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Level 3 자율주행버스 실주행 데이터를 활용한 제어권 전환 영향 요인 분석

Analysis of Factors Affecting Disengagement Using Actual Driving Data in Level 3 Autonomous Bus

  • 이은선 (경기대학교 도시.교통공학과) ;
  • 신치현 (경기대학교 도시.교통공학과)
  • EunSeon Lee (Dept. of Urban & Transportation Eng., Kyonggi University) ;
  • ChiHyun Shin (Dept. of Urban & Transportation Eng., Kyonggi University)
  • 투고 : 2024.08.16
  • 심사 : 2024.09.24
  • 발행 : 2024.10.31

초록

정부는 2025년까지 Level 4 자율주행 버스·셔틀 상용화를 목표로 현재 도심부 도로에서 Level 3 자율주행버스의 실증을 확대하고 있으나 도심 환경의 다양한 주행 영향 요인으로 인해 안전 문제가 지속적으로 제기되고 있다. 본 연구는 판교에서 운행 중인 자율주행버스의 실주행 데이터를 활용하여 제어권 전환 다발 지점을 식별하고 정적 및 동적 도로환경요인 분석을 통해 영향 요인을 도출하였다. 분석 결과, 제어권 전환은 교차로와 버스정류장 부근에서 자주 발생하며 정류장의 존재가 전환 발생 확률을 증가시키는 것으로 나타났다. 그러나 이는 운전자의 잦은 자의적 개입 때문인 것으로 추정되어 이 변수를 제외하고 분석한 결과, 횡단보도 수 및 진출입로의 존재와 동적 요인인 안개와 비가 제어권 전환 발생 확률을 높이는 것으로 나타났다. 이를 바탕으로 자율주행버스의 운행 안전성 향상과 서비스의 신뢰도 제고를 위해 제어권 전환 최소화를 위한 개선 방향을 제안하였다.

The government aims to commercialize Level 4 autonomous buses and shuttles by 2025, expanding the demonstration of Level 3 autonomous buses on urban streets, where various factors affecting the driving conditions raise safety concerns. This study used actual driving data from autonomous buses in Pangyo to identify the disengagement locations and analyzed the static and dynamic road environment factors. The results showed that the disengagement of autonomous buses frequently occurs near intersections and bus stops, with those at the bus stops due primarily to operational procedures requiring driver intervention. Excluding these, the analysis identified crosswalks and driveways as static factors, whereas fog and rain are dynamic factors affecting disengagements. Based on these findings, recommendations were proposed to minimize disengagements, aiming to improve the operational safety of autonomous buses in Korea and address upcoming challenges.

키워드

과제정보

본 연구는 국토교통부/국토교통과학기술진흥원 자율주행기술개발혁신사업 연구개발과제의 지원으로 수행되었습니다(RS-2023-KA160881, 자율협력주행을 위한 미래도로 설계 및 실증 기술 개발).

참고문헌

  1. Cho, H. J.(2003), "Analysis of hazardous fog and index development in Korea", Journal of the Korean Geographical Society, vol. 38, no. 4, pp.478-489. 
  2. Cho, N. H., Jun, C. M. and Kang, Y. O.(2018), "A visualization of traffic accidents hotspot along the road network", Journal of Cadastre & Land InformatiX, vol. 48, no. 1, pp.201-213. 
  3. Choi, S. K. and Shin, C. H.(2023), "Analysis of driving behavior and capacity estimation using actual traffic data of autonomous vehicles at signalized intersections", Journal of Korean Society of Transportation, vol. 41, no. 5, pp.624-637. 
  4. Electronics and Telecommunications Research Institute(2021), Guidelines for human factors in take-over for the safe introduction of autonomous vehicles, pp.8-35. 
  5. Hyun, S. H., Son, J. W., Oh, Y. C., Han, J. H. and You, B. Y.(2022), "Analysis of autonomous vehicle disengagement under urban environment", The Korean Society of Automotive Engineers Spring Conference, pp.1270-1271. 
  6. Kim, S. H.(2022), "Autonomous vehicles: Current and future perspective", The Korean Institute of Electrical Engineers, vol. 71, no. 4, pp.29-32. 
  7. Kim, S. H.(2024), Improving autonomous driving operation based on frequent takeover zones and factor analysis using autonomous driving data, University of Seoul. 
  8. Kim, T. Y., Maeng, J. Y., Kang, K. P. and Bae, S. H.(2023), "Spatial factors' analysis of affecting on automated driving safety using spatial information analysis based on level 4 ODD elements", The Journal of The Korea Institute of Intelligent Transport Systems, vol. 22, no. 5, pp.182-199. 
  9. Korea Meteorological Administration Weather, https://www.weather.go.kr/w/observation/land/awsobs.do, 2024.05.20. 
  10. Lee, E. J., Kim, H. J., Lim, D. H. and Seo, Y. H.(2023), "Development of monitoring indicators for safe autonomous vehicle operation: Case study of Pangyo Zero City", Traffic Safety Research, vol. 42, no. 2, pp.49-76. 
  11. Ministry of Land, Infrastructure and Transport(2024), Freeways are also being designated as autonomous vehicle demonstration areas, and autonomous truck/freight transportation is around the corner.
  12. Naver Map, https://map.naver.com, 2024.07.20. 
  13. Park, S. H., Yun, Y. W., Ko, H. G., Jeong, H. R. and Yun, I. S.(2020), "Analysis of the influence of road.traffic conditions and weather on the take-over of a conditional autonomous vehicle", The Journal of The Korea Institute of Intelligent Transport Systems, vol. 19, no. 6, pp.235-249. 
  14. Urban Traffic Information Center, http://www.utic.go.kr/, 2024.07.01. 
  15. Weather i, https://www.weatheri.co.kr/, 2024. 05. 20. 
  16. Woo, B. R., Lee, J. W. and Tak, S. H.(2023), "The effect of road environmental factors on the severity of autonomous vehicle accidents", Journal of Transport Research, vol. 30, no. 4, pp.15-24. 
  17. Yun, H. N., Kim, S. L., Lee, J. W. and Yang, J. H.(2018), "Analysis of cause of disengagement based on US California DMV autonomous driving disengagement report", Transactions of the Korean Society of Automotive Engineers, vol. 26, no. 4, pp.464-475.