Assessing the Influence of Pavement Performance on Road Safety Through Crash Frequency and Severity Analysis
Prathyush Kumar Reddy Lebaku, Lu Gao, Jingran Sun, Xingju Wang, Xuejian Kang

TL;DR
This study analyzes how pavement conditions influence road safety by examining crash frequency and severity, revealing that better-maintained roads and safety features reduce crashes and severity, emphasizing the importance of pavement maintenance.
Contribution
The paper introduces a comprehensive spatial and statistical analysis linking pavement performance to crash outcomes, utilizing machine learning and regression models with real-world data.
Findings
Higher speed limits increase crash frequency.
Well-maintained roads reduce crash severity.
Adverse weather conditions increase crash severity.
Abstract
Road safety is impacted by a range of factors that can be categorized into human, vehicle, and roadway/environmental elements. This research explores the connection between pavement performance and road safety, particularly in relation to crash frequency and severity, using data from the Iowa Department of Transportation (DOT) for 2022. By merging crash data with pavement inventory data, we conduct a spatial analysis that incorporates the geographical coordinates of crash sites with the conditions of road segments. Statistical methods are applied to compare crash rates and severity across various pavement condition categories. To identify the most influential factors affecting crash rates and severity, we use machine learning models along with negative binomial and ordered probit regression models. The study's key findings reveal that higher speed limits, well-maintained roads, and…
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