International Journal of Highway Engineering (한국도로학회논문집)

Korean Society of Road Engineers (한국도로학회)
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Analysis of Factors influencing Severity of Motorcycle Accidents using Ordered Probit Model

순서형 프로빗모형에 의한 이륜차 사고심각도의 영향요인 분석

  • Choi, Jung Woo (Department of Transportation Engineering, Myongji University) ;
  • Kum, Ki Jung (Department of Transportation Engineering, Myongji University)
  • 최정우 (명지대학교 공과대학 교통공학과) ;
  • 금기정 (명지대학교 공과대학 교통공학과)
  • Received : 2014.07.28
  • Accepted : 2014.09.12
  • Published : 2014.10.16
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Abstract

PURPOSES : This study drew factors affecting motorcycle accidents in Seoul by severity using an ordered probit model and aimed to analyze and verify the drawn influence factors. METHODS : As the severity of the accidents could be classified into three types (fatal injury, serious injury and minor injury), this study drew the factors affecting accidents by a comparative analysis employing an ordered probit model, removed the variables that would not secure significance sequentially to construct a model with high explanatory power regarding the factors affecting the severity of motorcycle accidents, and calculated the marginal effect of each factor to understand the degree of each factor's impact on the severity. First, Model 1 put in all variables; Model 2 was constructed by removing the variables of the road surface conditions that could not meet the level of significance (p=0.608); Model 3 was constructed by removing gender variable (p=0.423); and Model 4 was constructed finally by removing age variable (p=0.320). RESULTS : As a result of an analysis, statistically significant variables were time of occurrence, type of accident, road alignment and motorcycle displacement, and it turned out that the impacts on the severity were in the following order: a road alignment of left downhill, the type of motorcycle-to-vehicle accidents and a road alignment of a flatland on the left. The significance of the models was tested using the likelihood ratio, the level of significance and suitability statistics about them, and as a result of the test, the significance level and suitability of the constructed models were all excellent. In addition, the model accuracy indicating the accuracy of a predicted value compared to that of the value actually observed was 70.3% for minor injury; 70.1% for serious injury; and 68.6% for fatal injury, and the overall accuracy was 70.2%, which was very high. CONCLUSIONS : As a result of an analysis of motorcycle accidents in Seoul through the ordered probit model and the marginal effect, it turned out that their severity increased in nighttime accidents as compared to daytime ones and gradually increased in the order of motorcycle-to-vehicle accidents, motorcycle-to-person ones and the ones involving motorcycle only. As a result of an analysis, the severity of accidents in road alignments of left downhill, left flatland and straight downhill increased as compared to those in a road alignment of straight flatland and that the severity of accidents of motorcycles with a displacement larger than 50cc was higher than that of those with a displacement smaller than 50cc.

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References

  1. Antoine Guisan, Frank E. Harrell, 2000. Ordinal response regression models in ecology, Journal of Vegetation Science, Vol 11, Issue 5, pages 617-626, October. https://doi.org/10.2307/3236568
  2. Chae, Beom Seok, 2005, A Study on the Characteristics and Solutions of Motorbike traffic Accidents, Korean Society of Civil Engineers Magazine, Vol. 53, No.8, August.
  3. Chimba, D., Lan, C. J., and Li, J., 2006, Statistical evaluation of motorcycle crash injury severities by using multinomial models., 84th Annual Meeting of the Transportation Research Board, Transportation Research Board, Washington, DC.
  4. Eustace, D., Indupuru, V., and Hovey, P., 2011, Identification of risk factors associated with motorcycle-related fatalities in Ohio., J. Transp. Eng.
  5. Ha O Keun, 2005, The Study on the Accident Injury Severity Using Ordered Probit Model, Journal of Korean Society of Transportation, Vol 23, No.4
  6. Hong Ji Yeon, 2011, Developing the Accident Injury Severity on a Field of Construction Work using Ordered Probit Model, Journal of the KOSIS, Vol 26, No.2
  7. Jang Tae Yeon, 2003, Marginal Effect Analysis of Travel Behavior by Count Data Model, Journal of Korean Society of Transportation, Vol 21, No.3
  8. Ju Mi Ypung, 2002, Probit and Ordered Probit Analysis and Its Application, Journal of Governmental Studies, Vol 6, No.1
  9. Kim Hong Jun, 2006, Statistics clearly based learning:-probability distribution, intervision
  10. Lee, Woo Seung, 2001, Motorcycle Operation Status and Future Challenges - policy debate, Seoul Development Institute
  11. Liu, I. and Agresti, A., 2005, The analysis of ordered categorical data: an overview and a survey of recent developments. Test, 14(1), 1-73. https://doi.org/10.1007/BF02595397
  12. McCullagh, P., 1980, Regression models for ordinal data, Journal of the Royal Statistical Society, Series B 42, 109-142.
  13. Na, Hee., Park, Byung Ho, 2012, Analysis on the Accident Severity of Motorcycle Using Ordered Logit Model, Journal of the Korea Planners Association, Vol.47, No.4, August.
  14. Moshe Ben-Akiva and Steven R. 1985, Lerman, Discrete Choice Analysis: Theory and Application to Travel Demand, MITPress
  15. Rifaat, S., Tay, R., and Barros, A,. 2011, Severity of motorcycle crashes in Calgary., Accid. Anal. Prev.
  16. Shaheed, M., and Dissanayake, S., 2011, Risk factors associated with motorcycle crash severity in Kansas., 90th Annual Meeting of the Transportation Research Board, Washington, DC.
  17. Steven Jones, Saravanan Gurupackiam, Joe Walsh, 2013, Factors Influencing the Severity of Crashes Caused by Motorcyclists: Analysis of Data from Alabama, American Society of Civil Engineers.