Spatial-Temporal Analysis of Injury Severity with Geographically Weighted Panel Logistic Regression Model
Joint Authors
Xiao, Daiquan
Xu, Xuecai
Duan, Li
Source
Journal of Advanced Transportation
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-08-20
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
This study is intended to investigate the influencing factors of injury severity by considering the heterogeneity issue of unobserved factors at different arterials and the spatial attributes in geographically weighted regression models.
To achieve the objectives, geographically weighted panel logistic regression model was developed, in which the geographically weighted logistic regression model addressed the injury severity from the spatial perspective, while the panel data model accommodated the heterogeneity attributed to unobserved factors from the temporal perspective.
The geo-crash data of Las Vegas metropolitan area from 2014 to 2016 was collected, involving 27 arterials with 25,029 injury samples.
By comparing the conventional logistic regression model and geographically weighted logistic regression models, the geographically weighted panel logistic regression model showed preference to the other models.
Results revealed that four main factors, human-beings (drivers/pedestrians/cyclists), vehicles, roadway, and environment, were potentially significant factors of increasing the injury severity.
The findings provide useful insights for practitioners and policy makers to improve safety along arterials.
American Psychological Association (APA)
Xiao, Daiquan& Xu, Xuecai& Duan, Li. 2019. Spatial-Temporal Analysis of Injury Severity with Geographically Weighted Panel Logistic Regression Model. Journal of Advanced Transportation،Vol. 2019, no. 2019, pp.1-15.
https://search.emarefa.net/detail/BIM-1170190
Modern Language Association (MLA)
Xiao, Daiquan…[et al.]. Spatial-Temporal Analysis of Injury Severity with Geographically Weighted Panel Logistic Regression Model. Journal of Advanced Transportation No. 2019 (2019), pp.1-15.
https://search.emarefa.net/detail/BIM-1170190
American Medical Association (AMA)
Xiao, Daiquan& Xu, Xuecai& Duan, Li. Spatial-Temporal Analysis of Injury Severity with Geographically Weighted Panel Logistic Regression Model. Journal of Advanced Transportation. 2019. Vol. 2019, no. 2019, pp.1-15.
https://search.emarefa.net/detail/BIM-1170190
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1170190