DOI QR코드

DOI QR Code

Development of Traffic Accident frequency Prediction Model by Administrative zone - A Case of Seoul

소규모 지역단위 교통사고예측모형 개발 - 서울시 행정동을 대상으로

  • Received : 2015.09.04
  • Accepted : 2015.09.22
  • Published : 2015.12.01

Abstract

In Korea, the local traffic safety master plan has been established and implemented according to the Traffic Safety Act. Each local government is required to establish a customized traffic safety policy and share roles for improvement of traffic safety and this means that local governments lead and promote effective local traffic safety policies fit for local circumstances in substance. For implementing efficient traffic safety policies, which accord with many-sided characteristics of local governments, the prediction of community-based traffic accidents, which considers local characteristics and the analysis of accident influence factors must be preceded, but there is a shortage of research on this. Most of existing studies on the community-based traffic accident prediction used social and economic variables related to accident exposure environments in countries or cities due to the limit of collected data. For this reason, there was a limit in applying the developed models to the actual reduction of traffic accidents. Thus, this study developed a local traffic accident prediction model, based on smaller regional units, administrative districts, which were not omitted in existing studies and suggested a method to reflect traffic safety facility and policy variables that traffic safety policy makers can control, in addition to social and economic variables related to accident exposure environments, in the model and apply them to the development of local traffic safety policies. The model development result showed that in terms of accident exposure environments, road extension, gross floor area of buildings, the ratio of bus lane installation and the number of crossroads and crosswalks had a positive relation with accidents and the ratio of crosswalk sign installation, the number of speed bumps and the results of clampdown by police force had a negative relation with accidents.

우리나라는 교통안전법에 의해 지역교통안전기본계획을 수립 시행하고 있다. 지자체별 맞춤형 교통안전시책 수립을 통해 교통안전 향상을 위한 대책 수립 및 역할분담이 강조되고 있으며, 이는 곧 지자체가 지역실정에 맞는 내실 있는 지역교통안전 정책을 실질적으로 주도하여 추진하는 것을 의미한다. 지자체들이 가지고 있는 다면적인 특성에 부합되는 효율적인 교통안전정책이 시행되기 위해서는 지역특성을 고려한 지역단위 교통사고를 예측하고 사고에 미치는 영향요인 분석이 선행되어야 하지만 이에 대한 연구는 미흡한 실정이다. 지역을 기반으로 하는 교통사고 예측에 관한 기존 연구들은 자료 수집의 한계로 대부분 국가 또는 도시를 분석단위로 사고노출환경과 관련되는 사회경제변수들을 활용한 연구가 대부분이었다. 교통사고 예측모형을 개발하는 이유는 교통사고 발생특성을 파악하여 교통사고를 줄일 수 있는 효율적인 대책을 발굴하는 것이 주요 목적이다. 이에 본 연구에서는 기존연구에서 다루지 못한 보다 작은 지역단위인 행정동을 단위로 지역교통사고 예측모형을 개발하였으며, 사고 노출환경 측면의 사회경제적 변수 외 교통안전정책가가 제어할 수 있는 교통안전시설 및 정책변수를 모형에 반영하여 지역교통안전 정책 수립시 활용할 수 있는 방안을 제시하였다. 모형개발 결과 사고노출환경 측면에서는 도로연장, 건축물 총 연면적, 버스전용차로 설치율, 교차로 및 횡단보도 개소수는 사고와 양(+)의 관계를 보이고 있으며, 횡단보도예고 설치율, 과속방지턱 개소수 및 경찰인력에 의한 단속실적은 사고와 음(-)의 관계에 있는 것으로 나타났다.

Acknowledgement

Supported by : 한국연구재단

References

  1. Adams, J. (1987). "Smeed's Law: Some Further Thoughts." Traffic Engineering and Control, Vol. 28, No. 2, pp. 70-73.
  2. Box, G. E. P. and Cox, D. R. (1964). "An analysis of transformations." Journal of the Royal Statistical Society. Series B(Methodological), Vol. 26, No. 2, pp. 211-252.
  3. Jin, C. J., Lee, H. S. and Choo, S. H. (2012). "Developing trip generation models using spatial regression analysis : A Case for Seoul, Korea." The Korea Spatial Planning Review, Vol. 73, pp. 131-143 (in Korean). https://doi.org/10.15793/kspr.2012.73..008
  4. Jung, J. S. and Hwang, U. G. (2010). "A macro-level study on the cause of homicide rate: Nationwide Analysis Using Spatial Regression Model." Journal of the Korean Association of Criminology, Vol. 22, No. 1, pp. 157-184 (in Korean).
  5. Jung, K. S., Moon, T. H., Jung, J. H. and Huh, S. Y. (2009). "Analysis of spatio-temporal pattern of urban crime and its influencing factors." Journal of the Korean Association of Geographic Information Studies, Vol. 12, No. 1, pp. 12-25 (in Korean).
  6. Kang, B. S. and Kim, G. S. (2001). Social Science statistical analysis, Datasolution Inc (in Korean).
  7. Kim, H. S. (1987). Methoden zur Beschreibung des Unfallgeschehens-Versuch eines Vergleichs Zwischen der Bundesrepublik Deutschland und der Republik Korea-, Ph.D. Dissertation, University of Karlsruhe, Karlsruhe, Germany.
  8. Kim, T. H., No, J. H. and Oh, Y. T. (2010). "Development of trip generation type models toward traffic zone characteristics." International Journal of Highway Engineering, Vol. 12, No. 4, pp. 93-100 (in Korean).
  9. Ko, W. K. (2011). Data Analysis of Social Science by data entering per step by SPSS, Kyungmoonsa Inc(in Korean).
  10. Kwon, K. D. (1993). A Study on Development of Forecasting Model for Traffic Accident in Seoul, Master Dissertation, Hongik University (in Korean).
  11. Lee, H. S. (2010). SPSS 10.0's manual, Bobmunsa Inc (in Korean).
  12. Lee, S. Y., Lee, J. H. and Hwang, M. J. (2007). "Studies on the transformation of the dependent variable in the non-linear regression analysis." Journal of The Korean Official Statistics, Vol. 12, pp. 1-22 (in Korean).
  13. Markowitz, F., Sciortino, S., Fleck, J. L. and Yee, B. M. (2006). "Pedestrian countdown signals: Experience with an Extensive Pilot Installation." Institute of Transportation Engineers, ITE Journal, Vol. 76, No. 1, pp. 43-48.
  14. Park, J. T. (2011a). "Development of traffic accident forecasting models considering urban-transportation system characteristics." Journal of Korea Transportation Research Society, Vol. 29, No. 6, pp. 39-56 (in Korean).
  15. Park, J. Y. (2011b). Development of Macroscopic Traffic Accident Analysis Model by Regional Characteristics, Master Dissertation, University of Seoul (in Korean).
  16. Pulugurtha, S. S. and Pasupuleti, N. (2010). "Assessment of link reliability as a function of congestion components." Journal of Transportation Engineering, Vol. 136, No. 10, pp. 903-913. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000156
  17. Smeed, R. J. (1949). "Some statistical aspects of road safety research." Journal of the Royal Statistical Society, Series A(General), Vol. 112, No. 1, pp. 1-34. https://doi.org/10.2307/2984177
  18. Sung, T. J. (2011). Easy Statistical Analysis Using SPS/AMOS, Hakjisa corp (in Korean).
  19. Wedagama, D. M. P., Bird, R. N. and Metcalfe, A. V. (2006). "The influence of urban land-use on non-motorised transport casualties." Accident Analysis & Prevention, Vol. 38, No. 6, pp. 1049-1057. https://doi.org/10.1016/j.aap.2006.01.006
  20. Wier, M., Weintraub, J., Humphreys, E. H. Seto, E. and Bhatia, R. (2009). "An area-level model of vehicle-pedestrian injury collisions with implications for land use and transportation planning." Accident Analysis & Prevention, Vol. 41, No. 1, pp. 137-145. https://doi.org/10.1016/j.aap.2008.10.001