Dynamic Workload Measurement and Modeling Driving and Conversing

Tillman et al. (2017) used evidence-accumulation modeling to ascertain the effects of a conversation (either with a passenger or on a hands-free cell phone) on a drivers’ mental workload. They found that a concurrent conversation increased the response threshold but did not alter the rate of evidence accumulation. However, this earlier research collapsed across speaking and listening components of a natural conversation, potentially masking any dynamic fluctuations associated with this dual-task combination. In the present study, a unique implementation of the Detection Response Task was used to simultaneously measure the demands on the driver and the non-driver when they were speaking or when they were listening. We found that the natural ebb and flow of a conversation altered both the rate of evidence accumulation and the response threshold for drivers and non-drivers alike. The dynamic fluctuations in cognitive workload observed with this novel method illustrate how quickly the parameters of cognition are altered by real-time task demands.