DOI QR코드

DOI QR Code

Safety Impacts of Red Light Enforcement on Signalized Intersections

교차로 신호위반 단속카메라 설치가 차량사고에 미치는 영향

  • 이상혁 (한밭대학교 도시공학과) ;
  • 이용두 (코넬대학교 토목환경공학과) ;
  • 도명식 (한밭대학교 도시공학과)
  • Received : 2012.05.11
  • Accepted : 2012.11.29
  • Published : 2012.12.31

Abstract

The frequency and severity of traffic accidents related to signalized intersections in urban areas have been more serious than those in both arterial segments and crosswalks. Especially, traffic accidents involved with injuries and fatalities have caused by traffic signal violations within intersections. Therefore, many countries including Korea have installed the red light enforcement camera (RLE) to reduce traffic accidents associated with the traffic signal violation. Meanwhile, many methodologies have been studied in terms of safety impacts estimation of red light enforcement, which, however, cannot be easy to conduct. In this study, safety impacts was estimated for intersections of Chicago downtown area using SPF models and EB approach. As a result, for all crash types and target traffic accident types such as "angle", "rear end", "sideswipe in the same and other directions", "turn", and "head on", fatal crashes were reduced by 26% and 38%. However, RLE may increase property-demage-only-crashes by 3.23% and 1.16%, respectively.

도시지역의 교통사고 중 교차로와 관련한 교통사고가 교통사고 건수와 교통사고 심각도에서 가로구간이나 횡단보도 관련 교통사고에 비해 높게 나타나고 있다. 특히 교차로에서 신호위반으로 인한 교통사고는 다른 교통사고유형과는 달리 중상과 경상에 관련된 교통사고비율이 높은 것으로 나타나고 있다. 이에 우리나라는 물론이고 많은 외국에서 신호위반으로 인한 교차로 교통사고를 줄이기 위하여 교차로 신호위반 단속카메라를 설치하고 있다. 이와 더불어 교차로 신호위반 단속카메라의 교통사고 감소에 미치는 효용에 대한 연구가 계속 이루어지고 있으나 신호위반 단속카메라만의 효과를 분석하기란 쉽지가 않다. 따라서 본 연구에서는 미국 Illinois주 Chicago시의 다운타운의 교차로 관련 데이터를 이용하여 SPF모형을 개발하고 개발된 모형을 활용하여 EB방법으로 교차로 신호위반 단속카메라의 효용에 대하여 분석하였다. 분석 결과, 목표로 지정한 교통사고 유형(측면직각추돌, 후방추돌, 같은 방향 측면추돌, 반대 방향 측면추돌, 회전시 추돌, 그리고 정면충돌)과 전체 교통사고유형 모두가 교차로 신호위반 단속카메라의 영향을 받는 것으로 나타났다. 전반적으로 신호위반 단속카메라 사망사고가 약 26% 감소한 것으로 나타났으며, 전체 사고는 5.49% 증가하는 것으로 나타났다. 또한 대물교통사고의 경우 3.23% 증가하는 것으로 나타났다. 또한 목표로 한 사고유형에 대한 교통사고효과 분석에서는 사망사고는 약 38% 감소한 것으로 나타났으며 전체 사고의 경우 1.46% 증가하는 것으로 나타났다. 또한 대물교통사고의 경우 1.16% 증가하는 것으로 나타났다.

Keywords

Acknowledgement

Supported by : Kyonggi University

References

  1. Council F. M., Persaun B., Lyon C., Eccles K., Griffith M. (2005), Safety Evaluation of Red-Light Camera, U.S. Department of Transportation, FHWA-HRT-05-048.
  2. Fitzsimmons E. J., Hallmark S., McDonald T., Orellana M., Matulac D. (2007), The Effectiveness of Iowa's Automated Red Light Running Enforcement Programs, Center for Transportation Research and Education, CTRE project 05-226.
  3. Garber N, J., Miller J. S., Abel R. E., Eslambolchi S., Korukonda S. K. (2007), The Impact of Red Light Cameras (Photo-Red Enforcement) on Crashes in Virginia, Virginia Transportation Research Council, FHWA/VTRC 07-R2.
  4. Hauer Z. (2001), Overdispersion in Modelling Accidents on Road Sections and in Empirical Bayes Estimation, Accident Anal, Prevent. 33, pp.799-808. https://doi.org/10.1016/S0001-4575(00)00094-4
  5. Jeong S. B., Hwang B. H., Sung N. M., Lee S. H. (2009), Development of Evaluation Model for Black Spot Improvement Priorities by using Emperical Bayes Method, J. Korean Soc. Transp., Vol.27, No.3, Korean Society of Transportation, pp.81-90.
  6. Jovanis P. P., Chang H. (1985), Modeling the Relationship of Accidents to Miles Traveled, Transportation Research Record 1068, TRB, National Research Council, pp.42-51.
  7. Kim S. Y., Choi J. S., Kim M. K., Sung H. J. (2011), Analysis of the Crash Reduction Effects of the Red Light Camera Systems and Determination of the User Benefits, J. the Korea Institute of Intelligent Transport Systems Vol.10, No.1, pp.1-15.
  8. Kim T. Y., Park B. H. (2009), Effects of Accident Reduction according to the Installation of Red Light Camera by Accident Type Using EB method, Proc. Korea Planners Association in Fall, pp.415-422.
  9. KoROAD (2012), www.koroad.co.kr
  10. Kwak Y. H. (2006), An Effect Analysis on the Improvement Strategics of Traffic Accident Area using Empirical Bayes Method, Master's Degree Thesis, Hanyang University.
  11. Li Z., Lee S. H., Lee Y. D., Zhou B., Bamzai R. (2010), A Methodology for Assessing the Safety Impacts of Highway Shoulder Paving, ASCE, T & DI Congress, Chicago, IL.
  12. Lord D., Washington S. P., Ivan J. N. (2005), Poisson, Poisson-Gamma and Zero-Inflated Regression Models of Motor Vehicle Crashes: Balancing Statistical fit and Theory, Accident Anal, Prevent. 37, pp.35-46. https://doi.org/10.1016/j.aap.2004.02.004
  13. Retting R. A., Ferguson S. A., Hakkert A. S. (2003), Effects of Red Light Cameras on Violations and Crashes: A Review of the International Literature, Traffic Injury Prevention, 4:1, pp.17-23. https://doi.org/10.1080/15389580309858
  14. Retting R. A., Kyrychenko S. Y. (2002), Reductions in Injury Crashes Associated with Red Light Camera Enforcement in Oxnard, California, American J. Public Health, 92(11), pp.1822-1825. https://doi.org/10.2105/AJPH.92.11.1822
  15. Retting R. A., Ulmer R. G., Williams A. F. (1999), Prevalence and Characteristics of Red Light Running Crashes in the United States, Accident Anal, Prevent. 31, pp.687-694. https://doi.org/10.1016/S0001-4575(99)00029-9
  16. Retting R. A., Williams A. F., Farmer C. M., Feldman A. F. (1999), Evaluation of Red Ligjt Camera Enforcement in Oxnard, California, Accident anal, Prevention 31. pp.169-174. https://doi.org/10.1016/S0001-4575(98)00059-1
  17. Schneider H. (2010), Effectiveness of Red-Light Cameras for Reduction the Number of Crashes at Intersections in the City of Lafayette, Louisiana Department of Transportation.
  18. Synectics Transportation Consultants Inc. (2003), Evaluation of The Red Light Camera Enforcement Pilot Project, Ontario Ministry of Transportation.
  19. Walden T. D. (2008), Analysis on the Effectiveness of Photographic Traffic Signal Enforcement Systems in Texas, Traffic Department of Transportation.
  20. Washington S., Shin K. (2005), The Impact of Red Light Camera (Automated Enforcement) on Safety in Arizona, Report No. FHWA-AZ-05-550, Arizona Department of Transportation.

Cited by

  1. Traffic Accident Reduction Effects of Section Speed Enforcement Systems(SSES) Operation in Freeways vol.32, pp.2, 2014, https://doi.org/10.7470/jkst.2014.32.2.119
  2. Effect Analysis on Red Light Camera for Signalized Intersection Safety -Focused on Side Right-Angle Collision Accidents- vol.17, pp.1, 2015, https://doi.org/10.7855/IJHE.2015.17.1.119
  3. Random Parameter Negative Binomial Model of Signalized Intersections vol.2016, 2016, https://doi.org/10.1155/2016/1436364
  4. Analysis of Traffic Accident Reduction Effects considering Monitoring Direction of Traffic Camera vol.20, pp.1, 2018, https://doi.org/10.7855/IJHE.2018.20.1.127
  5. A Study on the Improvement of Prediction Accuracy for Traffic Accident Models Using Machine Learning (Generalized Regression Neural Network) vol.20, pp.6, 2018, https://doi.org/10.7855/IJHE.2018.20.6.179
  6. For Preventative Automated Driving System (PADS): Traffic Accident Context Analysis Based on Deep Neural Networks vol.9, pp.11, 2012, https://doi.org/10.3390/electronics9111829