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Human drivers are requested by the Automated Vehicle (AV) to perform takeover actions if needed. Existing research mainly focuses on predicting the takeover quality due to distraction using wearable sensor data. It is unrealistic, unnatural, and inapplicable to require human drivers to wear these sensors when driving an AV so that their situational awareness for takeover actions can be continuously monitored. Moreover, traffic conflicts can be observed even if drivers take over as requested. Current practice mainly develops conflict-actuated collision avoidance systems that alert drivers once the traffic conflict reaches a certain threshold. There is a research need to anticipate conflicts other than by measuring them. Besides, drivers are still responsible for responding to the alerts, which leaves the possibility of resulting in human error-related safety issues. This research aims at developing a Non-intrusive, Ultra …