubé, Y. et Agbossou, K. (2019, May 3-5). Using an intelligent vision system for obstacle detection in winter condition. Dans VEHITS 2019 - Proceedings of the 5th International Conference on Vehicle Technology and Intelligent Transport Systems, Heraklion, Crete.

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Résumé

This paper explores the performance of an Advanced Driving Assistance System (ADAS) during navigation in urban traffic and a winter condition. The selected ADAS technology, Mobileye, has been integrated into a hydrogen electric vehicle. A set of three cameras (visible spectrum) has also been installed to give a surrounding view of the test vehicle. The tests were carried out during the dusk as well as in the night in winter condition. Using Matlab, the messages provided by Mobileye system have been analyzed. More than 2800 samples (short sequences of 5s Mobileye messages) have been processed and compared with the corresponding video samples recorded by the three cameras. In average, the selected ADAS device was able to provide 99% of true positive vehicle detection and classification, even in poor ambient lighting condition in winter. However, 72% of samples involving a pedestrian was correctly classified.

Type de document:	Document issu d'une conférence ou d'un atelier
Mots-clés libres:	Vehicle technology Collision avoidance Mobileye Advanced driving assistance system Winter navigation
Date de dépôt:	12 avr. 2023 14:24
Dernière modification:	12 avr. 2023 14:24
Version du document déposé:	Version officielle de l'éditeur
URI:	https://depot-e.uqtr.ca/id/eprint/10637

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