Cabin Human

Research on "cabin human" focuses on understanding and optimizing the human experience within enclosed spaces like vehicle cabins, primarily addressing occupant comfort and interaction with in-cabin systems. Current efforts utilize machine learning, particularly reinforcement learning and transformer-based architectures, to personalize cabin environments (e.g., adaptive lighting) and predict occupant behavior (e.g., driver intention prediction) from multi-sensor data. This research is significant for improving vehicle safety and comfort, as well as informing the design of more intuitive and user-friendly interfaces for autonomous vehicles and other enclosed environments.