Přístupnostní navigace
E-application
Search Search Close
Publication detail
SVĚDIROH, S. ŽALUD, L.
Original Title
Real-Time Autonomous Vehicle Sensor Performance Assessment in Adverse Weather Conditions
Type
article in a collection out of WoS and Scopus
Language
English
Original Abstract
The future of automotive industry appears to be intricately linked to Advanced Driver Assistance Systems (ADAS) and various levels of Automated Driving Systems (ADS). Over the years, numerous companies have incorporated sensors into their vehicles, hovewer, none have yet achieved the development of a completely robust and self-aware system capable of operating safely in adverse weather conditions. To guarantee safety, the vehicle must possess an awareness of its environment and the current performance of its sensors. This includes the ability to detect not only currrent weather conditions such as rain, fog, haze, and snow, but also smoke, soiling from various sources, and extreme lighting conditions such as glare or low light. It is crucial for the vehicle to detect those conditions in real-time without delaying decision-making systems. This study summarises the effects of various environmental threats on commonly used sensors in ADAS or ADS and proposes algorithms to detect degrading sensor performance, which can then be integrated into the sensor fusion framework utilised in the creation of the vehicle's local map. The ultimate aim of such system is to accurately detect and report sensor degradation, enabling subsequent sensor fusion and path-planning algorithms to modify the vehicle's behaviour and minimise unreasonable risk.
Keywords
ADAS, ADS, dwerse Weather, Sensor Performance Assessment
Authors
SVĚDIROH, S.; ŽALUD, L.
Released
25. 4. 2023
Publisher
Brno University of Technology, Faculty of Electrical Engineering and Communication
Location
Brno
ISBN
978-80-214-6153-6
Book
Proceedings I of the 29th Student EEICT 2023 General papers
Edition
1
Pages from
423
Pages to
428
Pages count
6
URL
https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_1.pdf
BibTex
@inproceedings{BUT183816, author="Stanislav {Svědiroh} and Luděk {Žalud}", title="Real-Time Autonomous Vehicle Sensor Performance Assessment in Adverse Weather Conditions", booktitle="Proceedings I of the 29th Student EEICT 2023 General papers", year="2023", series="1", pages="423--428", publisher="Brno University of Technology, Faculty of Electrical Engineering and Communication", address="Brno", isbn="978-80-214-6153-6", url="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_1.pdf" }