Examining collision avoidance behavior of distracted drivers: A correlated grouped random parameters accelerated failure time model with heterogeneity-in-means

Current research mostly studied the driving behavior of distracted drivers in abrupt situations, but different types of distraction may lead to differential crash risks, particularly during collision avoidance, which has been overlooked in the literature. As such, this study investigated and compared drivers' collision avoidance performance under different distraction conditions. Forty-four licensed drivers completed driving simulation experiments under normal driving, cognitive distraction, and manual distraction conditions. To comprehend the collision avoidance behavior under different distraction conditions, this study analyzed hazard response time, deceleration time, and collision avoidance time-critical components in avoiding secondary collisions. For these performance measures, correlated grouped random parameters accelerated failure time models were developed, considering repeated experiment design and unobserved heterogeneity. Results indicate that drivers in manual distraction took more time to respond during the hazard response phase compared to cognitive distraction. The majority of distracted drivers were observed to spend less time decelerating and avoiding collisions than in normal driving conditions, indicating a risk compensation behavior. Further, this study found that gender was associated with differential increase in collision avoidance time, with male drivers having longer collision avoidance time under manual distraction than female drivers and female drivers having longer collision avoidance time under cognitive distraction than male drivers. Overall, this study provides insights into collision avoidance behavior and aids in developing automated collision avoidance assistance systems.

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Publication Details

Journal
Accident Analysis & Prevention
Published
2025-03-23
DOI
https://doi.org/10.1016/j.aap.2025.108016
Citations
5
Primary Topic
Traffic and Road Safety
Type
article
Field-Weighted Citation Impact
6.52

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article

Examining collision avoidance behavior of distracted drivers: A correlated grouped random parameters accelerated failure time model with heterogeneity-in-means

Yasir Ali, Yongjun Shen, Md. Mazharul Haque, Qikai Qu et al.
5 citations
Accident Analysis & Prevention
Traffic and Road Safety
6.52
article

Examining collision avoidance behavior of distracted drivers: A correlated grouped random parameters accelerated failure time model with heterogeneity-in-means

Yasir Ali, Yongjun Shen, Md. Mazharul Haque, Qikai Qu, Qiong Bao
article en
5 citations

Abstract

Current research mostly studied the driving behavior of distracted drivers in abrupt situations, but different types of distraction may lead to differential crash risks, particularly during collision avoidance, which has been overlooked in the literature. As such, this study investigated and compared drivers' collision avoidance performance under different distraction conditions. Forty-four licensed drivers completed driving simulation experiments under normal driving, cognitive distraction, and manual distraction conditions. To comprehend the collision avoidance behavior under different distraction conditions, this study analyzed hazard response time, deceleration time, and collision avoidance time-critical components in avoiding secondary collisions. For these performance measures, correlated grouped random parameters accelerated failure time models were developed, considering repeated experiment design and unobserved heterogeneity. Results indicate that drivers in manual distraction took more time to respond during the hazard response phase compared to cognitive distraction. The majority of distracted drivers were observed to spend less time decelerating and avoiding collisions than in normal driving conditions, indicating a risk compensation behavior. Further, this study found that gender was associated with differential increase in collision avoidance time, with male drivers having longer collision avoidance time under manual distraction than female drivers and female drivers having longer collision avoidance time under cognitive distraction than male drivers. Overall, this study provides insights into collision avoidance behavior and aids in developing automated collision avoidance assistance systems.

Accident Analysis & PreventionVol. 215
Loughborough University (GB), Queensland University of Technology (AU), Southeast University (BD), Southeast University (CN)
National Natural Science Foundation of China, China Scholarship Council, Humanities and Social Sciences Youth Foundation, Ministry of Education of the People's Republic of China
Openalex Percentile: Top 4%
Traffic and Road Safety
6.52
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