Spatial analysis methods for identifying hazardous locations on expressways in Korea
- Authors
- Park, S. H.; Jang, K.; Kim, D. -K.; Kho, S. -Y.; Kang, S.
- Issue Date
- 8월-2015
- Publisher
- SHARIF UNIV TECHNOLOGY
- Keywords
- Hazardous locations; Spatial interaction; Geographic information system; Geographically weighted regression; Kernel density estimation
- Citation
- SCIENTIA IRANICA, v.22, no.4, pp.1594 - 1603
- Indexed
- SCIE
SCOPUS
- Journal Title
- SCIENTIA IRANICA
- Volume
- 22
- Number
- 4
- Start Page
- 1594
- End Page
- 1603
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/92820
- ISSN
- 1026-3098
- Abstract
- Identifying hazardous locations on highways is a fundamental step in safety improvement programs and projects since it provides decision makers with a basis for allocating budgets and other resources in a cost-effective manner. Extensive research has been conducted to identify such locations. However, most studies have ignored the spatial characteristics of crash occurrences and the relative significance of injury severity. In this study, we develop a procedure for identifying hazardous locations on expressways based on Geographically Weighted Regression (GWR) and Equivalent Property Damage Only (EPDO). GWR is a spatial regression method that can reflect spatial dependency and heterogeneous relationships between crash occurrences and other explanatory variables. EPDO is a comprehensive measure of crash occurrences weighted by the level of injury severity. We apply this procedure to a case study in Gyeongbu Expressway in Korea. The findings from our case study show that the procedure can identify hazardous locations on roadways while reflecting crash frequency and injury severity simultaneously with the comprehensive measure. (C) 2015 Sharif University of Technology. All rights reserved.
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Collections - College of Engineering > School of Civil, Environmental and Architectural Engineering > 1. Journal Articles
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