Rainy weather significantly affects traffic safety, especially in the State of Louisiana. With the aim of identifying the patterns of collective association of attributes in rainfall-involved crashes statewide, crashes that occurred during rainy weather and resulted in two injury groups, fatal and severe injury (FSI) and moderate injury (MI), were extracted from databases acquired from the Louisiana Department of Transportation and Development. A total of 3,381 crashes were extracted, comprising 502 FSI crashes (14.85%) and 2,879 MI crashes (85.15%). This study applied the cluster correspondence analysis (CCA) method, a unique method in combination with cluster analysis and correspondence analysis, to generate clusters by partitioning of individual attributes based on the profiles over the categorical variables identified through dimensional reduction of the dataset. In addition to the biplots illustrating the association of all attributes in the clusters, the top 20 standardized residuals indicating the stronger association are presented in bar plots. Four optimum clusters from FSI and MI crashes reveal that the association of roadway, crash environment, and driver condition characteristics identified in the clusters are highly distinguishable across roadway functional classes. Specifically, varieties of attributes linked to speed limit, lighting condition, alignment, area type, manner of collision, restraint usage, and alcohol/drug can have associative impacts on these two injury severities. The identified associations of crash attributes across various functional class roadways could provide valuable understanding for the development of countermeasures which prioritize the prevention of fatalities and injuries.


    Zugriff

    Download

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Using Cluster Correspondence Analysis to Explore Rainy Weather Crashes in Louisiana


    Weitere Titelangaben:

    Transportation Research Record


    Beteiligte:
    Ashifur Rahman, M. (Autor:in) / Das, Subasish (Autor:in) / Sun, Xiaoduan (Autor:in)


    Erscheinungsdatum :

    2022-03-03




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Exploring Attribute Associations in Pedestrian-Involved Hit-and-Run Crashes through Cluster Correspondence Analysis

    Rahman, M. Ashifur / Das, Subasish / Hossain, Ahmed et al. | Transportation Research Record | 2024


    Modeling Highway Safety and Simulation in Rainy Weather

    Jung, Soyoung | Online Contents | 2011


    Modeling Highway Safety and Simulation in Rainy Weather

    Jung, Soyoung / Qin, Xiao / Noyce, David A. | Transportation Research Record | 2011


    Risk of a road accident in rainy weather

    Brodsky, Harold / Hakkert, A.Shalom | Elsevier | 1987


    Injury Severity of Multivehicle Crash in Rainy Weather

    Jung, Soyoung | Online Contents | 2012