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

  • 제20권4호
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  • Pages.13-27
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  • 2021
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  • 1738-0774(pISSN)
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  • 2384-1729(eISSN)
한국ITS학회 (The Korea Institute of Intelligent Transport Systems)
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IDM을 이용한 자율주행자동차 시장점유율 변화가 고속도로 교통류에 미치는 영향 분석

Analysis of Effects of Autonomous Vehicle Market Share Changes on Expressway Traffic Flow Using IDM

  • 고우리 (아주대학교 교통공학과) ;
  • 박상민 (아주대학교 교통시스템공학과) ;
  • 소재현 (아주대학교 교통시스템공학과) ;
  • 윤일수 (아주대학교 교통시스템공학과)
  • Ko, Woori (Dept. of Transportation Eng., Univ. of Ajou) ;
  • Park, Sangmin (Dept. of Transportation System Eng., Univ. of Ajou) ;
  • So, Jaehyun(Jason) (Dept. of Transportation System Eng., Univ. of Ajou) ;
  • Yun, Ilsoo (Dept. of Transportation System Eng., Univ. of Ajou)
  • 투고 : 2021.06.09
  • 심사 : 2021.07.19
  • 발행 : 2021.08.31
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초록

본 연구에서는 영동고속도로 용인IC~양지IC구간을 대상으로 2020년 데이터를 활용하여 자율주행자동차의 시장점유율 변화가 교통류에 미치는 영향을 추정하였다. 교통류에 미치는 영향 정도를 추정하기 위해 미시교통시뮬레이션 모형인 VISSIM을 활용하였다. 자율주행자동차의 종방향 제어를 반영하기 위해서 intelligent driver model(IDM)을 구축 후 VISSIM에 적용하여 일반차와 비교를 수행하고 주행행태를 검증하였다. 자율주행자동차의 시장점유율에 따른 이동성 및 안전성 분석 결과, 자율주행자동차 도입 시 시장점유율이 높아질수록 네트워크의 이동성은 향상되지만, 안전성의 경우 차종이 혼재되었을 때 교통류가 불안정해지므로 더욱 안전 관리에 집중해야 한다는 것을 확인하였다.

In this study, the impact of traffic flow on the market penetration rate of autonomous vehicles(AV) was analyzed using the data for the year 2020 of the Yongin IC~Yangji IC section of Yeongdong Expressway. For this analysis, a microscopic traffic simulation model VISSIM was utilized. To construct the longitudinal control of the AV, the Intelligent Driver Model(IDM) was built and applied, and the driving behavior was verified by comparison with a normal vehicle. An examination of the study results of mobility and safety according to the market penetration rate of the AV, showed that the network's mobility improves as the market penetration rate increases. However, from the point of view of safety, the network becomes unstable when normal vehicles and AVs are mixed, so there should be a focus on traffic management for ensuring safety in mixed traffic situations.

키워드

과제정보

본 논문은 국토교통부/국토교통과학기술진흥원의 지원(과제번호 21AMDP-C160637-01) 및 2020년도 정부(교육부) 재 원으로 한국연구재단의 기초연구사업(NRF-2020R1I1A1A01072166) 지원에 의해 수행되었습니다. 본 논문은 2021년 한국ITS학회 춘계학술대회에 게재되었던 논문을 수정·보완하여 작성하였습니다.

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피인용 문헌

  1. The Impact of Automated Vehicles on Traffic Flow and Road Capacity on Urban Road Networks vol.2021, 2021, https://doi.org/10.1155/2021/8404951