ArticlePloS one2026
Pupillary dynamics during hands-off L2 driving and transitions of control under high cognitive load.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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12 authors.
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Abstract
Arousal plays a vital role in facilitating the human ability to respond flexibly in a goal-directed manner, and pupillometry offers a non-invasive window into arousal-related neural processes given the close relationship between pupil size and Locus Coeruleus-Norepinephrine (LC-NE) activity. Whilst pupillometry has been used to detect cognitive load in manual and automated driving, the dynamic relationship between pre-stimulus (baseline) pupillary state and task-evoked pupillary responses (TEPRs) has not been investigated in driving contexts. This is important because variability in baseline pupil size - itself influenced by cognitive demands such as non-driving related task engagement - may contribute to variability in TEPRs independently of how drivers respond to critical events. This driving simulator experiment aimed to establish whether pupillometry during hands-off Level 2 (L2) driving was a reliable indicator of cognitive load, and to examine whether relationships between pupillary dynamics and behaviour established in controlled laboratory paradigms generalise to applied tasks. The size and reactivity of drivers' (N = 38) pupils were measured during hands-off L2 driving with and without a cognitive load task, followed by critical and non-critical transitions of control. Analysis revealed that mean, not standard deviation, of pupil diameter was a reliable indicator of cognitive load. Furthermore, higher baseline pupil diameter was associated with smaller TEPRs, and this relationship persisted after correcting for regression to the mean artefacts - suggesting that pre-stimulus pupillary state genuinely constrains subsequent TEPRs. Limited evidence was found that TEPRs or pre-stimulus pupillary variability predicted driver reaction times, potentially reflecting the motoric variability inherent in naturalistic driving responses. Finally, more critical events were associated with larger pupil diameter, indicating that drivers were exerting greater effort to manage the transition. These results indicate that pupillometry is a useful measure of cognitive load and that laboratory-established pupillometric relationships extend, at least partially, to applied driving contexts, with implications for the development of Driver Monitoring Systems (DMS).
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