Leveraging Software Product Lines for Testing Autonomous Vehicles.

Stefan Klikovits, Alessio Gambi, Deepak Dhungana, Rick Rabiser

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

Abstract

Extensive testing of Automated Driving Systems (ADS), such as Advanced Driver Assistance Systems and Autonomous Vehicles, is commonly conducted using simulators programmed to implement various driving scenarios, a technique known as scenario-based testing. ADS scenario-based testing using simulations is challenging because it requires identifying scenarios that can effectively test ADS functionalities while ensuring that driving simulators' features match the driving scenarios' requirements. This short paper discusses the main challenges of systematically conducting simulation-based testing and proposes leveraging Software Product Line techniques to address them. Specifically, we argue that variability models can be used to support testers in generating test scenarios by effectively capturing and relating the variability in driving simulators, testing scenarios, and ADS implementations. We conclude by outlining an agenda for future research in this important area.

OriginalspracheEnglisch
TitelVaMoS 2024, Proceedings - 18th International Working Conference on Variability Modelling of Software-Intensive Systems
Seiten56-60
Seitenumfang5
ISBN (elektronisch)9798400708770
DOIs
PublikationsstatusVeröffentlicht - 7 Feb. 2024

Publikationsreihe

NameACM International Conference Proceeding Series

Forschungsfelder

  • Autonomous Vehicles

IMC Forschungsschwerpunkte

  • Software engineering and intelligent systems

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