Mengjiao Wu, Xuesong Wang*, Ashleigh Filtness, Lishengsa Yue, Ziyuan Huang, Yujun Jiao
Abstract: In-vehicle fatigue warnings alert drivers when signs of fatigue are detected. These warnings can temporarily restore alertness, helping drivers respond before a crash occurs. They play a key role in reducing fatigue-related crash risk. However, the optimal loudness and effective duration of such warnings are not yet well understood. This study aims to analyze the effectiveness of auditory warnings from two perspectives: first, by employing the Kaplan-Meier method and the Random Survival Forest model to analyze alertness maintenance time across different warning loudness levels and to identify influencing factors. And second, by applying a Bayesian Cox proportional hazards model with random intercepts and slopes to examine individual differences in baseline alertness maintenance risk and sensitivity to 50 dB auditory warnings within the driver population. The results indicate that auditory warnings heighten drivers’ awareness of fatigue and extend the duration over which drivers maintain alertness following a warning. For mild task-related fatigue, one to three warnings produced an incremental benefit compared with no warning, as indicated by longer alertness maintenance. Compared to novice drivers, experienced drivers exhibited a higher baseline risk of reduced vigilance, greater sensitivity to the 50 dB warning, and a lower risk of post-warning fatigue. Overall, this study provides practical guidance for fatigue warning design and accounts for individual differences in alertness maintenance risk. It also introduces a new perspective for evaluating warning effectiveness based on alertness maintenance time.
引用：Mengjiao Wu, Xuesong Wang*, Ashleigh Filtness, Lishengsa Yue, Ziyuan Huang, Yujun Jiao. Loudness of in-Vehicle Auditory Warnings: Sustained Counteraction of Task-Related Driver Fatigue and Individual Differences in Alertness Maintenance. Accident Analysis & Prevention, Volume 227, March 2026, 108381.