Projects per year
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.
Original language | English |
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Title of host publication | 2020 IEEE Sensors Applications Symposium, SAS 2020 - Proceedings |
Number of pages | 6 |
ISBN (Electronic) | 9781728148427 |
DOIs | |
Publication status | Published - Mar 2020 |
Event | 15th IEEE Sensors Applications Symposium: SAS 2020 - Kuala Lumpur, Malaysia Duration: 9 Mar 2020 → 11 Mar 2020 |
Publication series
Name | 2020 IEEE Sensors Applications Symposium, SAS 2020 - Proceedings |
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Conference
Conference | 15th IEEE Sensors Applications Symposium |
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Abbreviated title | SAS 2020 |
Country/Territory | Malaysia |
City | Kuala Lumpur |
Period | 9/03/20 → 11/03/20 |
Keywords
- 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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Hardware/Software-Codesign
Steger, C., Seifert, C., Stelzer, P., Feldbacher, M., Fiala, G. & Basic, F.
1/01/95 → …
Project: Research area
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PRYSTINE - Programmable Systems for Intelligence in Automobiles
Steger, C., Strasser, A. & Stelzer, P.
1/05/18 → 30/04/21
Project: Research project