Adaptive Gain Theory Predicts Phasic Pupillary Dilations During Non-Critical Transitions of Control from Hands-Off L2 Driving Systems

Cognitive control plays a vital role in facilitating the human ability to respond flexibly in a goal-directed manner. Adaptive Gain Theory (AGT) posits that the Locus Coeruleus-Norepinephrine (LC-NE) system is implicated in this regulation and that pupillometry is a non-invasive indicator of LC activity. Most tests of AGT have focused on highly controlled cognitive and perceptual tasks, however it has been proposed that the LC-NE system plays a more general role in regulating the cortical based mechanisms involved in decision making. Non-critical transitions of control from SAE levels of automation to manual driving are a potentially useful testbed for complex decision-making processes that are mediated by this neuromodulatory system. To date, pupillometry has focused on the detection of mental workload (MWL) in the context of automated and manual driving. Therefore, this study had two general aims: to establish whether pupillometry during hands-off SAE Level 2 (L2) driving was a reliable and valid indicator of MWL, and to test the predictions of AGT in an applied context. The size and reactivity of drivers’ (N = 38) pupils were measured during hands-off SAE L2 driving with and without a MWL task, followed by non-critical transitions of control. Analysis revealed that mean, not standard deviation, of pupil diameter was a reliable indicator of MWL. However, neither measure correlated with subjective MWL assessments. Furthermore, interaction effects between MWL and the transition of control window revealed support for AGT predictions. These results indicate that pupillometry is a useful measure of MWL as well as an indication of the cognitive resource mobilisation needed to facilitate transitions of control. We discuss why subjective assessments of MWL rarely correlate with objective measures and the need to investigate neuroscientifically plausible mechanisms of cognitive control in the pursuit of valid and reliable Driver Monitoring Systems (DMS).