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Impacts of Automated Vehicles on Traffic Flow Changes

자율주행자동차 도입으로 인한 교통흐름 변화 분석

  • 정승원 (홍익대학교 과학기술연구소) ;
  • 문영준 (한국교통연구원 교통기술연구소) ;
  • 이성렬 (삼성교통안전문화연구소) ;
  • 황기연 (홍익대학교 도시공학과)
  • Received : 2017.11.24
  • Accepted : 2017.12.20
  • Published : 2017.12.31

Abstract

Traffic congestion occurs from drivers' human factors such as driver reaction time, reckless lane change, and inexperienced driving. When Automated Vehicles are introduced, human factors are excluded, resulting in increased average vehicle speed, stabilizing traffic flow, and increasing road capacity. This study analyzed traffic flow changes through traffic volume-speed-density plots, and increased road capacity due to Automated Vehicles. As a result of the analysis, when rate of automated vehicles gests higher, the traffic flow became stable. Additionally, it was analyzed that when all vehicles were automated, the road capacity increased by about 120 %. It is expected that there will be a positive expectation in terms of traffic congestion and traffic demand management due to the introduction of Automated Vehicles.

교통혼잡은 운전자의 인지반응시간, 운전미숙, 무리한 차로변경 등 인적요인으로부터 발생된다. 자율주행자동차가 도입되면 이러한 인적요인들이 배제되고 군집주행으로 인해 평균주행속도 상승, 교통흐름 안정화, 도로용량 증대 효과가 예상된다. 본 연구는 자율주행자동차도입으로 인한 교통흐름 변화를 교통량-밀도-속도 산포도 그래프를 통해 분석하고, 도로용량 증대 효과를 도출하였다. 분석 결과, 자율주행자동차의 혼입율이 높아질수록 교통량-밀도-속도의 그래프 곡선이 완화되며, 폭이 줄어들어 교통류가 안정적으로 변화하였다. 또한 자율주행자동차 혼입율 100%에서는 도로용량이 약 120% 증대되는 것으로 분석되었다. 자율주행자동차 도입으로 인한 교통혼잡개선 및 교통수요관리 측면에서 긍정적인 기대효과가 있을 것으로 분석되었다.

Keywords

References

  1. 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, no. 1, pp.10-18. https://doi.org/10.1007/s11633-014-0760-2
  2. Arnaout, G. M., Khasawneh M. T., Zhang J. and Bowling S. R.(2010), "An IntelliDrive application for reducing traffic congestions using agent-based approach," Systems and Information Engineering Design Symposium, pp.221-224.
  3. Broen N. L. and Chiang D. P.(1996), "Braking response times for 100 drivers in the avoidance of an unexpected obstacle as measured in a driving simulator," Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 40, no. 18, pp.900-904.
  4. Fambro D., Koppa R., Picha D. and Fitzpatrick K.(1998), "Driver perception-brake response in stopping sight distance situations," Transportation Research Record: Journal of the Transportation Research Board, vol. 1628, pp.1-7. https://doi.org/10.3141/1628-01
  5. Green M.(2000), "How long does it take to stop? Methodological analysis of driver perception-brake times," Transportation human factors, vol. 2, no. 3, pp.195-216. https://doi.org/10.1207/STHF0203_1
  6. Kesting A., Treiber M. and Helbing D.(2007), "General lane-changing model MOBIL for car-following models," Transportation Research Record: Journal of the Transportation Research Board, vol. 1999, pp.86-94. https://doi.org/10.3141/1999-10
  7. Kesting A., Treiber M., Schonhof M. and Helbing D.(2008), "Adaptive cruise control design for active congestion avoidance," Transportation Research Part C, vol. 16, no. 6, pp.668-683. https://doi.org/10.1016/j.trc.2007.12.004
  8. Lee J. D., Park I. S. and Hwang K. Y.(2015), "Comparative traffic analysis between electric personal mobility and partial autonomous vehicle using agent-based model," The Korea Transport Institute, Journal of Transportation Research, vol. 22, no. 1, pp.27-44.
  9. Ma J., Zhou F., and Demetsky M. J.(2012), "Evaluating mobility and sustainability benefits of cooperative adaptive cruise control using agent-based modeling approach," Systems and Information Design Symposium (SIEDS) 2012 IEEE, pp.74-78.
  10. Olson P. L. and Sivak M.(1986), "Perception-response time to unexpected roadway hazards," Human Factors, vol. 28, no. 1, pp.91-96. https://doi.org/10.1177/001872088602800110
  11. Park I. S., Lee J. D., Lee J. Y. and Hwang K. Y.(2015), "Impacts of Automated Vehicles on Freeway Traffic-flow-Focused on Seoul-Singal Basic Sections of GyeongBu 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
  12. Shladover S., Su D. and Lu X. Y.(2012), "Impacts of cooperative adaptive cruise control on freeway traffic flow," Transportation Research Record: Journal of the Transportation Research Board, vol. 2324, pp.63-70. https://doi.org/10.3141/2324-08
  13. Van Arem B., Van Driel C. J. and Visser R.(2006), "The impact of cooperative adaptive cruise control on traffic-flow characteristics," IEEE Transactions on Intelligent Transportation Systems, vol. 7, no. 4, pp.429-436. https://doi.org/10.1109/TITS.2006.884615
  14. Vander Werf J., Shladover S., Miller M. and Kourjanskaia N.(2002), "Effects of adaptive cruise control systems on highway traffic flow capacity," Transportation Research Record: Journal of the Transportation Research Board, vol. 1800, pp.78-84. https://doi.org/10.3141/1800-10

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