Document Type : Research Paper
Authors
1 Roads and Transport Department, College of Engineering, University of Al-Qadisiyah, Iraq
2 Texas A&M Transportation Institute, 1111 RELLIS Parkway, Bryan, TX 77807, United States
Abstract
One of the worst epidemics that endangers our life and has an impact on the future is the epidemic of road accidents. The goal of this study is to define traffic accidents, comprehend their causes, pinpoint the key elements that affect the seriousness of driver injuries, and ultimately identify the factors that contribute to accidents, such as excessive speed, alcohol, and drug use, the driver, the road, the vehicle, and environmental factors. Understanding prior research and studies is crucial. In earlier experiments, data visualization was accomplished using the VOS viewer. The Dimension, Web of Science, and Scopus websites were used to download the information for the keywords in Excel format. By country, it lists these terms, authors, and researchers. The researcher was able to conduct a study that was identical to his or her study with the aid of the keywords " driver injury severity," " driver crash," and " crash analysis."
Keywords
- Sarkar S, Maiti J. Machine learning in occupational accident analysis: A review using science mapping approach with citation network analysis. Safety Science. 2020; 131:104900.
- Zou X, Vu HL. Mapping the knowledge domain of road safety studies: A scientometric analysis. Accident Analysis & Prevention. 2019; 132:105243.
- van Eck, N. J., & Waltman, L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics. 2010; 84: 523–538.
- Aria, M., and Cuccurullo, C. bibliometrix: AnR-tool for comprehensive science mapping analysis, Journal of Informetrics. 2017; 11(4): 959-975.
- Perianes-Rodriguez, A., Waltman, L., & Van Eck, N.J. (2016). Constructing bibliometric networks: A comparison between full and fractional counting. Journal of Informetrics, 10(4), 1178–1195.
- Van Eck, N.J., & Waltman, L. (2011). Text mining and visualization using VOSviewer. ISSI Newsletter, 7(3), 50–54.
- Van Eck, N.J., Waltman, L., Dekker, R., & Van den Berg, J. (2010). A comparison of two techniques for bibliometric mapping: Multidimensional scaling and VOS. Journal of the American Society for Information Science and Technology, 61(12), 2405–2416.
- Waltman, L., Van Eck, N.J., & Noyons, E.C.M. (2010). A unified approach to mapping and clustering of bibliometric networks. Journal of Informetrics, 4(4), 629–635.
- Merigó JM, Miranda J, Modak NM, Boustras G, de la Sotta C. Forty years of Safety Science: A bibliometric overview. Safety Science. 2019; 115:66–88.
- Renski, H., Khattak, A., & Council, F. (1998). Impact of Speed Limit increases on Crash Injury Severity: Analysis of Single-Vehicle Crashes on North Carolina Interstate highways. Presented at the 78th Annual meeting of the Transportation Research Board, Washington, D.C.
- Kim, K., Li, L., Richardson, J., and Nitz, L. ~1998!. ‘‘Drivers at fault: influences of age, sex, and vehicle type.’’ J. Safety Res., 29~3! 171– 179.
- National Highway Traffic Safety Administration. (2016b). Fatality Analysis Reporting System [Data files]. Modified 09/12/2016. Accessed 09/14/2016. Available at ftp://ftp. nhtsa.dot.gov/FARS/. Washington, DC: National Highway Traffic Safety Administration.
- Triplett T, Santos R, Rosenbloom S. (2016). American driving survey: 2014-2015. Washington, DC: AAA Foundation for Traffic Safety.
- Garber, N. J., 2000, The Effect of Speed, Flow, and Geometric Characteristics on crash rates for different types of Virginia Highways Transportation Research Council, Charlottesville.
- Abdel-Aty, M. 2003, Analysis of Driver Injury Severity Levels at Multiple Locations Using Ordered Probit Models. Journal of Safety Research, Vol. 34, pp. 597-603.
- HURST P.M. Epidemiological aspects of alcohol in driver crashes and citations. J. Saf. Res. 5: 130-148, 1973.
- Aljanahi, A.A.M., Rhodes, A.H., Metcalfe, A.V., 1999. Speed, speed limits, and road traffic accidents under free flow conditions. Accident Analysis and Prevention 31 (2), 161–168.
- Li, L., Kim, K., 2000. Estimating driver crash risks based on the extended Bradley-Terry model: an induced exposure method. Journal of Royal Statistical Society A 163 (2), 227–240.
- Kim, K., Nitz, L., Richardson, J., Li, L., 1995. Personal and behavioral predictors of an automobile crash and injury severity. Accident Analysis and Prevention 27 (4), 469–481.
- American Automobile Association (AAA), 2009. Teen Crashes – Everyone is at Risk: People Fatally Injured in Motor Vehicle Crashes Involving 15- to 17-Year-olds.http://exchange.aaa.com/wp-content/uploads/2012/05/AAA-Teen-Crashes-Everyones-At-Risk.pdf.
- Kim, J.K., Ulf arsson, G.F., Kim, S., Shankar, V.N., 2013. Driver-injury severity in single-vehicle crashes in California: a mixed logit analysis of heterogeneity due to age and gender. Accident Analysis and Prevention 50, 1073–1081.
- Yu, H., Yuan, R., Li, Z., Zhang, G., & Ma, D. T. (2020). Identifying heterogeneous factors for driver injury severity variations in snow-related rural single-vehicle crashes. Accident Analysis & Prevention, 144, 105587.
- Das, Subasish & Datta, Songjukta & Al-Zubaidi, Hamsa & Obaid, Ihsan. (2021). Applying interpretable machine learning to classify tree and utility pole related crash injury types. IATSS Research. 45. 10.1016/j.iatssr.2021.01.001.
- Hamsa Zubaidi, Ihsan Obaid, Ali Alnedawi, Subasish Das, Md Mazharul Haque, Temporal instability assessment of injury severities of motor vehicle drivers at give-way controlled unsignalized intersections: A random parameters approach with heterogeneity in means and variances, Accident Analysis & Prevention, Volume 156, 2021, 106151,ISSN 0001-4575.
- Subasish Das, Lisa Minjares-Kyle, Lingtao Wu, Russell H. Henk , Understanding crash potential associated with teen driving: Survey analysis using multivariate graphical method ,Journal of Safety Research ,Volume 70,2019,Pages 213-222,ISSN 0022-4375.
- Ashifur Rahman, Md. Mahmud Hossain, Elisabeta Mitran, Xiaoduan Sun, Understanding the contributing factors to young driver crashes: A comparison of crash profiles of three age groups, Transportation Engineering ,Volume 5,2021,100076,ISSN 2666-691X.
- Redelmeier, Donald & Manzoor, Fizza. (2019). Life-threatening alcohol-related traffic crashes in adverse weather: A double-matched case-control analysis from Canada. BMJ Open. 9. e024415. 10.1136/bmjopen-2018-024415.
- Lin, HA., Chan, CW., Wiratama, B.S. et al. Evaluating the effect of drunk driving on fatal injuries among vulnerable road users in Taiwan: a population-based study. BMC Public Health 22, 2059 (2022).
- Charles Goldenbeld, Katrien Torfs, Willem Vlakveld, Sjoerd Houwing, Impaired driving due to alcohol or drugs: International differences and determinants based on E-Survey of Road Users' Attitudes first-wave results in 32 countries, IATSS Research, Volume 44, Issue 3,2020,Pages 188-196,ISSN 0386-1112.
- Fouda Mbarga, N., Abubakari, AR., Aminde, L.N. et al. Seatbelt use and risk of major injuries sustained by vehicle occupants during motor-vehicle crashes: a systematic review and meta-analysis of cohort studies. BMC Public Health 18, 1413 (2018).
- Nawaf Alnawmasi, Fred Mannering,A temporal assessment of distracted driving injury severities using alternate unobserved-heterogeneity modeling approaches,Analytic Methods in Accident Research,Volume 34,2022,100216,ISSN 2213-6657.
- Ihsan Obaid, Ali Alnedawi, Ghufraan Mohammed Aboud, Reuben Tamakloe, Hamsa Zuabidi, Subasish Das,Factors associated with driver injury severity of motor vehicle crashes on sealed and unsealed pavements: Random parameter model with heterogeneity in means and variances,International Journal of Transportation Science and Technology, 2022,ISSN 2046-0430,https://doi.org/10.1016/j.ijtst.2022.04.002.
- Zubaidi, H.A., Anderson, J.C., Hernandez, S., 2020. Understanding roundabout safety through the application of advanced econometric techniques. J. Transp. Sci. Technol. https://doi.org/10.1016/j.ijtst.2020.03.001.
- Subasish Das, Songjukta Datta, Hamsa Abbas Zubaidi, Ihsan Ali Obaid, Applying interpretable machine learning to classify tree and utility pole related crash injury types, IATSS Research,Volume 45, Issue 3,2021,Pages 310-316, ISSN 0386-1112,https://doi.org/10.1016/j.iatssr.2021.01.001.
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