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Vehicle Data Management System for Scenario-Based Validation of Automated Driving Functions

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Smart Cities, Green Technologies and Intelligent Transport Systems (SMARTGREENS 2019, VEHITS 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1217))

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Abstract

Proving the functionality of AI-controlled automated vehicles is a challenging task due to the enormous overall complexity. Although a scenario-based validation approach is widely accepted in the literature, the identification of these scenarios is still an open issue.

Real-world test drives are valuable data sources for this purpose. However, an automated system is required for data management and scenario identification to analyze the vast amount of data in a legitimate amount of time and effort. Therefore, this work proposes a modular multi-tier Vehicle Data Management System for large-scale test campaign management and analysis as the basis for scenario-based validation of automated driving functions. For system demonstration, lane-change maneuvers are identified and extracted, and an onboard DAS is evaluated with a real-world test drive sequence.

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Notes

  1. 1.

    Intelligent Validierung von Fahrerassistanzsystemen (engl.: intelligent validation of driver assistance systems) of the Hochschule Emden/Leer.

  2. 2.

    The Automotive Data and Time-triggered Framework (ADTF) of Elektrobit is used for synchronous data measurement and capturing.

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Acknowledgements

We thank LG Electronics, Vehicle Solution Company, Republic of Korea, for supporting this project by cooperating in capturing large-scale test drives and providing valuable measurement equipment.

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Authors and Affiliations

  1. Department of Electronics and Informatics, Hochschule Emden/Leer, University of Applied Sciences, Emden, Germany

    Lars Klitzke, Carsten Koch & Andreas Haja

  2. German Aerospace Center (DLR), Institute of Transportation Systems, Braunschweig, Germany

    Frank Köster

Authors
  1. Lars Klitzke
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  2. Carsten Koch
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  3. Andreas Haja
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  4. Frank Köster
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Corresponding author

Correspondence to Lars Klitzke .

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Editors and Affiliations

  1. Dublin City University, Dublin, Ireland

    Markus Helfert

  2. Department of Corporate Technology, Siemens AG, Munich, Germany

    Cornel Klein

  3. School of Business, Innovation Value Institute, Maynooth University, Maynooth, Kildare, Ireland

    Brian Donnellan

  4. Ford Research and Advanced Engineering, Dearborn, MI, USA

    Oleg Gusikhin

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Klitzke, L., Koch, C., Haja, A., Köster, F. (2021). Vehicle Data Management System for Scenario-Based Validation of Automated Driving Functions. In: Helfert, M., Klein, C., Donnellan, B., Gusikhin, O. (eds) Smart Cities, Green Technologies and Intelligent Transport Systems. SMARTGREENS VEHITS 2019 2019. Communications in Computer and Information Science, vol 1217. Springer, Cham. https://doi.org/10.1007/978-3-030-68028-2_16

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  • DOI: https://doi.org/10.1007/978-3-030-68028-2_16

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