Formal Scenario-Based Testing of Autonomous Vehicles: From Simulation to the Real World

We present a new approach to automated scenario-based testing of the safety of autonomous vehicles, especially those using advanced artificial intelligence-based components, spanning both simulation-based evaluation as well as testing in the real world. Our approach is based on formal methods, combi...

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Bibliographic Details
Published in2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC) pp. 1 - 8
Main Authors Fremont, Daniel J., Kim, Edward, Pant, Yash Vardhan, Seshia, Sanjit A., Acharya, Atul, Bruso, Xantha, Wells, Paul, Lemke, Steve, Lu, Qiang, Mehta, Shalin
Format Conference Proceeding
LanguageEnglish
Published IEEE 20.09.2020
Subjects
Analytical models
Autonomous vehicles
Data models
Mathematical model
Roads
Safety
Testing
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DOI10.1109/ITSC45102.2020.9294368

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Summary:We present a new approach to automated scenario-based testing of the safety of autonomous vehicles, especially those using advanced artificial intelligence-based components, spanning both simulation-based evaluation as well as testing in the real world. Our approach is based on formal methods, combining formal specification of scenarios and safety properties, algorithmic test case generation using formal simulation, test case selection for track testing, executing test cases on the track, and analyzing the resulting data. Experiments with a real autonomous vehicle at an industrial testing facility support our hypotheses that (i) formal simulation can be effective at identifying test cases to run on the track, and (ii) the gap between simulated and real worlds can be systematically evaluated and bridged.
DOI:10.1109/ITSC45102.2020.9294368