UC Berkeley's Ruzena Bajcsy will present Modeling Human Distraction in the Car Due to Acoustic Annoyances at 4 p.m. Oct. 25 at the ITS Transportation Seminar in 290 Hearst Memorial Mining Building.
Abstract
In this presentation we shall review the predictability of safe driving with safety guarantees and investigate the effects of the driver state using a control theoretic driver’s model. For safe driving, others have used visual data, while auditory information has been neglected. Here, we explore the effect of sound and its annoyance on the driver with respect to safety considerations, using psychoacoustic parameters.
Presenter
During Ruzena Bajcsy’s 50 years of robotics research, she has pursued research in connecting perception and action, motivated by psychology (J.J. Gibson) and biology. She has investigated this line of research in several applications using different computational models, such as discrete event models and hybrid systems. This work was all done at the University of Pennsylvania’s GRASP laboratory. Upon arrival at UC Berkeley, she focused on modeling people, again using robotic technology, by modeling driver attention during driving, as well as in human-robot interaction. In both of these applications, she has found it necessary to employ planning, perception, and action. This project draws on recent work in animal behavioral studies, especially as they pertain to navigation. Moving forward, the project hopes to validate some algorithms that mimic related animal behavior.