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Investigation of injury severities in single-vehicle crashes in North Carolina using mixed logit models
- Source :
- Journal of Safety Research. 77:161-169
- Publication Year :
- 2021
- Publisher :
- Elsevier BV, 2021.
-
Abstract
- Introduction Roadway departure (RwD) crashes, comprising run-off-road (ROR) and cross-median/centerline head-on collisions, are one of the most lethal crash types. According to the FHWA, between 2015 and 2017, an average of 52 percent of motor vehicle traffic fatalities occurred each year due to roadway departure crashes. An avoidance maneuver, inattention or fatigue, or traveling too fast with respect to weather or geometric road conditions are among the most common reasons a driver leaves the travel lane. Roadway and roadside geometric design features such as clear zones play a significant role in whether human error results in a crash. Method: In this paper, we used mixed-logit models to investigate the contributing factors on injury severity of single-vehicle ROR crashes. To that end, we obtained five years' (2010–2014) of crash data related to roadway departures (i.e., overturn and fixed-object crashes) from the Federal Highway Administration's Highway Safety Information System Database. Results: The results indicate that factors such as driver conditions (e.g., age), environmental conditions (e.g., weather conditions), roadway geometric design features (e.g., shoulder width), and vehicle conditions significantly contributed to the severity of ROR crashes. Conclusions: Our results provide valuable information for traffic design and management agencies to improve roadside design policies and implementing appropriately forgiving roadsides for errant vehicles. Practical applications: Our results show that increasing shoulder width and keeping fences at the road can reduce ROR crash severity significantly. Also, increasing road friction by innovative materials and raising awareness campaigns for careful driving at daylight can decrease the ROR crash severity.
- Subjects :
- Male
Automobile Driving
Human error
Poison control
Crash
Transport engineering
Injury Severity Score
Mixed logit
0502 economics and business
North Carolina
Humans
Single vehicle
0501 psychology and cognitive sciences
Daylight
Crash data
Safety, Risk, Reliability and Quality
050107 human factors
050210 logistics & transportation
05 social sciences
Accidents, Traffic
Building and Construction
Motor Vehicles
Logistic Models
Geometric design
Environmental science
Female
Subjects
Details
- ISSN :
- 00224375
- Volume :
- 77
- Database :
- OpenAIRE
- Journal :
- Journal of Safety Research
- Accession number :
- edsair.doi.dedup.....e2eb1570f7ec3ce8c1fb9dbf659238a6