Preprint Article Version 1 This version is not peer-reviewed

Pedestrian Injury Severity Analysis in Motor Vehicle Crashes in Ohio

Version 1 : Received: 3 April 2018 / Approved: 3 April 2018 / Online: 3 April 2018 (10:44:42 CEST)
Version 2 : Received: 27 April 2018 / Approved: 27 April 2018 / Online: 27 April 2018 (08:10:22 CEST)

A peer-reviewed article of this Preprint also exists.

Uddin, M.; Ahmed, F. Pedestrian Injury Severity Analysis in Motor Vehicle Crashes in Ohio. Safety 2018, 4, 20. Uddin, M.; Ahmed, F. Pedestrian Injury Severity Analysis in Motor Vehicle Crashes in Ohio. Safety 2018, 4, 20.

Journal reference: Safety 2018, 4, 20
DOI: 10.3390/safety4020020

Abstract

Background: According to the National Highway Traffic Safety Administration, 116 pedestrians were killed in motor vehicle crashes in Ohio in 2015. However, no study to date has analyzed crashes in Ohio exploring the factors contributing to the pedestrian injury severity resulting from motor vehicle crashes. This study fills this gap by investigating the crashes involving pedestrians exclusively in Ohio. Materials and Methods: This study uses the crash data from the Highway Safety Information System, from 2009 to 2013. The explanatory factors include the pedestrian, driver, vehicle, crash, and roadway characteristics. Both fixed- and random-parameters ordered probit models of injury severity (where possible outcomes are major, minor, and possible/no injury) were estimated. Results: The model results indicate that being older pedestrian (65 and over), younger driver (less than 24), driving under influence (DUI), being struck by truck, dark-unlighted roadways, six-lane roadways, and speed limit of 40 mph and 50 mph were associated with more severe injuries to the pedestrians. Conversely, older driver (65 and over), passenger car, crash occurring in urban locations, daytime traffic off-peak (10 AM to 3:59 PM), weekdays, and daylight condition were associated with less severe injuries. Conclusion: This study provides specific safety recommendations so that effective countermeasures could be developed and implemented by the policy makers, which in turn will improve overall highway safety.

Subject Areas

pedestrian safety; crash severity; crash factors; ordered probit model; random parameter model

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