SceML: a graphical modeling framework for scenario-based testing of autonomous vehicles

Resource type
Conference
Author(s)
Barbara Schütt, Thilo Braun, Stefan Otten, Eric Sax
Year
2020
Abstract
Ensuring the functional correctness and safety of autonomous ve-hicles is a major challenge for the automotive industry. However,exhaustive physical test drives are not feasible, as billions of drivenkilometers would be required to obtain reliable results. Scenario-based testing is an approach to tackle this problem and reducenecessary test drives by replacing driven kilometers with simula-tions of relevant or interesting scenarios. These scenarios can begenerated or extracted from recorded data with machine learningalgorithms or created by experts. In this paper, we propose a novelgraphical scenario modeling language. The graphical frameworkallows experts to create new scenarios or review ones designed byother experts or generated by machine learning algorithms. Thescenario description is modeled as a graph and based on behaviortrees. It supports different abstraction levels of scenario descriptionduring software and test development. Additionally, the graph-based structure provides modularity and reusable sub-scenarios,an important use case in scenario modeling. A graphical visualiza-tion of the scenario enhances comprehensibility for different users.The presented approach eases the scenario creation process andincreases the usage of scenarios within development and testingprocesses.
DOI
https://dx.doi.org/10.1145/3365438.3410933
Research focus
Safe and Intelligent Vehicles
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Published by
Thilo Braun