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Applying CT-FLA for AEB Function Testing: A Virtual Driving Case Study

Ludwig Kampel, Michael Wagner, Dimitris E. Simos, Mihai Nica, Dino Dodig, David Kaufmann, Franz Wotawa

Abstract:  The advancements of automated and autonomous vehicles requires virtual verification and validation of automated driving functions, in order to provide necessary safety levels and to increase acceptance of such systems. The aim of our work is to investigate the feasibility of combinatorial testing fault localization (CT-FLA) in the domain of virtual driving function testing. We apply CT-FLA to screen parameter settings that lead to critical driving scenarios in a virtual verification and validation framework used for automated driving function testing. Our first results indicate that CT-FLA methods can help to identify parameter-value combinations leading to crash scenarios. Index Terms—Combinatorial testing, Combinatorial fault lo- calization, AEB, autonomous driving, test scenario generation


Applying CT-FLA for AEB Function Testing: A Virtual Driving Case Study


 

Acknowledgement

ArchitectECA2030 has been accepted for funding within (ECSEL JU) in collaboration with the European Union’s H2020 Framework Programs under grant agreement No 877539.

The project will receive an ECSEL JU funding up to 4 M€ completed with national budgets from national funding authorities in Germany, Netherlands, Czech Republic, Austria and Norway.  

Project Facts

Short Name: ArchitectECA2030

Full Name: Trustable architectures with acceptable residual risk for the electric, connected and automated cars

Duration:  01/07/2020- 30/06/2023

Total Costs: ~ € 13,6 Mio.

Consortium: 20 partners from 8 countries

Coordinator: Infineon Technologies AG

Funding

 

Horizon 2020
Horizon 2020

 

    

National Funding

National Funding

 


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