Driver injury severity in single-vehicle run off road crash on 2-lanes and 4-lanes highway in Thailand
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Abstract
The aim of this study was to identify factors such as: roadway operational characteristic, crash characteristic, surrounded environment, vehicle type, driver information, severity level of driver, and temporal information, affecting driver injury severity involving in single-vehicle run off road accident occurred on 2-lanes highways and 4-lanes highway using Multinomial Logit model. The analyses used secondary data obtained from police accident record (extracted from Highway Accident Information Management System (HAIMS)).The variables were found to increase chance of fatality are driver older than 55-year-old, driver under influence of alcohol, drowsiness driver, run off road on straight and curve, accident on highways with depressed median and accident on concrete pavement. The variables were found to mitigate severity are adult driver 25-35-year-old, using seat belt, accident on highway with raised median and hit fixed object accident. The contributions of this study were drawn: Thailand related authorities such as Department of Highway or Royal Thai Police should emphasize their effort on education campaigns on road safety for all road users, especially old drivers, enforce the law on drunk driving and seatbelt; and for road design perspective: monitor and build roadside safety features such as safety barrier alongside the highway particularly run off road black spot and curve roads. The study also mentions the safety benefit of asphalt pavement over concrete pavement and safety planner should consider implementing raised median in urban area for safety purpose.
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References
WHO. Global status report on road safety 2018. USA: World Health Organization; 2018.
Champahom T, Jomnonkwao S, Watthanaklang D, Karoonsoontawong A, Chatpattananan V, Ratanavaraha V. Applying hierarchical logistic models to compare urban and rural roadway modeling of severity of rear-end vehicular crashes. Accid Anal Prev. 2020;141:105537.
Wu Q, Zhang G, Zhu X, Liu XC, Tarefder R. Analysis of driver injury severity in single-vehicle crashes on rural and urban roadways. Accid Anal Prev. 2016;94: 35-45.
Kim JK, Ulfarsson GF, Kim S, Shankar VN. Driver-injury severity in single-vehicle crashes in California: a mixed logit analysis of heterogeneity due to age and gender. Accid Anal Prev. 2013;50:1073-81.
Xie Y, Zhao K, Huynh N. Analysis of driver injury severity in rural single-vehicle crashes. Accid Anal Prev. 2012;47:36-44.
Zhou M, Chin HC. Factors affecting the injury severity of out-of-control single-vehicle crashes in Singapore. Accid Anal Prev. 2019;124:104-12.
Bella F. Driver perception of roadside configurations on two-lane rural roads: effects on speed and lateral placement. Accid Anal Prev. 2013;50:251-62.
Awadzi KD, Classen S, Hall A, Duncan RP, Garvan C W. Predictors of injury among younger and older adults in fatal motor vehicle crashes. Accid Anal Prev. 2008;40:1804-10.
Kashani AT, Mohaymany AS. Analysis of the traffic injury severity on two-lane, two-way rural roads based on classification tree models. Saf Sci. 2011;49:1314-20.
Abegaz T, Berhane Y, Worku A, Assrat A, Assefa A. Effects of excessive speeding and falling asleep while driving on crash injury severity in Ethiopia: a generalized ordered logit model analysis. Accid Anal Prev. 2014;71:15-21.
Kaplan S, Prato CG. Risk factors associated with bus accident severity in the United States: A generalized ordered logit model. J Saf Res. 2012;43:171-80.
Yasmin S, Eluru N, Bhat CR, Tay R. A latent segmentation based generalized ordered logit model to examine factors influencing driver injury severity. Anal Methods Accid Res. 2014;1:23-38.
Wang X, Kockelman KM. Use of heteroscedastic ordered logit model to study severity of occupant injury: distinguishing effects of vehicle weight and type. Transport Res Rec. 2005;1908:195-204.
Wang X, Kockelman KM. Occupant injury severity using a heteroscedastic ordered logit model: distinguishing the effects of vehicle weight and type. the 84th Annual Meeting of the Transportation Research Board; 2005 Jan 9-13; Washington, USA. Washington: Mira Digital Pub; 2005.
Abdel-Aty M. Analysis of driver injury severity levels at multiple locations using ordered probit models. J Saf Res. 2003;34:597-603.
Chimba D, Sando T. Multinomial probability assessment of motorcycle injury severities. Adv Transport Stud. 2010;21:73-80.
Celik AK, Oktay E. A multinomial logit analysis of risk factors influencing road traffic injury severities in the Erzurum and Kars Provinces of Turkey. Accid Anal Prev. 2014;72:66-77.
Tay R, Choi J, Kattan L, Khan A. A multinomial logit model of pedestrian–vehicle crash severity. Int J Sustain Transp. 2011;5:233-49.
Savolainen PT, Mannering FL, Lord D, Quddus MA. The statistical analysis of highway crash-injury severities: a review and assessment of methodological alternatives. Accid Anal Prev. 2011;43:1666-76.
Schneider WH, Savolainen PT, Zimmerman K. Driver injury severity resulting from single-vehicle crashes along horizontal curves on rural two-lane highways. Transport Res Rec. 2009;2102(1):85-92.
Geedipally SR, Turner PA, Patil S. Analysis of motorcycle crashes in Texas with multinomial logit model. Transport Res Rec. 2011;2265(1):62-9.
Wu Q, Zhang G, Ci Y, Wu L, Tarefder RA, Alcántara AD. Exploratory multinomial logit model–based driver injury severity analyses for teenage and adult drivers in intersection-related crashes. Traffic Inj Prev. 2016;17(4):413-22.
Shankar V, Mannering F. An exploratory multinomial logit analysis of single-vehicle motorcycle accident severity. J Saf Res. 1996;27(3):183-94.
Chen Z, Fan WD. A multinomial logit model of pedestrian-vehicle crash severity in North Carolina. Int J Transport Sci Tech. 2019;8(1):43-52.
Ye F, Lord D. Comparing three commonly used crash severity models on sample size requirements: multinomial logit, ordered probit and mixed logit models. Anal Methods Accid Res. 2014;1:72-85.
Ratanavaraha V, Suangka S. Impacts of accident severity factors and loss values of crashes on expressways in Thailand. IATSS Res. 2014;37(2): 130-6.
Rifaat SM, Chin HC. Accident severity analysis using ordered probit model. J Adv Transport. 2007;41(1):91-114.
Weiss HB, Kaplan S, Prato CG. Analysis of factors associated with injury severity in crashes involving young New Zealand drivers. Accid Anal Prev. 2014;65:142-55.
Yau KK. Risk factors affecting the severity of single vehicle traffic accidents in Hong Kong. Accid Anal Prev. 2004;36(3):333-40.
Islam S, Mannering F. Driver aging and its effect on male and female single-vehicle accident injuries: Some additional evidence. J Saf Res. 2006;37(3):267-76.
Srinivasan KK. Injury severity analysis with variable and correlated thresholds: ordered mixed logit formulation. Transport Res Rec. 2002;1784(1):132-41.
Spainhour LK, Mishra A. Analysis of fatal run-off-the-road crashes involving overcorrection. Transport Res Rec. 2008;2069(1):1-8.
Li Y, Liu C, Ding L. Impact of pavement conditions on crash severity. Accid Anal Prev. 2013;59:399-406.
Garber NJ, Hoel LA. Traffic & Highway Engineering-SI Version. 5th Ed. USA: Cengage Learning; 2009.
Al-Bdairi NSS, Hernandez S. An empirical analysis of run-off-road injury severity crashes involving large trucks. Accid Anal Prev. 2017;102:93-100.
Schultz GG, Thurgood DJ, Olsen AN, Reese CS. Analyzing raised median safety impacts using Bayesian method. Transport Res Rec. 2011;2223(1):96-103.
Kockelman KM, Kweon YJ. Driver injury severity: an application of ordered probit models. Accid Anal Prev. 2002;34(3):313-21.
Liu C, Subramanian R. Factors related to fatal single-vehicle run-off-road crashes. USA: NHTSA; 2009.