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A car driver’s cognitive distraction is a main factor behind car accidents. One’s state of mind is subconsciously exposed as a reaction reflecting it by external stimuli. A visual event that occurs in front of the driver when a peripheral vehicle overtakes the driver’s vehicle is regarded as the external stimulus. We focus on temporal relationships between the driver’s eye gaze and the peripheral vehicle behavior. The analysis result showed that the temporal relationships depend on the driver’s state. In particular we confirmed that the timing of the gaze toward the stimulus under the distracted state induced by a music retrieval task using an automatic speech recognition system is later than that under a neutral state while only driving without the secondary cognitive task. This temporal feature can contribute to detecting the cognitive distraction automatically. A detector based on a Bayesian framework using this feature achieves better accuracy than one based on the percentage road center method.

Analysis of Temporal Relationships between Eye Gaze and Peripheral Vehicle Behavior for Detecting Driver Distraction