Age and pedestrian injury severity in motor-vehicle crashes: A heteroskedastic logit analysis

The purpose of this paper is to identify and compare the contributing factors to bicyclist injury severity in urban and rural areas. Two mixed logit models are developed for both the urban and rural areas separately to identify factors that significantly contribute to the injury severity outcome of bicyclists resulting from bicycle–motor vehicle crashes. Data collected from 2007 to 2014 in North Carolina are utilized for the model development. The model estimation results show that factors including bicyclist age from 25 to 54, driver age under 25, vehicle speed, and divided road are found to significantly affect the injury severity outcome of bicyclists in bicycle–motor vehicle crashes in rural areas only. In contrast, factors including drivers age over 60, van, single unit truck, head-on crash, motorist overtaking bicyclist, two-way roadway, road condition, and crash time are found to have a significant impact on the injury severity of bicyclists in urban areas only.

Download Full-text

Pedestrian Injury Severity Analysis in Motor Vehicle Crashes in Ohio

10.20944/preprints201804.0035.v2 ◽

2018 ◽

Author(s):

Majbah Uddin ◽

Fahim Ahmed

Keyword(s):

Injury Severity ◽

Motor Vehicle ◽

Safety Information ◽

Highway Safety ◽

Motor Vehicle Crashes ◽

Vehicle Crashes ◽

Highway Traffic ◽

Severe Injuries ◽

National Highway Traffic Safety ◽

Pedestrian Injury

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.

Download Full-text

Pedestrian Injury Severity Analysis in Motor Vehicle Crashes in Ohio

10.20944/preprints201804.0035.v1 ◽

2018 ◽

Author(s):

Majbah Uddin ◽

Fahim Ahmed

Keyword(s):

Injury Severity ◽

Motor Vehicle ◽

Safety Information ◽

Highway Safety ◽

Motor Vehicle Crashes ◽

Vehicle Crashes ◽

Highway Traffic ◽

Severe Injuries ◽

National Highway Traffic Safety ◽

Pedestrian Injury

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.

Download Full-text

Random parameter probit models to analyze pedestrian red-light violations and injury severity in pedestrian–motor vehicle crashes at signalized crossings

Journal of Transportation Safety & Security ◽

10.1080/19439962.2018.1551257 ◽

2019 ◽

Vol 12 (6) ◽

pp. 818-837 ◽

Cited By ~ 8

Author(s):

Jie Wang ◽

Helai Huang ◽

Pengpeng Xu ◽

Siqi Xie ◽

S. C. Wong

Keyword(s):

Injury Severity ◽

Motor Vehicle ◽

Red Light ◽

Random Parameter ◽

Motor Vehicle Crashes ◽

Vehicle Crashes ◽

Probit Models

Download Full-text

Motor Vehicle Crashes Involving Railroad Crossing Signal Masts and Guardrails

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198119857952 ◽

2019 ◽

Vol 2673 (12) ◽

pp. 191-203

Author(s):

Justin D. Cyr ◽

John W. Shaw ◽

Peter T. Savolainen

Keyword(s):

United States ◽

Regression Models ◽

Injury Severity ◽

Motor Vehicle ◽

Motor Vehicle Crashes ◽

Future Research ◽

Vehicle Crashes ◽

Principal Element ◽

Crash Rates ◽

Serious Injuries

The installation of “active” warning devices, such as crossing signals and gates, is a principal element of state and federal railroad crossing safety programs, and their effectiveness in preventing vehicle–train collision is well documented. While most active crossings are occupied by trains only a few minutes each day, non-crashworthy items are frequently present at active crossings including crossing signal masts, crossing gate mechanisms, cantilever supports, and signal controller bungalows. Various agencies utilize longitudinal guardrail systems to protect errant motorists from striking non-frangible crossing signal hardware. This study sought to determine whether such guardrails influence the prevalence and severity of motor vehicle strikes involving crossing hardware. A review of 10 years of police crash-report narratives in Iowa, United States (U.S.) indicates an average of 15.6 crashes per year at 1,853 crossings involving signal masts, signal guardrails, or related infrastructure. Over this period, one fatality and five serious injuries occurred as a result of these crashes. The crash-injury severity distributions appeared similar in crashes with and without guardrail, and regression models showed that guardrail presence did not affect the rate of crashes involving railroad apparatus. Although the use of longitudinal guardrail systems did not appear to have a strong effect on crash rates or severity at active grade crossings, other methods for reducing crash prevalence and severity could be explored in future research, such as the development of crashworthy signal assemblies for flashing-signal-only crossings and the redesign of gate and cantilever supports to increase separation from the traveled way.

Download Full-text