1) Artificial Intelligence – vehicle-level logic
- Planning & Scheduling
Example: Tesla Model 3 Trip Planner + scheduled OTA software updates (user can choose an installation time in the car UI). Tesla+1
- Knowledge Representation
Example: EV battery maintenance recommendation systems that analyse sensor data and then generate service suggestions using rule-based logic on top of neural-network outputs. Google Patents
- Natural Language Processing (NLP) – foundation for the In-Vehicle Agent
Example: BMW Intelligent Personal Assistant (“Hey BMW”) in many BMW models, which uses natural, conversational voice control for navigation, infotainment and vehicle functions. BMW UK+1
- Computer Vision – umbrella for AI Perception
Example: Tesla Autopilot / Tesla Vision uses camera-only computer vision and neural networks for perception (lanes, vehicles, traffic lights). Comet+1
- Expert Systems (rule- / knowledge-based diagnostics)
Example: EV battery predictive-maintenance systems that run neural nets plus rule-based logic to recommend service intervals. Google Patents+1
- AI Ethics & Safety (FuSa, HARA/TARA)
Note: These are process and governance frameworks applied across most modern ADAS vehicles, rather than a single “feature” in one model.