Spatial Analysis to Identify Pedestrian Crash Zones: A Case Study of School Zones in Thailand
Somluk Bunnarong*, Prapatpong Upala
Identifiers and Pagination:Year: 2018
First Page: 167
Last Page: 181
Publisher Id: TOTJ-12-167
Article History:Received Date: 23/2/2018
Revision Received Date: 26/3/2018
Acceptance Date: 06/5/2018
Electronic publication date: 24/05/2018
Collection year: 2018
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
In Thailand, it has the second highest road traffic fatality rate in the world at 36.2 deaths per 100,000 populations. The pedestrian crash zones are based on the road and physical environment, vehicle and driver behavior and pedestrian behavior, especially the area around the school. Therefore, this paper would like to improve safety by identifying crash area through Geographic Information Systems (GIS).
The objective of this paper is to identify pedestrian crash zones of primary schools and secondary schools in Bangkok, Thailand through the spatial analysis and GIS tool.
The research methodology was the data collection from pedestrian-vehicle crashes in 2016 at 12 schools of 1,218 locations in Bangkok. The data analysis used GIS for geocoding the crash locations. The spatial patterns and pedestrian crash zone map were applied by Moran’s I statistic and the Kernel Density Estimation (KDE).
The Moran’s index showed that the accident locations within school zone were a clustered pattern considering on Moran’s Index which approached +1 and the z-scores greater than 2.58. The KDE showed that the pedestrian crash zones were different depending on the physical environment; however, the most significant areas were at urban areas, crowded areas, and intersections of arterial roads and local roads about 508 meters from the school center.
This research could be concluded that the spatial patterns and pedestrian crash zone map will assist the transportation planners and traffic police for identifying crash locations and specific vulnerable road users, especially pedestrians and bicycle users.