Conference: Creating a Framework for the Representativeness Assessment of Automated Driving Safety Assurance

Over the past years, automated driving has moved towards a stage, where the public introduction of automated driving functions (ADF) seems conceivable. However, the question of verification and validation of these systems as well as assuring their safety is still a discussion among researchers, manufacturers, and authorities. Whilst the approach of scenario-based testing has established itself for this task in research and application, open questions remain regarding the relevance of scenarios and their needed representativeness. Within this paper, we present a framework which can help with this task by taking different data sources into account to assess the representativeness of scenario parameters in these data sources as well as in recorded data. As scenario parameters apart from traffic participants we take weather and road parameters into account. Within the research project Hi-Drive, enabling the ADFs to deal with these parameters is an important topic of research.

RWTH Publications server

Recommended citation:

@INPROCEEDINGS{Hiller2022,
  author       = {Hiller, Johannes Manuel and Kalyagina, Svetlana and Eckstein, Lutz},
  title        = {Creating a Framework for the Representativeness Assessment of Automated Driving Safety Assurance},
  booktitle    = {28th ITS World Congress , Los Angeles (USA), 18 Sep 2022 - 22 Sep 2022},
  reportid     = {RWTH-2022-10485},
  year         = {2022},
  month        = {Sep},
  date         = {2022-09-18},
  organization = {28th ITS World Congress , Los Angeles (USA), 18 Sep 2022 - 22 Sep 2022},
  url          = {https://publications.rwth-aachen.de/record/855855},
  doi          = {10.18154/RWTH-2022-10485},
}