12 papers
Self-Adaptive Anomaly Detection with Reinforcement Learning and Human Feedback in Connected Vehicles
Matthias WeiÃ, Athreya Hosahalli Prakash, Maurice Artelt +3
Connected vehicles are autonomous cyber-physical systems whose behavior must be continuously monitored during operation to detect deviations from normal operation before they propa…
Evaluating Hardware Abstraction Layer Concepts for Software Defined Vehicles: Insights into Applicability and Effectiveness
Akshay Narla, Johannes Stümpfle, Souvik Saha +2
The emergence of Software-Defined Vehicles represents a fundamental shift in automotive design, prioritizing software-centric architectures over traditional hardware-driven models.…
SDVDiag: Multimodal Causal Discovery for Online Diagnosis in Software-defined Vehicles
Matthias WeiÃ, Athreya Hosahalli Prakash, Falk Dettinger +2
The transition toward software-defined vehicles concentrates an increasing share of vehicle functionality into distributed software services, where failures propagate through servi…
Towards Intelligent Computation Offloading in Dynamic Vehicular Networks: A Scalable Multilayer Pipeline
Falk Dettinger, Matthias WeiÃ, Baran Can Gül +3
Software Defined Vehicles face an increasing computational gap as advanced algorithms and frequent software updates demand more processing power while onboard hardware remains stat…
SDVDiag: Using Context-Aware Causality Mining for the Diagnosis of Connected Vehicle Functions
Matthias WeiÃ, Falk Dettinger, Elias Detrois +2
Real-world implementations of connected vehicle functions are spreading steadily, yet operating these functions reliably remains challenging due to their distributed nature and the…
FedMultiEmo: Real-Time Emotion Recognition via Multimodal Federated Learning
Baran Can Gül, Suraksha Nadig, Stefanos Tziampazis +2
In-vehicle emotion recognition underpins adaptive driver-assistance systems and, ultimately, occupant safety. However, practical deployment is hindered by (i) modality fragility -…