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A Process for Scenario Prioritization and Selection in Simulation-Based Safety Testing of Automated Driving Systems

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Product-Focused Software Process Improvement (PROFES 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14483))

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Abstract

Simulation-based safety testing of Automated Driving Systems (ADS) is a cost-effective and safe alternative to field tests. However, it is practically impossible to test every scenario using a simulator. We propose a process for prioritizing and selecting scenarios from an existing list of scenarios. The aim is to refine the scope of tested scenarios and focus on the most representative and critical ones for evaluating ADS safety. As a proof-of-concept, we apply our process to two pre-existing scenario catalogs provided by the Land Transport Authority of Singapore and the Department of Transportation. After applying our process, we prioritized and selected six scenario groups containing 51 scenarios for testing ADS in the CARLA simulator.

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Notes

  1. 1.

    Uber Self-driving Crash.

  2. 2.

    Tesla Autopilot Crash.

  3. 3.

    NHTSA.

  4. 4.

    List of Pre-Crash Scenario for Crash Avoidance Research.

  5. 5.

    Test Scenarios- European New Car Assessment Programme.

  6. 6.

    List of Scenario Categories for the Assessment of Automated Vehicles.

  7. 7.

    NCSA Tools, Publications, and Data (Traffic Safety facts Annual Report Tables).

  8. 8.

    European Road Safety Data Portal - European Union.

  9. 9.

    Statistics at DfT - United Kingdom.

  10. 10.

    Canadian Motor Vehicle Traffic Collision Statistics: 2021.

  11. 11.

    Stat. for collision with dynamic&fixed objects: Ch. 3\(\rightarrow \)Passenger Cars\(\rightarrow \) Table 42.

  12. 12.

    Stat. for weather and lighting conditions: Goto: Chap. 2\(\rightarrow \)Time \(\rightarrow \)Table 26.

  13. 13.

    Stat. for occupants, non-occupants killed&injured in traffic crashes:Goto:Chapter 1:Trends \(\rightarrow \) General\(\rightarrow \) Table 3.

  14. 14.

    Stat. for crashes by vehicle driving maneuver: see table “Vehicles Involved in Single- and Two-Vehicle Fatal Crashes by Vehicle Maneuver”, State: USA, Year: 2020.

  15. 15.

    List of scenarios - Land Transport Authority of Singapore.

  16. 16.

    List of scenarios - US Department of Transportation - Table 1.

  17. 17.

    GES Crash Statistics - See Table 5: All crashes.

  18. 18.

    https://carla.org/.

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Acknowledgements

This research was partly funded by the Austrian BMK, BMAW, and State of Upper Austria under the SCCH competence center INTEGRATE [(FFG grant 892418)], the Estonian Research Council (grant PRG1226), Bolt Technology OÜ, and the Estonian state stipend for doctoral studies.

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Authors and Affiliations

  1. University of Tartu, Narva mnt 18, 51009, Tartu, Estonia

    Fauzia Khan, Hina Anwar & Dietmar Pfahl

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  1. Fauzia Khan
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  2. Hina Anwar
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  3. Dietmar Pfahl
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Correspondence to Fauzia Khan .

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Editors and Affiliations

  1. FHV Vorarlberg University of Applied Science, Dornbirn, Austria

    Regine Kadgien

  2. Fraunhofer Institute for Experimental Software Engineering, Kaiserslautern, Germany

    Andreas Jedlitschka

  3. FHV Vorarlberg University of Applied Science, Dornbirn, Austria

    Andrea Janes

  4. University of Oulu, Oulu, Finland

    Valentina Lenarduzzi

  5. University of Oulu, Oulu, Finland

    Xiaozhou Li

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Khan, F., Anwar, H., Pfahl, D. (2024). A Process for Scenario Prioritization and Selection in Simulation-Based Safety Testing of Automated Driving Systems. In: Kadgien, R., Jedlitschka, A., Janes, A., Lenarduzzi, V., Li, X. (eds) Product-Focused Software Process Improvement. PROFES 2023. Lecture Notes in Computer Science, vol 14483. Springer, Cham. https://doi.org/10.1007/978-3-031-49266-2_6

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  • DOI: https://doi.org/10.1007/978-3-031-49266-2_6

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