Abstract
The data from World Health Organization and the National Highway Safety Administration show that traffic crash is the leading cause of death. In particular, the distracted driving behavior of young drivers (15–20 age) is identified as the main contributor to fatal crashes. Proper driving behaviors (e.g., keeping the vehicle within the lane, observing traffic signs) are regarded as complex activities that involve diverse cognitive processes such as attention, memory, vision, spatial orientation, and decision making. Therefore, it is imperative to explore how the cognitive processes related to the driving to understand the underpinnings of the driving behavior and ultimately develop various countermeasures to reduce fatal crashes. The advances in technology allowing the design of high-fidelity driving simulators and the wearable neuroimaging modalities have offered possibilities for the investigation of cognitive mechanisms of driving behavior in naturalistic settings, safely and effectively. This preliminary study examines an innovative approach to analyze the underlying cognitive activity changes among the young drivers while performing the driving task with and without a secondary task. In this study, the emerging sensing technologies, functional near infrared spectroscopy (fNIRS) and the state-of-art driving simulator were applied. Our initial results suggest that the driving and the chosen cognitive task conditions performed separately did not generate brain activations in prefrontal cortex (PFC) in young drivers. On the contrary, increased PFC activations were observed when driving and cognitive interference task were performed simultaneously. Furthermore, our study findings indicate that additional neural resources are required in the PFC during high speeds driving condition compared to the lower speeds case during dual task driving.
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Izzetoglu, M., Park, S. (2021). Exploring Relationship Between Driver’s Behavior and Cognitive Measures Observed by fNIRS in a Driving Simulator. In: Schmorrow, D.D., Fidopiastis, C.M. (eds) Augmented Cognition. HCII 2021. Lecture Notes in Computer Science(), vol 12776. Springer, Cham. https://doi.org/10.1007/978-3-030-78114-9_18
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DOI: https://doi.org/10.1007/978-3-030-78114-9_18
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