A multimedia corpus of driving behaviors

In this paper we present our multimedia corpus of real-world driving data (NUDrive), built with the primary objective of firming foundations for applying digital signal processing technologies in the vehicular environment. NUDrive is a content rich corpus composed of driving, speech, video, and physiological signals. So far, we have collected data from 250 drivers, who drove an instrumented vehicle under very similar conditions. In order to provide a more meaningful description of the situations drivers experience, a comprehensive data annotation protocol is proposed. We also briefly present a multimedia processing system, which uses information from various sources in NUDrive to implement a context-dependent estimation of a driver's spontaneous frustration. Results are encouraging and stress the relevance of content rich driving corpora to driver behavior modeling.