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

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F23%3APU148338" target="_blank" >RIV/00216305:26220/23:PU148338 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_1.pdf" target="_blank" >https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_1.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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 performan

Název v anglickém jazyce

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

Popis výsledku anglicky

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 performan

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

20204 - Robotics and automatic control

Projekt

<a href="/cs/project/8A20002" target="_blank" >8A20002: Trustable architectures with acceptable residual risk for the electric, connected and automated cars</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů