Abstract Driver Monitoring System (DMS), usually equipped with a camera, is an emerging
vehicle safety system that can monitor driver attentiveness and trigger timely alarms when …

To make safe transitions from autonomous to manual control, a vehicle must have a
representation of the awareness of driver state; two metrics which quantify this state are the …

Safe path planning in autonomous driving is a complex task due to the interplay of static
scene elements and uncertain surrounding agents. While all static scene elements are a …

Take-over performance plays a significant role in evaluating drivers' state, and serves as a
crucial reference for enhancing control transitions in the context of conditionally automated …

Autonomous vehicles are the near future of the automobile industry. However, until they
reach Level 5, humans and cars will share this intermediate future. Therefore, studying the …

Multi-sensor frameworks provide opportunities for ensemble learning and sensor fusion to
make use of redundancy and supplemental information, helpful in real-world safety …

Driver activity classification is crucial for ensuring road safety, with applications ranging from
driver assistance systems to autonomous vehicle control transitions. In this paper, we …

Vehicle light detection, association, and localization are required for important downstream
safe autonomous driving tasks, such as predicting a vehicle's light state to determine if the …

Understanding occupant-vehicle interactions by modeling control transitions is important to
ensure safe approaches to passenger vehicle automation. Models which contain contextual …

Advanced Driver Assistance Systems (ADAS) in intelligent vehicles rely on accurate driver
perception within the vehicle cabin, often leveraging a combination of sensing modalities …