SOURCE-LINKED INTELLIGENCE
ARIA - An Agentic Framework for Autonomous Testing of Infotainment Systems
Automotive infotainment validation still relies on manual testing, slow, costly, and incompatible with agile releases and OTA updates. Scripted automation only partly helps: it couples test logic to implementation, yielding brittle, high-maintenance suites. Existing LLM-driven frameworks mostly target web/mobile apps, using single- or dual-agent setups that overload one or two models with perception, planning, action selection, and validation at once, prone to hallucinations and unproductive exploration loops given infotainment complexity. We present ARIA (Autonomous Real-time Infotainment Ass
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-04T09:18:01.000Z
First collected: 2026-09-20T22:31:48.298Z. This is not the publication date.