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2017 Vol.35, Issue 5 Preview Page
Analysis of Bicycle Accidents in Korea Based on Regional Characteristics

지역 특성을 고려한 국내 자전거 사고 분석

Tae Yang KIM1
,
Byung Ho PARK1*
김 태양1
,
박 병호1*
1Department of Urban Engineering, Chungbuk National University
1충북대학교 도시공학과
*교신저자. *Corresponding Author. 
October 2017. pp. 447-457
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Abstract

This study aims to analyze the accidents of green mode bicycle. In pursuing the above, this study gave special emphasis on modeling the bicycle accidents reflecting the regional characteristics. The main results are as follows. First, the null hypotheses that the number of accident and ratio of serious injury and fatality (FSI) were the same over regions were rejected. Second, as the common variables, the number of bicycle was judged to have positive (+) impact to the accidents and the bicycle using ratio was inferred to increase the ratio of FSI. Third, the elderly population ratio among 3 factors which gave impact to the accidents of Si_A (city-county consolidation) was concluded to have the greatest elasticity. The developed area ratio between 2 factors in Si_B (city which is not consolidated) was, however, estimated to have the higher elasticity. Fourth, the number of car registration among 5 accident factors of Gun (county) was analyzed to have the greatest elasticity. Finally, the commuting trip ratio among 7 accident factors of Gu (district) was judged to have the greatest elasticity. This study can be expected to give some implications to regional policy-making related to bicycle.

Keywords
bicycle accident
elasticity
negative binomial regression
post-hoc test
regional characteristic

본 연구는 녹색교통수단인 자전거의 교통사고를 분석하는데 그 목적이 있다. 이를 위하여 본 연구에서는 국내 지역별 특성에 근거한 자전거 사고모형 개발에 중점을 두었다. 주요 연구결과는 다음과 같다. 첫째, 자전거 사고건수와 중상이상 사고비율이 지역별로 차이가 없다는 귀무가설이 기각되었다. 둘째, 각 지역 공통으로 자전거보유대수는 사고건수 증가, 그리고 자전거이용률은 중상이상 사고비율 증가에 영향을 미치는 것으로 판단되었다. 셋째, 통합시의 사고에 영향을 미치는 3개 요인 중 고령인구비율의 탄력성이 가장 큰 것으로 판단되었다. 또한 일반시의 사고에 영향을 미치는 2개 요인 중 시가화면적비율의 탄력성이 가장 큰 것으로 판단되었다. 셋째, 군의 5개 사고 요인 중 자동차보유대수의 탄력성이 가장 큰 것으로 평가되었다. 마지막으로 구의 7개 사고 요인 중 출근통행률의 탄력성이 가장 큰 것으로 판단되었다. 본 연구는 지역 단위 자전거 안전대책 수립에 몇 가지 함의를 제공할 수 있을 것으로 기대된다.

키워드
자전거 사고
탄력성
음이항 회귀
사후검정
지역특성
References
1
Cai Q., Abdel-Aty M., Lee J. (2017), Macro-level Vulnerable Road Users Crash Analysis: A Bayesian Joint Modeling Approach of Frequency and Proportion, Accident Analysis and Prevention, 107, 11-19.
2
Cai Q., Lee J., Eluru N., Abdel-Aty M. (2016), Macro-level Pedestrian and Bicycle Crash Analysis: Incorporating Spatial Spillover Effects in Dual State Count Models, Accident Analysis and Prevention, 93, 14-22.
3
Chen P. (2015), Built Environment Factors in Explaining the Automobile Involved Bicycle Crash Frequencies: A Spatial Statistic Approach, Safety Science, 79, 336-343.
4
Kim E. C., Oh J. T., Kim M. S. (2007), A Study on Crash Causations for Bicycles in Signalized Intersections Using Non-linear Regression Models, Journal of Korea Planning Association, 42(3), 261-272.
5
Kim K. Y., Beak T. H., Lim J. K., Park B. H. (2015), Traffic Accident Density Models Reflecting the Characteristic of the Traffic Analysis Zone in Cheongju, International Journal of Highway Engineering, 17(6), 75-83.
6
Korea Transport Institute (2012), Bicycle Traffic Accident Reduction Seminar, 1-28.
7
Korea Transport Institute Bicycle Traffic Session, https://www.koti.re.kr/slzs/bcyclMain.do, 2017.06.03.
8
Kwon S. D., Kim Y. M., Kim J. G., Ha T. J. (2015), Development of Bicycle Accident Prediction Model and Suggestion of Countermeasures on Bicycle Accidents, Journal of Korean Society of Civil Engineers, 35(5), 1135-1146.
9
Oh J. T., Kim E. C., Kim D. H. (2007), A Study on the Bicycle Accident Injury Severity at Urban Intersections, Journal of Korean Society of Civil Engineers, 27(4D), 389-395.
10
Park N. Y., Park B. H. (2017), Regional Traffic Accident Model Based on Urban Decline Index, Journal of Korea Planning Association, 52(4), 89-98.
11
Shin H. J., Hong J. Y., Lee S. B. (2012), A Study on the Factors Affecting the Severity of Bicycle-Related Accidents, Journal of Transport Research, 19(1), 67-78.
12
Siddiqui C., Abdel-Aty M., Choi K. J. (2012), Macroscopic Spatial Analysis of Pedestrian and Bicycle Crashes, Accident Analysis and Prevention, 45, 382-391.
13
Yasmin S., Eluru N. (2016), Latent Segmentation Based Count Models: Analysis of Bicycle Safety in Montreal and Toronto, Accident Analysis and Prevention, 95, 157-171.
Information
  • Publisher :Korean Society of Transportation
  • Publisher(Ko) :대한교통학회
  • Journal Title :Journal of Korean Society of Transportation
  • Journal Title(Ko) :대한교통학회지
  • Volume : 35
  • No :5
  • Pages :447-457
  • Received Date : 2017-07-13
  • Revised Date : 2017-07-19
  • Accepted Date : 2017-10-30
  • DOI :https://doi.org/10.7470/jkst.2017.35.5.447
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