Enabling Live State-of-Health Monitoring for a Safety-Critical Automotive LiDAR System

Andreas Strasser, Philipp Stelzer, Christian Steger, Norbert Druml

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem Konferenzband

Abstract

In the next few years, modern vehicles will integrate the next level of Advanced Driver-Assistance Systems (ADAS) such as Light Detection and Ranging (LiDAR) which will be one of the key enabler for autonomous driving. Autonomous driving will be in charge for controlling the vehicle without any inputs of a passenger. This requires highly robust and reliable components and systems. In general, mechanical defects are detectable through vibrations or noise changes but for semiconductor components these capabilities are not available. Semiconductor components fail silently and abrupt without any prior information and this could lead to fatal accidents when systems fail during autonomous driving phases. In this publication, we are introducing a novel state-of-health monitoring system for automotive LiDAR system that is capable to economically record the component history and automatically processes these data to the statistical Failure-In-Time (FIT) Rate that is primarily used in the Automotive domain such as in the "ISO 26262 - Road Vehicle Safety" standard.
Originalspracheenglisch
Titel2020 IEEE Sensors Applications Symposium, SAS 2020 - Proceedings
Seitenumfang6
ISBN (elektronisch)9781728148427
DOIs
PublikationsstatusVeröffentlicht - Mär 2020
Veranstaltung2020 IEEE Sensors Applications Symposium - Kuala Lumpur, Malaysia
Dauer: 9 Mär 202011 Mär 2020

Publikationsreihe

Name2020 IEEE Sensors Applications Symposium, SAS 2020 - Proceedings

Konferenz

Konferenz2020 IEEE Sensors Applications Symposium
KurztitelSAS 2020
LandMalaysia
OrtKuala Lumpur
Zeitraum9/03/2011/03/20

ASJC Scopus subject areas

  • !!Instrumentation
  • !!Computer Vision and Pattern Recognition
  • !!Computer Science Applications

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