5 citations · 20 across the 6 of their papers we have counts for
7 papers
Real-time Trust Prediction in Conditionally Automated Driving Using Physiological Measures
Jackie Ayoub, Lilit Avetisian, X. Jessie Yang +1
Trust calibration presents a main challenge during the interaction between drivers and automated vehicles (AVs). In order to calibrate trust, it is important to measure drivers' tr…
Disengagement Cause-and-Effect Relationships Extraction Using an NLP Pipeline
Yangtao Zhang, X. Jessie Yang, Feng Zhou
The advancement in machine learning and artificial intelligence is promoting the testing and deployment of autonomous vehicles (AVs) on public roads. The California Department of M…
Predicting Driver Takeover Time in Conditionally Automated Driving
Jackie Ayoub, Na Du, X. Jessie Yang +1
It is extremely important to ensure a safe takeover transition in conditionally automated driving. One of the critical factors that quantifies the safe takeover transition is takeo…
Predicting Driver Fatigue in Automated Driving with Explainability
Feng Zhou, Areen Alsaid, Mike Blommer +5
Research indicates that monotonous automated driving increases the incidence of fatigued driving. Although many prediction models based on advanced machine learning techniques were…
Modeling Dispositional and Initial learned Trust in Automated Vehicles with Predictability and Explainability
Jackie Ayoub, X. Jessie Yang, Feng Zhou
Technological advances in the automotive industry are bringing automated driving closer to road use. However, one of the most important factors affecting public acceptance of autom…
Psychophysiological responses to takeover requests in conditionally automated driving
Na Du, X. Jessie Yang, Feng Zhou
In SAE Level 3 automated driving, taking over control from automation raises significant safety concerns because drivers out of the vehicle control loop have difficulty negotiating…