The Journal of The Korea Institute of Intelligent Transport Systems (한국ITS학회 논문지)

The Korea Institute of Intelligent Transport Systems (한국ITS학회)
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A Study of the Effect Factor of Unexpected Accidents on Expressways

고속도로 돌발상황 발생 영향 요인 연구

  • 김혜진 (아주대학교 TOD기반 지속가능 도시교통연구센터 ) ;
  • 공용혁 (아주대학교 교통공학과 ) ;
  • 최동준 (아주대학교 교통공학과)
  • Received : 2023.03.07
  • Accepted : 2023.04.05
  • Published : 2023.04.30
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Abstract

The fatality rate of secondary accidents is seven times that of general traffic accidents. If limited to highways, one in four deaths are said to occur from secondary accidents. Unexpected situations which do not give drivers time to prepare are the cause of secondary accidents. This risk results in more fatalities on highways with high driving speeds. Existing studies have conducted research on traffic accidents and on secondary traffic accidents that occur after a primary traffic accident, without considering unexpected situations that may occur on the road. Therefore, to reduce damage and casualties caused by secondary accidents, there is a need to create a safe road environment by removing the possibility of causing accidents. This study analyzes whether the day of occurrence, time of occurrence, and radius of the curve of an unexpected situation are related to the occurrence of an unexpected situation. This study was based on data of accidents that occurred in 2022 on the Cheonan-Nonsan Expressway and the Seoul-Yangyang Expressway. The radius of the curve was calculated by dividing the section of the highway into straight, clothoid, and curved sections through cluster analysis. Results of the analysis indicate that the day and time of occurrence and the curve radius are associated with unexpected situations.

2차 사고의 치사율은 일반 교통사고의 7배이며 고속도로에 한정하면, 사망자 4명 중 1명은 2차 사고로 인한 사망이라고 할 수 있다. 돌발상황은 2차 사고를 유발할 수 있으며 운전자에게 대비할 시간을 주지 않아 주행속도가 높은 고속도로에서의 사고 위험은 더욱 치명적이다. 그러나 기존 연구에서는 이미 교통사고에 관한 연구를 수행하거나 교통사고 후 발생하는 2차 사고에 관한 연구를 수행하고 있어서 그 외 도로에서 발생할 수 있는 다른 돌발상황에 대해 고려하지 못하고 있다. 따라서 2차 사고로 인한 피해와 사상자 감소를 위해서는 교통사고 외에도 사고 유발 가능성을 제거하여 안전한 도로환경을 만들 필요성이 존재한다. 본 연구에서는 돌발상황과 발생요일, 발생시간, 곡선반경이 돌발상황 발생과 연관성이 있는지에 대하여 분석하였다. 돌발상황은 천안논산고속도로와 서울양양고속도로에서 2022년 발생한 자료를 사용하였으며 고속도로의 구간을 분할하여 곡선반경을 계산하고 이를 군집분석을 통해 직선부, 완화곡선부, 곡선부로 구분하여 분석하였다. 분석결과 발생요일, 발생시간, 곡선반경이 돌발상황과 연관성이 있는 것으로 분석되었다.

Keywords

References

  1. Chakraborty, P., Hegde, C. and Sharma, A.(2019), "Data-driven Parallelizable Traffic Incident Detection Using Spation-temporally Denoised Robust Thresholds", Transportation Research Part C: Emerging Technologies, vol. 105, pp.81-99. https://doi.org/10.1016/j.trc.2019.05.034
  2. Choi, J. T., Shin, C. H. and Kang, S. M.(2012), "Development of an AIDA(Automatic Incident Detection Algorithm) for Uninterrupted Flow By Diminishing the Random Noise Effect of Traffic Detector Variables", The Journal of the Korea Institute of Intelligent Transport Systems, vol. 11, no. 2, pp.29-38. https://doi.org/10.12815/kits.2012.11.2.29
  3. Ciro, C., Maurizio, G. and Alessandra, P.(2007), "A Crash-Prediction Model for Multi-Lane Roads", Accident Analysis and Prevention, vol. 39, pp.657-670. https://doi.org/10.1016/j.aap.2006.10.012
  4. Federal Highway Administration(FHWA)(2000), Speed Prediction for Two Lane Rural Highways, pp.99-171.
  5. Jin, X., Cheu, R. and Srinivasan, D.(2001), "Development and Adaptation of Constructive Probabilistic Neural Network in Freeway Incident Detection", Transportation Research Part C: Emerging Technologies, vol. 10, no. 5, pp.1173-1187.
  6. Kang, J. G. and Lee, S. K.(2002), "Traffic Accident Prediction Model by Freeway Geometric Types", Journal of Korean Society of Transportation, vol. 20, no. 4, pp.163-175.
  7. Kang, M. W., Son, B. S., Dho, C. U. and Kang, J. S.(2002), "Development of Accident Prediction Models at Freeway Curve Section Based on Geometric Characteristics", Journal of the Korean Society of Civil Engineers D, vol. 22, no. 6D, pp.1077-1088.
  8. Kim, D. K.(2012), Analysis of The Factors Effecting of Secondary-Accident in Highways, The University of Seoul Master Degree Research, pp.1-97.
  9. Kim, S.(2006), "A Study on the Classification of Traffic Flow Areas for Detecting Sudden Situations", The Korea Society of Transportation, vol. 24, no. 3, pp.39-50.
  10. Kong, Y. H., Kim, H. J., Yi, Y. J. and Kang, S. J.(2021), "Development of Incident Detection Algorithm using GPS Data", The Journal of the Korea Institute of Electronic Communication Sciences, vol. 16, no. 4, pp.771-782.
  11. Kwon, C.(2019), Development of Automatic Incident Detection Model for Highway Using Machine Learning, Ajou University Master Degree Research, pp.5-7.
  12. No, H. J.(2011), Statistical Package for the Social Sciences, Hakhyunsa, p.483.