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Translating Driving Research from Simulation to Interstate Driving with Realistic Traffic and Passenger Interactions

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Advances in Human Factors in Simulation and Modeling (AHFE 2018)

Abstract

In this driving study, participants were assigned to a driver-passenger dyad and performed two drives along Interstate-95 in normal traffic conditions. During the driving session, the driver had to safely navigate the route while listening and discussing news stories that were relayed by the passenger. The driver then performed a set of memory tasks to evaluate how well they retained information from the discussion in a multitask context. We report preliminary analyses that examined subjective factors which may influence success in social communication, including trait and state similarity derived from questionnaires as well as physiological synchrony from implicit state measurements derived from brain activity data. Although this dataset is still in collection, these initial findings suggest potential metrics that capture the contextual complexity in naturalistic, multitask environments, providing a rich opportunity to study how successful communication reflects shared social and emotional experiences.

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Correspondence to Jean M. Vettel .

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Vettel, J.M. et al. (2019). Translating Driving Research from Simulation to Interstate Driving with Realistic Traffic and Passenger Interactions. In: Cassenti, D. (eds) Advances in Human Factors in Simulation and Modeling. AHFE 2018. Advances in Intelligent Systems and Computing, vol 780. Springer, Cham. https://doi.org/10.1007/978-3-319-94223-0_12

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