DOI QR코드

DOI QR Code

Traffic Operation Strategy for the Mixed Traffic Flow on Autonomous Vehicle Pilot Zone: Focusing on Pangyo Zero City

자율주행차 혼재 시 시범운행지구 교통운영전략 수립: 판교제로시티를 중심으로

  • Donghyun Lim (Advanced Institutes of Convergence Technology) ;
  • Woosuk Kim (Advanced Institutes of Convergence Technology) ;
  • Jongho Kim (Advanced Institutes of Convergence Technology) ;
  • Hyungjoo Kim (Advanced Institutes of Convergence Technology)
  • 임동현 (차세대융합기술연구원 첨단교통체계연구실 ) ;
  • 김우석 (차세대융합기술연구원 첨단교통체계연구실 ) ;
  • 김종호 (차세대융합기술연구원 첨단교통체계연구실 ) ;
  • 김형주 (차세대융합기술연구원 첨단교통체계연구실 )
  • Received : 2022.11.22
  • Accepted : 2022.12.20
  • Published : 2023.02.28

Abstract

This study was undertaken to strategize the mixed traffic operation of autonomous vehicles in the pilot zone. This was achieved by analyzing the changes expected when autonomous vehicles are mixed in the autonomous vehicle pilot zone. Although finding a safe and efficient traffic operation strategy is required for the pilot zone to serve as a test bed for autonomous vehicles, there is no available operation strategy based on the mixture of autonomous vehicles. In order to presents a traffic operation strategies for each period of autonomous vehicle introduction, traffic efficiency and safety analysis was performed according to the autonomous vehicle market percentage rate. Based on the analysis results, the introduction stage was divided into introductory stage, transition period, and stable period based on the autonomous vehicle market share of 30% and 70%. This study presents the following traffic operation strategies. Considering the traffic flow operation strategy, we suggest the advancement of the existing road infrastructure at the introductory stage, and operating an autonomous driving lane and the mileage system during the transition period. We also propose expanding the operation of autonomous driving lanes and easing the speed limit during the stable period. In the traffic safety strategy, we present a manual and legal system for responding to autonomous vehicle accidents in the introductory stage, an analysis of the causes of autonomous vehicle accidents and the implementation of preventive policies in the transition period, and the advancement of the autonomous system and the reinforcement of the security system during the stable period. Through the traffic operation strategy presented in this study, we foresee the possibility of preemptively responding to the changes of traffic flow and traffic safety expected due to the mixture of autonomous vehicles in the autonomous vehicle pilot zone in the future.

본 연구는 국내 자율주행차 시범운행지구 지정 및 운영에 따라 자율주행차 혼재 시 예상되는 교통 변화를 분석하여, 시범운행지구의 자율주행차 혼재 교통운영전략 수립을 목적으로 한다. 시범운행지구가 자율주행차의 안정적 상용화를 위한 테스트 베드로서의 역할을 해내기 위해서는 안전하고 효율적인 교통운영전략 수립이 요구됨에도 현재까지는 자율주행차 혼재에 따른 교통운영전략은 부재하다. 이에 본 연구에서는 자율주행차 혼재 시 자율주행차 시범운행 지구의 교통운영전략을 수립하고자 한다. 자율주행차 도입 단계별 교통운영전략 수립을 위해 자율주행차 혼입률에 따른 교통 효율성 및 안전성 분석을 수행하였으며, 분석 결과를 토대로 자율주행차 혼입률 30%, 70%를 기준으로 도입기, 과도기, 안정기로 구분하였다. 본 연구에서 자율주행차 도입 단계별로 제시한 교통류와 교통안전 관점의 교통운영전략은 다음과 같다. 교통류 운영전략은 자율주행차 도입기에는 기존 도로 인프라 첨단화, 과도기에는 자율주행차 전용차로 및 일반차 마일리지 제도 운영, 안정기에는 자율주행차 전용차로 확대 운영 및 제한속도 완화를 제시하였다. 교통안전 전략은 도입기에는 자율주행차 사고 발생 대응 매뉴얼 및 법 제도 마련, 과도기에는 자율주행차 사고 원인 분석 및 예방정책 시행, 안정기에는 자율주행차 시스템 고도화 및 보안정책 강화를 제시하였다. 본 연구에서 제시한 교통운영전략을 통해 향후 자율주행차 시범운행지구 내 자율주행차 혼재로 인해 예상되는 교통류 및 교통안전 관에서 선제적으로 대응할 수 있을 것으로 기대된다.

Keywords

Acknowledgement

This work was supported by the Institute for Information & Communication Technology Planning & Evaluation(IITP) grant funded by the Korea government(MSIT) (No. 2021001415).

References

  1. Accenture, https://www.accenture.com/us-en/industries/insurance-index, 2017.11.01.
  2. Atkins-Department for Transport(2016), Research on the impacts of connected and autonomous vehicles(cavs) on traffic low, pp.1-57.
  3. Bruce, G. S., Marie, C. O., Jing, W., Sheila, G. K., Suzanne, E. L. and Thomas, A. D.(2009), "Hard braking events among novice teenage drivers by passenger characteristics", Proceedings of the Fifth International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design 2009 June 22, pp.236-242.
  4. Department of Motor Vehicles(2015-2019), Autonomous Vehicle Collision Reports, Department of Mo torVehicles, United States. Available from www.dmv.ca.gov/portal/vehicle-industry-services/autonomous-vehicles/autonomous-vehicle-collision-reports/, 2021.03.18.
  5. Ekram, A. A. and Rahma, M. S.(2018), "Effects of connected and autonomous vehicles on contraflow operations for emergency evacuation: A microsimulation study", Transportation Research Board 97th Annual Meeting, pp.18-25.
  6. Gyeoggi Research Institute(2016), A study of the measure to support the driving of autonomous vehicles in Pangyo creative economy vally, pp.1-170.
  7. Gyeoggi Research Institute(2020), A study of inferring factors of the commuter's mode choice considering the introduction of the autonomous driving shuttle services, p.3.
  8. Jeong, J. H., Park, J. Y. and Kim, K. Y.(2020), "Evaluation of the effect of urban network on the autonomous and non-autonomous environment using traffic simulation", The 82th Conference of Korea Society of Transportation, p.33.
  9. Jo, Y., Jung, A. R., Oh, C., Park, J. H. and Yun, D. G.(2022), "Suitability Evaluation for Simulated Maneuvering of Autonomous Vehicles", The Journal of the Korea Institute of Intelligent Transport Systems, vol. 21, no. 2, pp.183-200. https://doi.org/10.12815/kits.2022.21.2.183
  10. Joint Ministry(2019), Future Automotive Industry Development Strategy.
  11. Jung, G. Y., Kim, Y. H. and Park, S. Y.(2020), "A Study on diverse preference for driving behaviors of the automated vehicles and the simulation methodology for its impact on the traffic", KOTI Handbook, RR-20-01, pp.1-192.
  12. Kabashkin, I. Y. and Prentkvskis, I.(2017), Reliability and statistics in transportation and communication (1st ed.), Springer International Publishing, Switzerland.
  13. Kesting, A., Treiber, M., Schonhof, M. and Helbing, D.(2008), "Adaptive Cruise Control Design for Active Congestion Avoidance", Transportation Research Report Part C, vol. 16, pp.668-683. https://doi.org/10.1016/j.trc.2007.12.004
  14. Kim, H. J. and Jang, S. E.(2012), "Calculate of the Peak-hour Ratio for Road Traffic Volumes using a Hybrid Clustering Technique", Korean Society of Transportation, vol. 30, no. 1, pp.19-30. https://doi.org/10.7470/jkst.2012.30.1.019
  15. Kim, H. J., Baek, S. C., Yun, D. G. and Park, J. J.(2021), "A Study on the Scenario Development for the Analysis of Mixed Traffic Characteristics Following the Introduction of Freeway Exclusive Lanes for Autonomous Vehicles", Korean Society of Transportation, vol. 39, no. 6, pp.838-848. https://doi.org/10.7470/jkst.2021.39.6.838
  16. Kim, J. H., Lim, D. H., Seo, Y. H., So, J. H. and Kim, H. J.(2022), Influence of dedicated lanes for connected and automated vehicles on highway traffic flow, The Institution of Engineering Technology Intelligent Transport Systems, pp.1-13.
  17. Kim, S. H., Lee, J. H., Kim, Y. J. and Lee, C. W.(2018), "Simulation-Based Analysis on Dynamic Merge Control at Freeway Work Zones in Automated Vehicle Environment", Journal of the Korean Society of Civil Engineering, vol. 38, no. 6, pp.867-878.
  18. Ko, W. R., Park, S. M., So, J. H. and Yun, I. S.(2021), "Analysis of effects of autonomous vehicle market share changes on expressway traffic flow using IDM", The Journal of the Korea Institute of Intelligent Transport Systems, vol. 20, no. 4, pp.13-27. https://doi.org/10.12815/kits.2021.20.4.13
  19. Korea Ministry of Land, Infrastructure and Transport(2020), Ministry of Land, Infrastructure and Transport Notice No. 2020-904.
  20. Korea Ministry of Land, Infrastructure and Transport(2021), Ministry of Land, Infrastructure and Transport Notice No. 2021-337.
  21. Korea Transport Institute(2022), A case study of mobility services in autonomous vehicle demonstration areas, no. 21-07, pp.1-146.
  22. Lee, B. J.(2017), Korea Research Institute for Human Settlements Policy Briff, no. 600, p.1.
  23. Lee, S. Y., Oh, M. S., Oh, C. and Jeong, E. B.(2018), "Automated driving aggressiveness for traffic management in automated driving environments", Journal of Korean Society of Transportation, vol. 36, no. 1, pp.38-50. https://doi.org/10.7470/jkst.2018.36.1.038
  24. Morando, M. M., Trung, L. T. and Vu, H.(2017), "Investigating safety impacts of autonomous vehicles using traffic micro-simulation", Australasian Transport Research Forum 2017, pp.1-6.
  25. Oh, S. H.(2017), Korea Research Institute for Human Settlements Policy Briff, no. 637, p.1.
  26. Oh, W. S., Hieu, N. C., Kim, S. M., Sohn, J. W. and Heo, J.(2016), "Spatial Autocorrelation of Disease Prevalence in South Korea Using 2012 Community Health Survey Data", Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, vol. 34, no. 3, pp.253-262. https://doi.org/10.7848/ksgpc.2016.34.3.253
  27. Opricovic, S. and Tzeng, G. H.(2004), "The Compromise Solution by MCDM Methods: A Comparative Analysis of VIKOR and TOPSIS", European Journal of Operational Research, vol. 156, no. 2, pp.445-455. https://doi.org/10.1016/S0377-2217(03)00020-1
  28. Park, I. S., Lee, J. D., Lee, J. Y. and Hwang, K. Y.(2015), "Impact of automated vehicles on freeway traffic-flow-focused on Seoul-signal basic sections of GyengBu freeway", The Journal of the Korea Institute of Intelligent Transport Systems, vol. 14, no. 6, pp.21-36. https://doi.org/10.12815/kits.2015.14.6.021
  29. Park, J. H.(2020), "A Study of the Application of Product Liability Law to Autonomous Vehicle Accidents", Jeju National university International Law Review, vol. 12, no. 1, pp.69-90.
  30. Park, Y. S.(2017), "Rank Reversal Phenomenon According to Normalization Methods in Quantitative Data", Academic Society of Global Business Administration, vol. 14, no. 6, pp.215-237. https://doi.org/10.38115/asgba.2017.14.6.215
  31. Planung Transport Verkehr(PTV) Group(2021), PTV Vissim 2021 User Manual, p.223.
  32. Prescient & Strategic Intelligence(2020), ADAS Sensor Market Research Report: By Type (Radar, LiDAR, Camera, Ultrasonic), Vehicle Autonomy (Semi-Autonomous Vehicle, Fully-Autonomous Vehicle), Vehicle Type (Passenger Car, Commercial Vehicle), Application (ACC System, AEB System, BSD System, LKAS, AFL System, CTA System, DMS, IPA System, NVS)-Industry Size, Trend, Growth and Demand Forecast to 2030.
  33. Tientrakool, P. C., Ho, Y. C. and Nicholas, F. M.(2011), "Highway Capacity Benefits from Using Vehicle-to-Vehicle Communication and Sensors for Collision Avoidance", Proceeding from Vehicular Technology Conference, pp.1-5.
  34. Transportation Technology and Policy(2009), Microscopic traffic simulation model settlement overview, pp.229-337.
  35. Yook, D. H., Lee, B. J. and Park, J. T.(2018), "Exploring the impacts of autonomous vehicle implementation through microscopic and macros copic approaches", The Journal of the Korea Institute of Intelligent Transport Systems, vol. 17, no. 5, pp.14-28. https://doi.org/10.12815/kits.2018.17.5.14
  36. Yoon, H. S.(2018), The Effects of High School Type on Self-Esteem Change, Seoul National University.
  37. Zhou, J., Ma, F. and Demetsky, M. J.(2012), "Evaluating mobility and sustainability benefits of cooperative adaptive cruise control using agent-based modeling approach", Systems and Information Engineering Design Symposium, pp.74-78.