Publication detail

Real-Time Autonomous Vehicle Sensor Performance Assessment in Adverse Weather Conditions

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"
}