The Journal of The Korea Institute of Intelligent Transport Systems (한국ITS학회 논문지)

The Korea Institute of Intelligent Transport Systems (한국ITS학회)
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Study on the Development of Truck Traffic Accident Prediction Models and Safety Rating on Expressways

고속도로 화물차 교통사고 건수 예측모형 및 안전등급 개발 연구

  • Jungeun Yoon (Dept. of Transportation Eng., Univ. of Ajou) ;
  • Harim Jeong (Dept. of Transportation Eng., Univ. of Ajou) ;
  • Jangho Park (Dept. of Civil System Eng., Univ. of Ajou) ;
  • Donghyo Kang (Dept. of Transportation Eng., Univ. of Ajou) ;
  • Ilsoo Yun (Dept. of Transportation Eng., Univ. of Ajou)
  • 윤정은 (아주대학교 교통공학과) ;
  • 정하림 (아주대학교 교통시스템공학과) ;
  • 박장호 (아주대학교 건설시스템공학과) ;
  • 강동효 (아주대학교 교통공학과) ;
  • 윤일수 (아주대학교 교통시스템공학과)
  • Received : 2022.10.31
  • Accepted : 2023.01.20
  • Published : 2023.02.28
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Abstract

In this study, the number of truck traffic accidents was predicted by using Poisson and negative binomial regression analysis to understand what factors affect accidents using expressway data. Significant variables in the truck traffic accident prediction model were continuous driving time, link length, truck traffic volume. number of bridges and number of drowsy shelters. The calculated LOSS rating was expressed on the national expressway network to diagnose the risk of truck accidents. This is expected to be used as basic data for policy establishment to reduce truck accidents on expressways.

본 연구에서는 전국 고속도로를 대상으로 화물차 교통사고에 영향을 미치는 주요 요인을 파악하고자 한다. 이를 위해, 고속도로 교통사고 자료들과 포아송 및 음이항 회귀모형을 이용하여 화물차 교통사고 건수 예측모형을 개발하였다. 모형에서 유의한 것으로 확인된 변수는 화물차 연속주행시간지수, 구간연장, 화물차 교통량, 구간내 교량 수, 졸음쉼터 개수이다. 또한, 구축된 예측모형을 이용하여 고속도로 구간별 안전등급(level of service of safety, LOSS)을 도출하였다. 이후 LOSS를 전국 고속도로 네트워크에 표출하여 고속도로 구간별 화물차 교통사고 위험도를 진단하였다. 본 연구에서 개발된 모형과 LOSS는 고속도로에서의 화물차 교통사고 저감을 위한 정책수립의 기초자료로 활용될 것으로 기대된다.

Keywords

Acknowledgement

본 연구는 국토교통부 및 국토교통과학기술진흥원의 연구비지원(RS-2022-00142239)에 의해 수행되었습니다.

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