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Towards a Model of Snow Accretion for Autonomous Vehicles.

Authors :
Carvalho, Mateus
Moradi, Sadegh
Hosseinnouri, Farimah
Keshavan, Kiran
Villeneuve, Eric
Gultepe, Ismail
Komar, John
Agelin-Chaab, Martin
Hangan, Horia
Source :
Atmosphere; May2024, Vol. 15 Issue 5, p548, 17p
Publication Year :
2024

Abstract

Snow accumulation on surfaces exposed to adverse weather conditions has been studied over the years due to a variety of problems observed in different industry sectors, such as aeronautics and wind and civil engineering. With the growing interest in autonomous vehicles (AVs), this concern extends to advanced driver-assistance systems (ADAS). Weather stressors, such as snow and icing, negatively influence the sensor functionality of AVs, and their autonomy is not guaranteed by manufacturers during episodes of intense weather precipitation. As a basis for mitigating the negative effects caused by heavy snowfall, models need to be developed to predict snow accumulation over critical surfaces of AVs. The present work proposes a framework for the study of snow accumulation on road vehicles. Existing icing and snow accretion models are reviewed, and adaptations for automotive applications are discussed. Based on the new capabilities developed by the Weather on Wheels (WoW) program at Ontario Tech University, a model architecture is proposed in order to progress toward adequate snow accretion predictions for autonomous vehicle operating conditions, and preliminary results are presented. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20734433
Volume :
15
Issue :
5
Database :
Complementary Index
Journal :
Atmosphere
Publication Type :
Academic Journal
Accession number :
177459958
Full Text :
https://doi.org/10.3390/atmos15050548