arXiv:2606.15559v1 Announce Type: cross Abstract: The transition toward software-defined vehicles concentrates an increasing share of vehicle functionality into distributed software services, where failures propagate through service dependencies and the surface symptom is often several causal hops away from the underlying defect. Existing approaches to causal root-cause analysis in such systems address this only partially: they typically reason over a single observability modality and operate in an offline, operator-driven mode that does not match the demands of continuous vehicle operation. T
The increasing complexity and software-defined nature of modern vehicles necessitate advanced diagnostic tools to manage system failures in real-time, moving beyond traditional offline approaches.
This development is crucial for ensuring the reliability and safety of autonomous and software-centric vehicles, which are becoming increasingly integrated into daily life and critical infrastructure.
The shift from offline, single-modality root-cause analysis to online, multimodal causal discovery fundamentally changes how complex vehicle software systems diagnose and manage failures.
- · Automotive OEMs
- · Software-defined vehicle developers
- · AI/ML diagnostic solution providers
- · Vehicle owners and operators
- · Traditional diagnostic tool manufacturers
- · Manual repair processes
- · Systems with poor fault isolation
Improved reliability and safety for software-defined vehicles through enhanced diagnostic capabilities.
Accelerated development and deployment of more complex autonomous driving functionalities due to better fault management.
Potential for a new cybersecurity attack vector if diagnostic systems themselves are compromised, leading to manipulated fault reporting.
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Read at arXiv cs.LG