The perception system of intelligent ground vehicles in all weather conditions: A systematic literature review

Mohammed, A. S., Amamou, A., Ayevide, F. K., Kelouwani, S., Agbossou, K. et Zioui, N. (2020). The perception system of intelligent ground vehicles in all weather conditions: A systematic literature review. Sensors, 20 (22). p. 6532. ISSN 1424-8220 DOI 10.3390/s20226532

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Résumé

Perception is a vital part of driving. Every year, the loss in visibility due to snow, fog, and rain causes serious accidents worldwide. Therefore, it is important to be aware of the impact of weather conditions on perception performance while driving on highways and urban traffic in all weather conditions. The goal of this paper is to provide a survey of sensing technologies used to detect the surrounding environment and obstacles during driving maneuvers in different weather conditions. Firstly, some important historical milestones are presented. Secondly, the state-of-the-art automated driving applications (adaptive cruise control, pedestrian collision avoidance, etc.) are introduced with a focus on all-weather activity. Thirdly, the most involved sensor technologies (radar, lidar, ultrasonic, camera, and far-infrared) employed by automated driving applications are studied. Furthermore, the difference between the current and expected states of performance is determined by the use of spider charts. As a result, a fusion perspective is proposed that can fill gaps and increase the robustness of the perception system.

Type de document:	Article
Mots-clés libres:	Advanced driver assistance systems Autonomous vehicles Infrared camera Lidar Radar Road safety Sensor Sensor fusion Ultrasonic sensor Weather conditions
Date de dépôt:	12 avr. 2023 12:21
Dernière modification:	12 avr. 2023 12:21
Version du document déposé:	Version officielle de l'éditeur
URI:	https://depot-e.uqtr.ca/id/eprint/10629

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