Standardized Agent-to-Human (A2H) Interaction Manifests
A2HCard specifies structured interaction metadata between in-vehicle AI agents and human occupants: declaring intent, risk levels, and confirmation boundaries through standardized, lightweight JSON-LD manifests rendered across head-up displays and cluster panels.
A2H Interaction Engine Zonal Architecture
Central Controller: A2H Interaction Engine — In-Cabin Manifest Renderer & HMI
Zonal Control Units & TSN Ring
- AR-HUD Spatial Projection Map
- Driver Gaze & Cognitive Load Filter
- Haptic Seat & Wheel Vibration Bus
- Voice Intent Confirmation Pipeline
- ISO 26262 Usability Safety Guard
Why Text-Only LLM Chatbots Fail Automotive Usability
Drivers cannot read multi-paragraph AI explanations while traveling at highway speeds. A2HCard defines micro-interaction manifests: structured visual cards combining glanceable iconography, decisive confidence metrics, and tactile haptic signatures that communicate autonomous intent in under 200 milliseconds.
Core Engineering Areas
- Structured JSON-LD Agent Cards — Defining standardized JSON-LD schemas allowing any onboard agent to publish action recommendations, cost impacts, and confirmation requirements.
- Cognitive Load & Gaze Adaptation — Monitoring driver pupillometry, head pose, and road complexity to suppress non-critical agent prompts during intense maneuvering.
- Haptic & Spatial Audio Signatures — Binding directional seat vibrations and 3D spatial audio chimes to agent decisions, confirming lane changes without requiring the driver to glance away.
Technical Articles
Related Cluster Architecture Specifications
- AutomotiveSDV — Full SDV Stack & Reference Architecture
- A2HumanCard — Standardized In-Vehicle AI Agent Capability Discovery, Trust & Authorization Cards
- AIDrivenSynBio — AI-Driven Synthetic Biology for Automotive In-Cabin Air Purification, Bio-Engineered Pathogen Scavengers & Molecular Biosensors
- AutomobileAgentic — Autonomous In-Vehicle Agentic AI & Deterministic Edge Execution