Before revision:  The proposed approach measures the eye-movement of passive drivers to evaluate their responses to real-world rear-end collisions. The results show substantial individual differences in the eye fixation patterns by driving experience, even among fully attentive drivers.
After revision:  The proposed approach measures the eye-movement of passive drivers to evaluate their responses to real-world rear-end collisions. MEDIRL is composed of visual, driving, and attention modules. Given a front-view driving video and corresponding eye fixations from humans, the visual and driving modules extract generic and driving-specific visual features, respectively. Finally, the attention module learns the intrinsic task-sensitive reward functions induced by eye fixation policies recorded from attentive drivers.