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Authors: Thilo Braun ; Lennart Ries ; Moritz Hesche ; Stefan Otten and Eric Sax

Affiliation: FZI Research Center for Information Technology, Haid-und-Neu-Str. 10-14, 76131 Karlsruhe, Germany

Keyword(s): Scenario-based Testing, Scenario Extraction, Graph Visualization.

Abstract: Since automated driving functions are safety-critical systems, extensive validation and verification is necessary. Scenario-based testing is a promising approach for this challenge. For selection of relevant scenarios, collected data and knowledge models are potential sources. In this paper we introduce a concept to use recorded trajectory and map data, abstracted to maneuvers, to describe the scenarios and visualize them intuitively. This enables a data-driven scenario-mining process to find relevant scenarios for the testing of automated driving functions. To compare the scenarios, a similarity measure based on the manuevers is designed and the scenarios and their similarities are represented as a graph. Graph-visualization methods, already successfully applied in other domains, structure the collected data for further analysis. The concept is exemplary applied to an urban traffic dataset.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Braun, T., Ries, L., Hesche, M., Otten, S. and Sax, E. (2022). Maneuver-based Visualization of Similarities between Recorded Traffic Scenarios. In Proceedings of the 11th International Conference on Data Science, Technology and Applications - DATA; ISBN 978-989-758-583-8; ISSN 2184-285X, SciTePress, pages 236-244. DOI: 10.5220/0011140600003269

@conference{data22,
author={Thilo Braun and Lennart Ries and Moritz Hesche and Stefan Otten and Eric Sax},
title={Maneuver-based Visualization of Similarities between Recorded Traffic Scenarios},
booktitle={Proceedings of the 11th International Conference on Data Science, Technology and Applications - DATA},
year={2022},
pages={236-244},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011140600003269},
isbn={978-989-758-583-8},
issn={2184-285X},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Data Science, Technology and Applications - DATA
TI - Maneuver-based Visualization of Similarities between Recorded Traffic Scenarios
SN - 978-989-758-583-8
IS - 2184-285X
AU - Braun, T.
AU - Ries, L.
AU - Hesche, M.
AU - Otten, S.
AU - Sax, E.
PY - 2022
SP - 236
EP - 244
DO - 10.5220/0011140600003269
PB - SciTePress

- Science and Technology Publications, Lda.
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