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Title:

Pedestrian Injury Severity in Motor Vehicle Crashes: An Integrated Spatio-Temporal Modeling Approach

Accession Number:

01698103

Record Type:

Component

Abstract:

Traffic crashes are outcomes of human activities interacting with the diverse cultural, socio-economic and geographic contexts, presenting a spatial and temporal nature. This study employs an integrated spatio-temporal modeling approach to untangle the crashed injury correlates that may vary across the space and time domain. Specifically, this study employs Geographically and Temporally Weighted Ordinal Logistic Regression (GTWOLR) to tackle the correlates of pedestrian injury severity in motor vehicle crashes. The method leverages the space- and time-referenced crash data and powerful computational tools. This study performed non-stationarity tests to verify whether the local correlates of pedestrian injury severity from GTWOLR have a significant spatio-temporal variation. Results showed that some variables passed the tests, indicating they have significantly varying relationships with pedestrian injury severity. These factors include pedestrian age, pedestrian position, crash location, motorist age and gender, DUI, motor vehicle type and the crash time in a day. The spatially and temporally varying correlates of pedestrian injury severity are valuable for researchers and practitioners who develop pedestrian safety improvement solutions. For example, results showed that DUI crashes in the city of Charlotte and Asheville are more likely to cause severe pedestrian injuries than same crashes in other areas; and DUI crashes are associated with an increasing likelihood of causing severe pedestrian injuries. Therefore, DUI may be a near-future focus for pedestrian safety improvements in North Carolina and especially for the city of Charlotte and Asheville. More implications can be drawn from the modeling results.

Supplemental Notes:

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

Report/Paper Numbers:

19-01140

Language:

English

Corporate Authors:

Transportation Research Board

Authors:

Liu, Jun
Hainen, Alex
Nambisan, Shashi

Pagination:

9p

Publication Date:

2019

Conference:

Transportation Research Board 98th Annual Meeting

Location: Washington DC, United States
Date: 2019-1-13 to 2019-1-17
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References (26) ; Tables

Subject Areas:

Highways; Pedestrians and Bicyclists; Safety and Human Factors

Source Data:

Transportation Research Board Annual Meeting 2019 Paper #19-01140

Files:

TRIS, TRB, ATRI

Created Date:

Dec 7 2018 9:46AM