Recognizing Behavioral Factors while Driving: A Real-World Multimodal Corpus to Monitor the Driver’s Affective State

Abstract

The presented study concentrates on the collection of emotional multimodal real-world in-car audio, video and physiological signal recordings while driving. To do so, three sensor systems were integrated in the car and four relevant emotional states of the driver were defined: neutral, positive, frustrated and anxious. To gather as natural as possible emotional data of the driver, the subjects needed to be unbiased and were therefore kept unaware of the detailed research objective. The emotions were induced using so-called Wizard-of-Oz experiments, where the drivers believed to be interacting with an automated technical system, which in fact was controlled by a human. Additionally, on board interviews while driving were conducted by an instructed psychologist. To evaluate the collected data, questionnaires were filled out by the subjects before, during and after the data collection. These included monitoring of the drivers perceived state of emotion, stress, sleepiness and thermal sensation but also detailed questionnaires on their driving experience, attitude towards technology and big five OCEAN personality traits. Afterwards, the data was annotated by expert labelers. Exemplary results of the evaluation of the experiments are given in the result section of this paper. They indicate that the emotional states were successfully induced and the annotation results are consistent for both performed annotation approaches.

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