Based on historical crash data, there is a growing concern about motor vehicle collisions involving pedestrians in South Carolina. Using pedestrian traffic crash records from 2010 to 2013, GIS spatial analysis was conducted using multiple geostatistical methods to identify pedestrian crash hotspots. The research goal was to identify clusters of pedestrians using kernel density estimation (KDE) and ordinary kriging analysis and make a comparison between these two methods. The resulting geostatistical models identified critical threshold zones prone to higher pedestrian crashes within urban areas. An analysis of the results indicated that the two methods were found to be moderately similar in identifying hotspots. Additional analysis is planned that focuses on identifying underlying causal factors common to the pedestrian crash hotspots. It is anticipated that the methodology and the developed criteria will provide traffic safety analysts an efficient approach to analyze pedestrian crash data, determine hot spots, and identify countermeasures that will have the highest cost/benefit.


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    Title :

    GIS Based Spatial Analysis of Pedestrian Crashes: A Case Study of South Carolina


    Contributors:

    Conference:

    International Conference on Transportation and Development 2018 ; 2018 ; Pittsburgh, Pennsylvania



    Publication date :

    2018-07-12




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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