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A Retargetable Fault Injection Framework for Safety Validation of Autonomous Vehicles

Yuting Fu, Andrei Terechko, Tjerk Bijlsma, Pjl Pieter Cuijpers, J Jeroen Redegeld, Ali Osman Ors

Year
2019
Citations
17

Abstract

Autonomous vehicles use Electronic Control Units running complex software to improve passenger comfort and safety. To test safety of in-vehicle electronics, the ISO 26262 standard on functional safety recommends using fault injection during component and system-level design. A Fault Injection Framework (FIF) induces hard-to-trigger hardware and software faults at runtime, enabling analysis of fault propagation effects. The growing number and complexity of diverse interacting components in vehicles demands a versatile FIF at the vehicle level. In this paper, we present a novel retargetable FIF based on debugger interfaces available on many target systems. We validated our FIF in three Hardware-In-the-Loop setups for autonomous driving based on the NXP BlueBox prototyping platform. To trigger a fault injection process, we developed an interactive user interface based on Robot Operating System, which also visualized vehicle system health. Our retargetable debugger-based fault injection mechanism confirmed safety properties and identified safety shortcomings of various automotive systems.

Keywords

Fault injectionComputer scienceEmbedded systemAutomotive engineeringReliability engineeringEngineeringProgramming languageSoftware

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