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Inicio  /  Applied Sciences  /  Vol: 13 Par: 20 (2023)  /  Artículo
ARTÍCULO
TITULO

Investigating Highway?Rail Grade Crossing Inventory Data Quality?s Role in Crash Model Estimation and Crash Prediction

Muhammad Umer Farooq and Aemal J. Khattak    

Resumen

In this study, the impact of errors and missing information in the inventory data of highway?rail grade crossings (HRGCs) on the crash frequency prediction models currently used in the US is investigated. Transportation authorities and safety regulators can apply the insights gained from this research to enhance the accuracy of crash frequency prediction models for HRGCs. By utilizing more accurate and complete inventory data, these models provide more reliable crash frequency predictions, enabling better resource allocation and more targeted safety interventions.

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