David Kidd is a third year doctoral student under the advisement of Dr. Christopher Monk. He received his Master's of Arts in Human Factors at George Mason University in 2008 and his Bachelor's of Science degree in Psychology at Virginia Tech in 2006.

Current Work

Driver Cognition

David is studying various aspects of driver distraction and cognition. Recently, he explored the central bottleneck theory in stop and go responses to yellow light changes. David is now beginning work on characterizing how distractions affect drivers stop and go decisions in the dilemma zone. He will also continue work he began during a fellowship at Liberty Mutual's Research Institute for Safety that compared drivers' perceptions of distracted driving performance to actual distracted driving performance.

Advanced Collision Warning Systems

David is currently working on topics related to the effectiveness of advanced collision warning systems (ACWS). The goal of this work is to identify the current features and specifications of ACWS that are available in today's automobiles. This information will be combined with previous empirical findings to develop a series of studies to test the effectiveness of different types of alerts, test alert effectiveness over time, probe issues related to transfer, and potentially answer a number of other questions.

Individual Differences

David is also interested in using generalizability theory as a method to quantify sources of variation as a means for improving the effectiveness of experimental design. His current work in this area is on identifying how generalizability theory can be used in Human Factors research to measure the effectiveness of experimental manipulations and controls.