Context-Sensitive Auditory Takeover Warning Under Weather and Scenario Demands: A Driving-Simulator Study with Eye-Tracking Evidence

Takeover safety remains a critical human-factors issue in conditionally automated driving because drivers must resume manual control under limited time and varying traffic conditions. This study examined how auditory alert urgency influences takeover safety under different weather and scenario conditions using a controlled driving-simulator experiment. Forty female licensed drivers completed a 3 × 2 × 2 within-subject design in OpenDS v.4.5 4.5, with three alert urgency levels, two weather conditions, and two representative takeover scenarios. Driving behavior and safety indicators were treated as the primary outcomes, while limited supplementary measures were retained as supporting evidence. Across the matched takeover tasks, alert urgency and scenario condition were associated with differences in takeover-related behavior and safety outcomes, whereas weather effects were more evident in subjective difficulty appraisal than in the main objective indicators. High-urgency alerts were perceived as the most urgent and the most helpful, whereas medium-urgency alerts showed the highest overall acceptability. Rainy weather and cut-in scenarios were consistently perceived as more demanding. Limited supplementary evidence provided selective support for interpreting the observed primary outcome patterns. These findings provide controlled simulator-based evidence for context-sensitive auditory warning design and takeover-support evaluation under combined environmental and scenario demands.