Modeling a cognitive–behavioral pathway to drivers’ behavioral intention in response to tunnel auditory warnings under acoustic fluctuations

Tunnel roadside auditory warning systems are designed to deliver critical safety messages. In-cabin acoustic fluctuations, such as those caused by vehicle speed and window state, are considered important factors that may impair perceptual and cognitive processing. This study examines how these acoustic variations influence drivers’ detection, comprehension, and behavioral intention regarding auditory warnings. The study recreated ten distinct in-cabin acoustic environments by combining five vehicle speeds (0, 20, 40, 60, and 80 km/h) with two window states (closed/open). Real-world tunnel auditory warning recordings under these conditions were integrated into an audio-visual experimental platform. Thirty-six licensed drivers participated in this controlled experiment, during which multiple cognitive processing indicators were collected: auditory perception reaction time, speech intelligibility, listening effort, semantic comprehension, heart rate variability, and behavioral intention. A two-stage analytical approach was implemented: generalized estimating equations (GEE) were first used to assess how speed and window state affected warning detection, followed by structural equation modeling (SEM) to evaluate the relationships among the cognitive processing indicators. Vehicle speed and window state significantly affected warning detection, with performance declining notably above 60 km/h, especially under open-window conditions. Both auditory perception reaction time and speech intelligibility were substantially impaired as speed increased. Listening effort rose with increased speech intelligibility, though this relationship demonstrated a non-linear pattern. Semantic comprehension was strongly predicted by speech intelligibility and showed significant variation across different levels of listening effort. Crucially, key information comprehension emerged as the strongest direct predictor of behavioral intention, while listening effort exhibited both direct and indirect effects on intention. The structural equation model confirmed these relationships, revealing significant mediation pathways through listening effort and comprehension in the connection between perceptual processing and behavioral outcomes. This study shows that drivers’ responses to tunnel roadside auditory warnings cannot be explained by detectability alone. Post-detection cognitive factors, particularly speech intelligibility and key information comprehension, play a critical role in shaping drivers’ behavioral intention following successful perception of the warning. The findings underscore the relevance of incorporating drivers’ perceptual and cognitive responses when assessing roadside auditory warnings in complex tunnel environments.