Sorokos, IoannisIoannisSorokosWolf, PatrickPatrickWolfReich, JanJanReichSchneider, DanielDanielSchneider2024-12-172024-12-172024https://publica.fraunhofer.de/handle/publica/48079610.1109/IOTSMS62296.2024.107103152-s2.0-85208034818Self-adaptive methods have been advocated for addressing challenges related to managing unknowns and uncertainties in autonomous driving, which in turn are caused by, e.g., machine-learning uncertainty, operation in an open context, and cybersecurity. Many works proposed specific vehicle architectures featuring self-adaptation mechanisms. However, each work tackles specific problems often using different levels of abstraction making the approaches hard to compare and making it even harder to compile complementary features into a single architecture. This paper systematizes the body of knowledge in self-adaptive vehicle architectures by proposing evaluation criteria based on the available literature (standards and research paper) and on identified desiderata for self-adaptive vehicles. We proceed to carry out a detailed analysis of selected papers based on the evaluation criteria in the context of the Level 3 Highway Pilot vehicle feature. The paper concludes by pointing out research gaps which we believe will foment future work on self-adaptive vehicle architectures.enfalseAutonomous VehiclesEvaluationResilienceRobustnessSafetySecuritySelf-Adaptive Architectureconference paper