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

Andreas Strasser, Philipp Stelzer, Christian Steger, Norbert Druml

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


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.
Original languageEnglish
Title of host publication2020 IEEE Sensors Applications Symposium, SAS 2020 - Proceedings
Number of pages6
ISBN (Electronic)9781728148427
Publication statusPublished - Mar 2020
Event15th IEEE Sensors Applications Symposium: SAS 2020 - Kuala Lumpur, Malaysia
Duration: 9 Mar 202011 Mar 2020

Publication series

Name2020 IEEE Sensors Applications Symposium, SAS 2020 - Proceedings


Conference15th IEEE Sensors Applications Symposium
Abbreviated titleSAS 2020
CityKuala Lumpur


  • FIT Monitor
  • Reliability
  • Monitor
  • Aging Monitor
  • LiDAR
  • Safety
  • Reliability Monitor

ASJC Scopus subject areas

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


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