Comparative analysis of GIS aided methods to identify pedestrian crash hotspots in urban networks

Comparative analysis of GIS aided methods to identify pedestrian crash hotspots in urban networks

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Part of #Comparative analysis of GIS aided methods to identify pedestrian crash hotspots in urban networks# :

Publishing year : 2015

Conference : Fourteenth International Conference on Transport and Traffic Engineering

Number of pages : 15

Abstract: GIS is a popular tool for visualization of crash data and analysis of hotspots highway segments and intersections, hence in this study four GIS aidedmethods have been used as hotspot identification methods: K-means clustering, STAC, Nearest hierarchical clustering, And Kernel density method. Thisstudy used the data of pedestrian related crashes of district 11 of Tehran over ayear. These crashes resulted in 63 individual crash concentration zones for 276pedestrian crashes in the study area. Moreover, the results of using the above methods show that although each of these methods have different assumptions and procedures, their outputs are almost similar and have no significant difference.In the next step, to determine the identified hot spot and validation of the study, based on the minimum The required values of the crash frequency were developed by Poissondistribution in four levels. Intersection of Jomhuri and Valiasrstreets and south side of Qazvin sq. Were the most dangerous hotspotshaving 9 pedestrian crashes in a year and less than 0.5 percent occurrence probabability in normal conditions.