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차량 블랙박스 자료를 활용한 택시-이륜차 사고에서의 이륜차 이용자 사고 심각도 분석

njury Severity Analysis of Cyclists in Two Wheeler to Taxi Crashes: An Application of Vehicle Black Box Data in Incheon, Korea

  • 김선중 (영남대학교 도시공학과) ;
  • 정연식 (영남대학교 도시공학과)
  • 투고 : 2018.10.16
  • 심사 : 2018.10.27
  • 발행 : 2018.12.01

초록

최근 도입되고 있는 첨단 차량 장치는 교통 안전분야에서 중요한 이슈가 되어왔던 중대형 사고 위주의 자료수집, 사고 자료의 정확성과 같은 다양한 문제를 해결할 수 있는 대안으로 부각되고 있다. 본 연구는 이러한 첨단 차량 장치의 하나인 차량 블랙박스 자료를 활용하여, 이륜차(two wheeler: TW) 즉, 자전거 혹은 오토바이와 택시간 사고 발생 시 이륜차 운전자의 사고 심각도를 분석하고자 하였다. 연구를 위해 인천시에서 2010년부터 2011년까지 영업용 택시 블랙박스에 기록된 택시-이륜차 사고 자료를 활용하였으며, 심각도 분석을 위해 순서형 프로빗 모형을 적용하였다. 결과적으로 기존 연구결과에서는 확인할 수 없는 새로운 심각도 요인이 발견되었다. 즉, 충돌 직전의 택시 속도가 높을수록, 택시 또는 이륜차의 파손이 발생한 경우, 사고 후 이륜차 운전자의 보행이 불가능할 경우, 그리고 1차 사고 후 이륜차 운전자가 2, 3차 충격으로 이어진 경우 사고 심각도는 더욱 높아지는 것으로 나타났다.

In recent, technological advancement including a vehicle black box (VBB) has led to reducing such underreporting issues and errors of crash data. The objective of this study is to analyze the injury severity of cyclists on taxi-to-two wheeler crashes based on the accurate crash data collected from the VBB in taxi. This study defined the two wheelers as bicycle and motorcycle. To perform this study, we used the VBB data collected from taxis operating in Incheon, South Korea for a two-year period (2010-2011). An ordered probit model was applied to analyze the injury severity in crashes. As a result, new injury severity factors were found: increase of the crash speed of taxi, damage of crash-involved vehicles (i.e., taxi and/or two wheeler), not standing of cyclists after crash, and second or third impact of cyclists after first crash.

키워드

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Fig. 1. Predicted Probabilities by Crash Speed

Table 1. Descriptive Statistics of Taxi-Two Wheeler Crash Data

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Table 1. Descriptive Statistics of Taxi-Two Wheeler Crash Data (Continued)

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Table 2. Results of Ordered Probit Model on Injury Severity

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Table 3. Marginal Probability Effects of Estimated Model

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