Triggering Conditions Analysis and Use Case for Validation of ADAS/ADS Functions

Víctor J. Expósito Jiménez*, Helmut Martin, Christian Schwarzl, Georg Macher, Eugen Brenner

*Corresponding author for this work

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


Safety in the automotive domain is a well-known topic, which has been in constant development in the past years. The complexity of new systems that add more advanced components in each function has opened new trends that have to be covered from the safety perspective. In this case, not only specifications and requirements have to be covered but also scenarios, which cover all relevant information of the vehicle environment. Many of them are not yet still sufficient defined or considered. In this context, Safety of the Intended Functionality (SOTIF) appears to ensure the system when it might fail because of technological shortcomings or misuses by users. An identification of the plausibly insufficiencies of ADAS/ADS functions has to be done to discover the potential triggering conditions that can lead to these unknown scenarios, which might effect a hazardous behaviour. The main goal of this publication is the definition of an use case to identify these triggering conditions that have been applied to the collision avoidance function implemented in our self-developed mobile Hardware-in-Loop (HiL) platform.

Original languageEnglish
Title of host publicationComputer Safety, Reliability, and Security. SAFECOMP 2022 Workshops
Subtitle of host publicationDECSoS, DepDevOps, SASSUR, SENSEI, USDAI, and WAISE, Proceedings
EditorsMario Trapp, Erwin Schoitsch, Jérémie Guiochet, Friedemann Bitsch
Place of PublicationCham
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages12
ISBN (Print)9783031148613
Publication statusPublished - 2022
Event41st International Conference on Computer Safety, Reliability and Security: SafeComp 2022 - online, Munich, Germany
Duration: 6 Sep 20229 Sep 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13415 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference41st International Conference on Computer Safety, Reliability and Security
Abbreviated titleSAFECOMP 2022


  • ADAS
  • Automated Driving Systems
  • Triggering conditions

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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