DOI QR코드

DOI QR Code

자율주행 자동차 도입 수준에 따른 도시부 도로 탄소배출량 감소효과 추정

Estimation of Carbon Emissions Reductions by the Penetration Rates of Autonomous Vehicles for Urban Road Network

  • 이혁준 (한양대학교 도시대학원 도시.지역개발경영학과) ;
  • 박종한 (한양대학교 도시대학원 도시.지역개발경영학과) ;
  • 고준호 (한양대학교 도시대학원 도시.지역개발경영학과)
  • Lee, Hyeok Jun (Graduate School of Urban Studies, Hanyang Univ) ;
  • Park, Jong Han (Graduate School of Urban Studies, Hanyang Univ) ;
  • Ko, Joonho (Graduate School of Urban Studies, Hanyang Univ)
  • 투고 : 2021.10.25
  • 심사 : 2021.12.07
  • 발행 : 2021.12.31

초록

최근 활발한 기술개발이 이루어지고 있는 자율주행 자동차는 다양한 교통문제를 해결하는 데 기여할 것으로 기대되고 있다. 국내 도로부문 온실가스 배출량이 1억 톤이 넘는 등 환경오염 문제가 심각해지면서 자율주행 자동차 도입에 따른 환경오염의 절감 부문에 대한 연구가 필요하다. 하지만 환경오염 절감 측면에서 자율주행에 관련한 실증적 연구는 미비한 상태이다. 이에 본 연구는 미시 시뮬레이션을 통해 서울시 개포동 일대 교차로 8개소를 대상으로 자율주행 자동차 도입에 따른 네트워크 성능변화를 분석하고 이를 통해 이산화탄소 배출량을 추정하였다. 분석결과 내연기관 자율주행 자동차 혼입 시 네트워크 전체 탄소 절감효과는 미미하였으며 혼입율이 적은 상황에서는 오히려 증가하기도 했다. 반면 자율주행 전기자동차 혼입 시 네트워크 전체 탄소 발생량이 크게 감소하는 것으로 분석되었다. 자율주행 자동차 도입만으로는 충분한 탄소배출량 감소 효과를 얻기는 어려우며 적절한 수요관리와 근본적인 연료사용의 전환을 통해 교통 부문 탄소배출을 줄여나가야할 것으로 보인다.

Recently, Autonomous Vehicle(AV) has been expected to solve various transportation problems. s the problem of environmental pollution become serious, research to reduce pollution is needed. However, empirical research on AV related pollution is insufficient. Based on this background, this study analyzed network performance changes and CO2 emissions introduc AVs and Electric Vehicles(EV) in eight intersections. The results show that when AVs with internal combustion engines were, the effect of carbon reduction over the network was insignificant. On the other hand, it was that the total amount of CO2 generated in the network decreased significantly when EVs and autonomous electric vehicles were emissions in the transportation sector.

키워드

과제정보

본 논문은 2021년 경찰청의 재원으로 도로교통공단의 지원을 받아 수행된 연구임.(1325163972, 자율주행을 위한 AI기반 신호제어시스템 개발) 본 논문은 한국ITS학회 2021년도 추계학술대회(2021.10.25)에서 발표된 내용을 수정.보완하여 작성된 것입니다.

참고문헌

  1. Anderson J. M., Kalra N., Stanley K. D., Sorensen P., Samaras C. and Olumatola O. A.(2014), Autonomous Vehicle Technology: A guide for policymakers, Santa Monica: RAND Corporation.
  2. Arnaout G. M. and Bowling S.(2014) "A progressive deployment strategy for cooperative adaptive cruise control to improve traffic dynamics," International Journal of Automation and Computing, vol. 11, pp.10-18. https://doi.org/10.1007/s11633-014-0760-2
  3. Barth M. and Boriboonsomsin K.(2009), "Energy and emissions impacts of a freeway-based dynamic eco-driving system," Transport. Research Part D: Transport Environment, vol. 14, pp.400-410. https://doi.org/10.1016/j.trd.2009.01.004
  4. Choi J. E. and Bae S. H.(2010), "Development of Quantitative Analysis Methodology on Environmental Effect through Adaptation of Advanced Safety Vehicle," J. Korea Inst. Intell. Transp. Syst., vol. 9, no. 6, pp.94-104.
  5. Dokic J., Muller B. and Meyer G.(2015), European Roadmap Smart Systems for Automated Driving, Berlin: EPoSS(European Technology Platform on Smart Systems Integration).
  6. Fagnant D. and Kockelman K. M.(2015), "The travel and environmental implications of shared autonomous vehicles, using agent-based model scenarios," Transportation Research Part C: Emerging Technologies, vol. 40, pp.1-13. https://doi.org/10.1016/j.trc.2013.12.001
  7. Fernandez P. and Nunes U.(2012), "Platooning with IVC-enabled autonomous vehicles: Strategies to mitigate communication delays, improve safety and traffic flow," IEEE Transactions on Intelligent Transportation Systems, vol. 13, no. 1, pp.91-106. https://doi.org/10.1109/TITS.2011.2179936
  8. Golbabaei F. and Yigitcanlar T.(2020), "The role of shared autonomous vehicle systems in delivering smart urban mobility: A systematic review of the literature," International Journal of Sustainable Transportation, vol. 15, no. 10, pp.731-748. https://doi.org/10.1080/15568318.2020.1798571
  9. Greenblatt J. and Saxena S.(2015), "Autonomous taxis could greatly reduce greenhouse-gas emissions of US light-duty vehicles," Nature Clim Change, vol. 5, pp.860-863. https://doi.org/10.1038/nclimate2685
  10. Harper Corey D., Chris T. H, Sonia M. and Constantine S.(2016), "Estimating potential increases in travel with autonomous vehicles for the non-driving, elderly and people with travel-restrictive medical conditions," Transportation Research Part C: Emerging Technologies, vol. 72, pp.1-9. https://doi.org/10.1016/j.trc.2016.09.003
  11. Hartmann M., Motamedidehkordi N., Krause S., Hoffmann S., Vortisch P. and Busch F.(2017), "Impact of automated vehicles on capacity of the german freeway network," ITS World Congress 2017 Compendium of Papers.
  12. Hensher D. A.(2018), "Tackling road congestion-What might it look like in the future under a collaborative and connected mobility model?," Transport Policy, vol. 66, pp.A1-A8. https://doi.org/10.1016/j.tranpol.2018.02.007
  13. JRC R. E., HASS H., LARIVE J. F., JRC L. L., MAAS H. and Rickeard D.(2014), WELL-TO-WHEELS Report Version 4. a JEC WELL-TO-WHEELS ANALYSIS, Institute for Energy and Transport, Joint Research Centre, Luxembourg: Publications Office of the European Union, 2014.
  14. Kang M. O., Kang G. K., Lee S. Y., Han S. W., Min D. K. and Lee B. J.(2009), Research on the Mitigation Potentioals and Mitigation Policies of the Transport and Buildings in Korea, Korea Environment Institute, pp.1-224.
  15. KOTEMS(Korea Transport Emission Management System), Transport Emission Statistics, https://www.kotems.or.kr/app/kotems/forward?pageUrl=/kotems/ptl/emissionstat/total/KotemsPtlEmissionstatTotalEmissionLs&topmenu1=02&topmenu2=01&topmenu3=02, 2021.8.28.
  16. Lee S. M.(2016), A Basic Study on the Eco-friendliness of Autonomous Vehicles, Korea Environment Institute, pp.1-36.
  17. Lee T. H.(2016), "Paris Agreement and Urban Energy Transition: A Lesson for Seoul's Energy and Climate Policy," Space and Environment, vol. 55, pp.48-78.
  18. Lu Q., Tettamanti T., Horcher D. and Varga I.(2019), "The impact of autonomous vehicles on urban traffic network capacity: An experimental analysis by microscopic traffic simulation," Transportation Letters, vol. 12, no. 8, pp.1-10.
  19. National Institute of Environmental Research(2013), National Air Pollutant Emission Calculation Method Manual.
  20. Olia A., Abdelgawad H., Abdulhai B. and Razavi S. N.(2016), "Assessing the potential impacts of connected vehicles: mobility, environmental, and safety perspectives," Journal of Intelligent Transportation Systems, vol. 20, pp.229-243. https://doi.org/10.1080/15472450.2015.1062728
  21. Park J. Y., Wu S. K. and Lee D. Y.(2018), Impact Analysis of Autonomous Vehicles and Policy Implications, The Korea Transport Institute, pp.1-200.
  22. Pinjari A. R., Augustin B. and Menon N.(2013), Highway Capacity Impacts of Autonomous Vehicles: An assessment, Tampa: University of South Florida.
  23. Song J., Wu Y., Xu Z. and Lin X.(2014), "Research on car-following model based on SUMO," The 7th IEEE/International Conference on Advanced Infocomm Technology, pp.47-55.
  24. Sperling D.(2018), Three Revolutions, Steering Automated, Shared, and Electric Vehicles To a Better Future, Island Press, p.15.
  25. Tientrakool P., Ho Y. and Maxemchuk N. F.(2011), "Highway Capacity Benefits from Using Vehicle-to-Vehicle Communication and Sensors for Collision Avoidance," Vehicular Technology Conference (VTC Fall).
  26. Underwood S. E.(2014), "Disruptive innovation on the path to sustainable mobility: Creating a roadmap for road transportation in the United States," In Road Vehicle Automation, Springer, pp.157-168.
  27. Wadud Z., MakKenzie D. and Leiby P.(2016), "Help of Hindrance? The Travel, Energy and Carbon Impacts of Highly Automated Vehicles," Transportation Research Part A.: Policy and Practice, vol. 86, pp.1-18. https://doi.org/10.1016/j.tra.2015.12.001