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Uncovering latent structures of crash typology in narcotic-involved fatal crashes for safe system interventions

delete2026-01-21
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OA
AI
A
Anannya Ghosh Tusti *
T
Tausif Islam Chowdhury
M
Md Monzurul Islam
M
Mahmuda Sultana Mimi
S
Subasish Das
DOI:10.1016/j.aap.2025.108382delete
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Abstract

Abstract

En 中文
Narcotic-impaired driving increases the risk of fatal crashes, yet existing studies rarely provide narcotic-specific crash typologies that link driver impairment to roadway, traffic, and environmental conditions. This gap limits the design of Safe System interventions that can proactively address the most common high-risk configurations. Using Fatality Analysis Reporting System data from 2018 to 2022, this study applies Cramer's V statistic for variable selection and Cluster Correspondence Analysis (CCA) to explore unsupervised crash typologies and latent patterns of narcotics-involved fatal crashes. CCA biplot coordinates group crashes into four clusters: highspeed lane changes on uncontrolled arterials, run-off-road impacts with rollovers, nighttime pedestrian or cyclist strikes on unlit roads, and moderate-speed angle crashes at signalized intersections. Results show that speed and lateral control failures dominate the first two clusters, narcotic-induced sensory and cognitive deficits under low visibility drive the third, and decision-making errors during turn phases characterize the fourth. Key factors such as posted speed limit, lighting condition, and driver age exert cluster-specific influences on incapacitating and fatal injury outcomes. These findings underscore the inadequacy of appropriate countermeasures and point to Safe System-aligned interventions, including dynamic speed management, enhanced roadside clear zones, targeted lighting upgrades, and intersection control strategies.
Keywords:
Narcotic-impaired driving
Cluster correspondence analysis
Crash severity
Speed management
Lighting conditions
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Accident Analysis and Prevention
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Texas State University System
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