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Title:

Spatial Analysis of Fatal and Injury Crashes in Flanders, Belgium: Application of Geographically Weighted Regression Technique

Accession Number:

01475839

Record Type:

Component

Availability:

Transportation Research Board Business Office

500 Fifth Street, NW
Washington, DC 20001 United States

Abstract:

Generalized Linear Models (GLMs) are the most widely used models utilized in crash prediction studies. These models illustrate the relationships between the dependent and explanatory variables by estimating fixed global estimates. Since the crash occurrences are often spatially heterogeneous and are affected by many spatial variables, the existence of spatial correlation in the data is examined by means of calculating Moran’s I measures for dependent and explanatory variables. The results indicate the necessity of considering the spatial correlation when developing crash prediction models. The main objective of this research is to develop different Zonal Crash Prediction Models (ZCPMs) within the Geographically Weighted Generalized Linear Models (GWGLM) framework in order to explore the spatial variations in association between Number of Injury Crashes (NOICs) (including fatal, severely and slightly injury crashes) and other explanatory variables. Different exposure, network and socio-demographic variables of 2200 Traffic Analysis Zones (TAZs) are considered as predictors of crashes in the study area, Flanders, Belgium. To this end, an activity-based transportation model framework is applied to produce exposure measurements while the network and socio-demographic variables are collected from other sources. Crash data used in this study consist of recorded crashes between 2004 and 2007. GWGLMs are developed using a Poisson error distribution and are often referred to as Geographically Weighted Poisson Regression (GWPR) models. Moreover, the performances of developed GWPR models are compared with their corresponding GLMs. The results show that GWPR models outperform the GLM models; this is due to the capability of GWPR models in capturing the spatial heterogeneity of crashes.

Supplemental Notes:

This paper was sponsored by TRB committee ANB20 Safety Data, Analysis and Evaluation.

Monograph Accession #:

01470560

Report/Paper Numbers:

13-1049

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Pirdavani, Ali
Brijs, Tom
Bellemans, Tom
Wets, Geert

Pagination:

18p

Publication Date:

2013

Conference:

Transportation Research Board 92nd Annual Meeting

Location: Washington DC, United States
Date: 2013-1-13 to 2013-1-17
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References; Tables

Geographic Terms:

Flanders (Belgium)

Subject Areas:

Highways; Safety and Human Factors; I80: Accident Studies

Source Data:

Transportation Research Board Annual Meeting 2013 Paper #13-1049

Files:

TRIS, TRB, ATRI

Created Date:

Feb 5 2013 12:18PM