DTG 데이터를 이용한 위험 운전 행동의 시공간 특성 분석 = Spatial and Temporal Analysis of Dangerous Driving Behavior Using DTG Data

다국어 초록 (Multilingual Abstract)

In order to prevent traffic accidents, it is crucial to analyze the geographic and temporal characteristics of dangerous driving behavior. In this study, we analyze the potentially dangerous areas based on the Digital Tachograph (DTG) data together with the dangerous driving behavior criteria. Our findings showed that rapid acceleration (38.81%), sharp turn (24.72%), and overspeed (23.80%) are the top three most occurred dangerous driving behavior. Regarding the dangerous areas, our results revealed that there is a strong correlation between the dangerous driving behavior and the real traffic accidents which its correlation coefficient around 0.83. Within a week, Saturday (17.07%) shows the highest ratio of dangerous driving behavior occurrences. Within a day, between 6 AM to 8 AM (9.95%) show the highest ratio of dangerous driving behavior occurrences. By doing this, we conclude that our findings will be helpful to prevent future traffic accidents in both public transportation and private vehicles through traffic safety policy and traffic safety training for drivers.

국문 초록 (Abstract)

구에서는 디지털운행기록장치(Digital Tachograph) 데이터 및 위험 운전 행동 규칙을 이용하여 위험운전 행동의 특성을 분석하였다. 위험 운전 행동 중에서는 급가속(38.81%), 급회전(24.72%), 과속(23.8%)이 가장 높은 세 가지 위험 운전 행동으로 나타났다. 위험 지역의 경우 서초구(11%), 강남구(7%), 영등포구(7%) 순으로 높은 위험 운전 행동 비율을 보였다. 특히 지역별 위험 운전 행동과 실제교통 사고 수치는 0.83의 높은 상관 계수를 보였다. 일주일 중에서는 토요일(17.07%)이 가장 높은 위험운전 행동 비율을 보였으며, 하루 중에서는 오전 6시~8시(9.95%)가 가장 높은 위험 운전 행동 비율을 보였다. 이러한 분석 결과는 위험 운전 방지 및 교통 정책 수립에 활용될 수 있을 것으로 사료 된다.

참고문헌 (Reference)

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