Dynamic workload measurement and modeling: Driving and conversing

J Exp Psychol Appl. 2023 Sep;29(3):645-653. doi: 10.1037/xap0000431. Epub 2022 Jul 4.

Abstract

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 nondriver 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 nondrivers 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. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

MeSH terms

  • Attention / physiology
  • Automobile Driving* / psychology
  • Cell Phone*
  • Cognition
  • Humans
  • Workload