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Roadway traffic crash during extreme heat days: insights from hazards-exposure-vulnerability-adaptation
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DOI：10.1016/j.aap.2025.108386.png)
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Abstract
En 中文
The escalating frequency of extreme heat events poses a potential threat to roadway safety, yet the spatial patterns of crash risk from more multi-dimensional perspectives remain underexplored. Using the HazardsExposure-Vulnerability-Adaptation paradigm, this study examines how traffic crash rates on extreme-heat days vary across roadway segments and road design characteristics in the City of Miami, Florida. This study analyzed traffic exposure and crash rates across three yearly extreme heat thresholds (90th, 95th, and 97th percentiles) from 2011 to 2015. A CatBoost model, interpreted via SHAP analysis, is used to identify key roadway and contextual features associated with higher or lower crash rates during extreme-heat days. The key findings are as follows: 1) Crash risk on extreme-heat days shows a threshold-dependent pattern across the examined percentiles. As the heat threshold intensifies from the 90th to the 97th percentile, the average network-wide crash rate increases, while the number of road segments with above-average crash rates follows a V-shaped pattern-first declining and then rising sharply at the highest threshold. This suggests that inherent adaptive characteristics of many roadways may be sufficient to moderate crash risk under moderately extreme heat but become increasingly inadequate once heat reaches very abnormally high threshold (e.g., the 97th percentile). 2) Models based on higher extreme-heat thresholds provide clearer insight into vulnerability patterns. Compared to the 90th and 95th percentile models, the 97th percentile model more clearly isolates roadway and contextual features most strongly associated with elevated crash rates on extreme-heat days, whereas lower thresholds appear more affected by noise from other coincident factors. 3) Roadway investment emerges as the primary adaptive factor associated with reduced risk. Physical attributes such as construction cost and geometric design are the most influential correlates of crash vulnerability on extreme-heat days, with higher-quality roadway investment linked to substantially lower crash rates. In contrast, the observed associations for safety control measures and emergency service accessibility are comparatively limited. These findings characterize which roadway environments are more vulnerable when extreme-heat conditions occur.
Keywords:
Extreme heat
Vulnerability
Adaptation
CatBoost model
Scenario analysis
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