Its a long day and only now I got time to post on this interesting paper -
Human-Centered Autonomous Vehicle Systems
I love this paper for the practicality and applicability of this kind of systems. Autonomous Systems and Humans are dependent on each other to learn / teach and understand each other for Safer modes of transportation. In such situations systems have to share common responsibility and dependency to make the rides safer.
This paper underlines this important idea and the shared responsibility across multiple levels. Supervised learning, Personalization, better communication for Safer Navigation
Some key lines (copied from paper)
- Machine learning is primarily used for the scene understanding problem but not for any other aspect of the stack driving scene
- Perception, motion planning, driver sensing, speech recognition, and speech synthesis are all neural network models
- Calibrate distraction, fatigue, cognitive load, emotional state, and activity (uses facial landmark configuration and facial motion analysis)
- Communicate the degree of uncertainty in the neural network prediction, segmentation, or estimation about the state of driving scene
- Arguing machines framework (detailed in [12]) to provide human supervision over the primary perception-control system
Nice Lines
"both humans and AI systems have flaws, and only when the share autonomy paradigm is considered at the system level do those flaws have a chance to be leveraged to become strengths"
The same principles should apply for chatbots for better communication.
Happy Learning!!!
