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Journal Articles Journal of Intelligent and Robotic Systems Year : 2023

Verifying Collision Risk Estimation using Autonomous Driving Scenarios Derived from a Formal Model

Abstract

Verifying Collision Risk Estimation using Formally Derived Scenarios use formal conformance test generation tools to derive, from a verified formal model, sets of scenarios to be run in a simulator. Second, we model check the traces of the simulation runs to validate the probabilistic estimation of collision risks. Using formal methods brings the combined advantages of an increased confidence in the correct representation of the chosen configuration (temporal logic verification), a guarantee of the coverage and relevance of automatically generated scenarios (conformance testing), and an automatic quantitative analysis of the test execution (verification and statistical analysis on traces).
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hal-04138579 , version 1 (23-06-2023)

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Jean-Baptiste Horel, Philippe Ledent, Lina Marsso, Lucie Muller, Christian Laugier, et al.. Verifying Collision Risk Estimation using Autonomous Driving Scenarios Derived from a Formal Model. Journal of Intelligent and Robotic Systems, 2023, 107 (4), pp.1-45. ⟨10.1007/s10846-023-01808-3⟩. ⟨hal-04138579⟩
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