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AV/ADAS Safety-Critical Testing Scenario Generation from Vehicle Crash Data
Technical Paper
2022-01-0104
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
This research leverages publicly available crash data to construct safety-critical scenarios focusing primarily on Level 3 Automated Driving Systems (ADS) safety assessment under highway driving conditions. NHTSA’s Crashworthiness Data System (CDS) has a rich dataset of representative crashes sampled from numerous Primary Sampling Units (PSUs) across the country. Each of these datasets includes the storyline, road geometry information, detailed description of actors involved in the crash, weather information, scene diagrams, crash images, and a myriad of other crash-specific details. The methodology adopted aims to generate critical scenarios from real-world driving to complement the existent regulatory tests for the validation of L3 ADS. For this work, a four-step approach was adopted to extract safety-critical scenarios from crash data. Firstly, a methodology was developed to filter crash cases relevant to the scope and resulting pdf files, and numerical crash data were downloaded from the CDS website. Then, the numerical data is utilized to characterize cases into crash categories. Thirdly, the numeric data and pdf data are used to combine multiple crash cases into fewer representative ‘logical scenarios’ which define the road network, actors, actor types, crash storyline encompassing a feasible parameter space. Finally, the generated logical scenarios are used to develop specific safety-critical scenarios. The key outcome of this research is a set of safety-critical scenarios based on real-world crash data, categorized according to specific ADS control objectives that can be utilized to validate ADS functionalities.
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Citation
Kibalama, D., Tulpule, P., and Chen, B., "AV/ADAS Safety-Critical Testing Scenario Generation from Vehicle Crash Data," SAE Technical Paper 2022-01-0104, 2022, https://doi.org/10.4271/2022-01-0104.Also In
References
- Huang , W.L. , Wang , K. , Lv , Y. , and Zhu , F.H. Autonomous Vehicles Testing Methods Review IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC Dec. 2016 163 168 10.1109/ITSC.2016.7795548
- Wagner , S. , Knoll , A. , Groh , K. , Kühbeck , T. et al. Virtual Assessment of Automated Driving: Methodology, Challenges, and Lessons Learned SAE International Journal of Connected and Automated Vehicles 2 4 2019 Dec 10.4271/12-02-04-0020
- Wachenfeld , W. and Winner , H. The Release of Autonomous Vehicles Autonomous Driving: Technical, Legal and Social Aspects Springer Berlin Heidelberg 2016 425 449 10.1007/978-3-662-48847-8_21
- Hallerbach , S. , Xia , Y. , Eberle , U. , and Koester , F. Simulation-Based Identification of Critical Scenarios for Cooperative and Automated Vehicles SAE Intl. J CAV 1 2 2018 93 106 https://doi.org/10.4271/2018-01-1066
- Allen , J. , Koo , W. , Murugesan , D. , and Zagorski , C. Testing Methods and Recommended Validation Strategies for Active Safety to Optimize Time and Cost Efficiency SAE Technical Paper 2020-01-1348 2020 https://doi.org/10.4271/2020-01-1348
- Kirovskii , O. Determination of Validation Testing Scenarios for an ADAS Functionality: Case Study SAE Technical Paper 2019-01-0137 2019 https://doi.org/10.4271/2019-01-0137
- Schram , R. and Schram , R.
- F. H. R. I. (BASt) https://www.gidas.org/index-2.html
- IGLAD Working Group http://www.iglad.net/
- NHTSA https://www.nhtsa.gov/crash-data-systems/crash-investigation-sampling-system
- Ulbrich , S. , Menzel , T. , Reschka , A. , Schuldt , F. , and Maurer , M. Defining and Substantiating the Terms Scene, Situation, and Scenario for Automated Driving IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC Oct. 2015 982 988 10.1109/ITSC.2015.164
- PEGASUS Project Office https://www.pegasusprojekt.de/en/pegasus-method
- Menzel , T. , Bagschik , G. , and Maurer , M. http://arxiv.org/abs/1801.08598
- ASAM e.V https://www.asam.net/index.php?eID=dumpFile&t=f&f=4092&token=d3b6a55e911b22179e3c0895fe2caae8f5492467
- ASAM e.V https://www.asam.net/index.php?eID=dumpFile&t=f&f=4422&token=e590561f3c39aa2260e5442e29e93f6693d1cccd
- NHTSA https://one.nhtsa.gov/Research/Crash-Injury-Research-
- NHTSA https://crashviewer.nhtsa.dot.gov/LegacyCDS/Search
- https://unece.org/sites/default/files/2021-03/R157e.pdf