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Journal Article

Citation

Sawtelle A, Shirazi M, Garder PE, Rubin J. J. Saf. Res. 2023; 84: 306-315.

Copyright

(Copyright © 2023, U.S. National Safety Council, Publisher Elsevier Publishing)

DOI

10.1016/j.jsr.2022.11.006

PMID

36868659

Abstract

INTRODUCTION: In Maine, lane departure crashes account for over 70% of roadway fatalities. The majority of roadways in Maine are rural. Moreover, Maine has aging infrastructure, houses the oldest population in the United States, and experiences the third coldest weather in the United States.

METHODS: This study analyzes the impact of roadway, driver, and weather factors on the severity of single-vehicle lane departure crashes occurring from 2017 to 2019 on rural roadways in Maine. Rather than using police reported weather, weather station data were utilized. Four facility types: Interstates, minor arterials, major collectors, and minor collectors were considered for analysis. The Multinomial Logistic Regression model was used for the analysis. The property damage only (PDO) outcome was considered as the reference (or base) category.

RESULTS: The modeling results show that the odds of a crash leading to major injury or fatality (KA outcome) increases by 330%, 150%, 243%, and 266% for older drivers (65 or above) compared to young drivers (29 or less) on Interstates, minor arterials, major collectors, and minor collectors, respectively. During the winter period (October to April), the odds of KA severity outcome (with respect to the PDO) decreases by 65%, 65%, 65%, and 48% on Interstates, minor arterials, major collectors, and minor collectors, respectively, presumably due to reduced speeds during winter weather events.

CONCLUSION: In Maine, factors such as older drivers, operating under the influence, speeding, precipitation, and not wearing a seatbelt showed higher odds of leading to injury. PRACTICAL APPLICATIONS: This study provides safety analysts and practitioners in Maine a comprehensive study of factors that influence the severity of crashes in Maine at different facilities to improve maintenance strategies, enhance safety using proper safety countermeasures, or increase awareness across the state.


Language: en

Keywords

Crash severity; Crash data; Statistical analysis; Lane departure; Multinomial logit

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