Before revision: A safe transition between autonomous and manual control requires sustained visual attentionof the driver for the perception and assessment of hazards in dynamic driving environments. Thus, drivers must retain a certain level of situation awareness to safely takeover. Understanding the visual attention allocation of drivers can pave the way for inferring their dynamic state of situational awareness.
After revision: Inspired by human visual attention, we introduce a Maximum Entropy Deep Inverse Reinforcement Learning (MEDIRL) framework for modeling the visual attention allocation of drivers can pave the way for inferring their dynamic state of situational awareness.