Embedded Linux Crash Resilience for Autonomous Vehicles

Abstract

This article examines the implementation of persistent crash logging infrastructure for autonomous vehicles running embedded Linux systems. It explores how proper failure capture mechanisms can transform system crashes from dangerous incidents into valuable learning opportunities. The article investigates the challenges of crash capture in embedded automotive environments, detailing the implementation of the Linux kernel's persistent storage (pstore) subsystem with the ramoops driver, and the enhancement of diagnostic capabilities through kdump integration. Through analysis of multiple studies and empirical data, the article demonstrates how this dual-layer approach to crash resilience significantly improves engineering efficiency, system reliability, and safety assurance. The paper demonstrates that a robust crash logging infrastructure allows organizations to solve once-undiagnosable failures, speed development cycles, and establish more cogent evidence-based safety arguments for regulatory approval. The paper demonstrates that continuous crash logging not only improves diagnostics for sophisticated failure modes but also delivers measurable benefits in development speed, certification processes, and overall system dependability in safety-critical autonomous vehicle deployments.