RESEARCH ARTICLE


Spatial Analysis to Identify Pedestrian Crash Zones: A Case Study of School Zones in Thailand



Somluk Bunnarong*, Prapatpong Upala
Faculty of Architecture, King Mongkut’s Institute of Technology Ladkrabang (KMITL), Bangkok, Thailand


Article Metrics

CrossRef Citations:
0
Total Statistics:

Full-Text HTML Views: 2342
Abstract HTML Views: 1130
PDF Downloads: 436
ePub Downloads: 259
Total Views/Downloads: 4167
Unique Statistics:

Full-Text HTML Views: 1106
Abstract HTML Views: 508
PDF Downloads: 328
ePub Downloads: 174
Total Views/Downloads: 2116



© 2018 Bunnarong and Upala.

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.

* Address correspondence to this author at the Faculty of Architecture, King Mongkut’s Institute of Technology Ladkrabang (KMITL), Bangkok, Thailand; Tel: +6685-365-6455; E-mail: momja28@gmail.com


Abstract

Background:

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).

Objective:

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.

Method:

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).

Results:

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.

Conclusion:

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.

Keywords: Pedestrian crash zones, Spatial analysis, Kernel density estimation, Geographic information system, School zone, Bangkok.