Investigation of injury severities in single-vehicle crashes in North Carolina using mixed logit models |
| |
| Affiliation: | 1. Laboratório Nacional de Engenharia Civil, Departamento de Transportes, Núcleo de Planeamento, Tráfego e Segurança Av. do Brasil 101, Lisboa 1700-066, Portugal;2. Department of Civil and Environmental Engineering, Rowan University, Glassboro, NJ 08028, United States;1. BMW Group, 80788 München, Germany;2. Technische Universität Chemnitz, 09107 Chemnitz, Germany;1. Center for Injury Research and Prevention, The Children''s Hospital of Philadelphia, 3535 Market Street, Suite 1150, Philadelphia, PA 19104 USA;2. Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine at the University of Pennsylvania, 423 Guardian Drive, Philadelphia, PA 19104 USA;3. Department of Pediatrics at the Perelman School of Medicine, University of Pennsylvania, 3620 Hamilton Walk, Philadelphia, PA 19104 USA;4. Department of Biostatistics, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109 USA;5. Survey Methodology Program, Institute for Social Research University of Michigan, Rm. 4068, 426 Thompson Street, Ann Arbor, MI 48109 USA;1. Lyles School of Civil Engineering, Purdue University, 550 Stadium Mall, West Lafayette, IN 47907-2051, USA;2. School of Highway, Chang’an University, Xi’an 710064, PR China;1. Virginia Tech Transportation Institute, 3500 Transportation Research Plaza, Blacksburg, VA 24060, United States;2. Virginia Polytechnic Institute and State University, 750 Drillfield Drive, 200 Patton Hall, Blacksburg, VA 24061, United States;1. Department of Transportation Engineering, Myongji University, 116 Myongji-ro, Yongin, 17058, South Korea;2. Department of Civil Engineering, Lassonde School of Engineering, York University, 4700 Keele Street, Toronto, Ontario, M3J 1P3, Canada;3. Department of Civil and Environmental Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea |
| |
| Abstract: | IntroductionRoadway 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. |
| |
| Keywords: | Roadway departure Run-off-road Mixed logit model Crash severity model |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
