All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

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

The result's identifiers

  • Result code in 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>

  • Result on the web

    <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

Alternative languages

  • Result language

    angličtina

  • Original language name

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

  • Original language description

    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

  • Czech name

  • Czech description

Classification

  • Type

    O - Miscellaneous

  • CEP classification

  • OECD FORD branch

    20204 - Robotics and automatic control

Result continuities

  • Project

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

  • Continuities

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

Others

  • Publication year

    2023

  • Confidentiality

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