Exploiting Surrogate Safety Measures and Road Design Characteristics towards Crash Investigations in Motorway Segments
نویسندگان
چکیده
High quality data on road crashes, design characteristics, and traffic are typically required to predict crash frequency. Surrogate Safety Measures (SSMs) an alternative category of indicators that can be used in safety analyses order quantify various unsafe events. The objective this research is exploit geometry SSMs toward investigations motorway segments. To end, for analysis, a database containing injury property-damage-only 668 segments was compiled utilized. results the developed negative binomial regression model revealed frequency positively correlated with average annual daily volume, length segment, harsh accelerations, braking. Moreover, four distinct clusters representing risk levels examined emerged from hierarchical clustering procedure, ranging more risk-prone, potentially locations safe locations. These also formed response variable classes random forest model. This classification as predictors achieved high performance all classes, averaging than 88% correct rates.
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ژورنال
عنوان ژورنال: Infrastructures
سال: 2023
ISSN: ['2412-3811']
DOI: https://doi.org/10.3390/infrastructures8030040