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

The Korea Institute of Intelligent Transport Systems (한국ITS학회)
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A Study on Extraction Method of Hazard Traffic Flow Segment

고속도로 위험 교통류 구간 추출 방안 연구

  • Chong, Kyusoo (Dept. of Future & Smart Construction Research, Korea Institute of Civil Engineering and Building Technology)
  • 정규수 (한국건설기술연구원 미래스마트건설연구본부)
  • Received : 2021.10.25
  • Accepted : 2021.11.08
  • Published : 2021.12.31
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Abstract

The number of freeway traffic accidents in Korea is about 4,000 as of 2020, and deaths per traffic accident is about 3.7 times higher than other roads due to non-recurring congestion and high driving speed. Most of the accident types on freeways are side and rear-end collisions, and one of the main factors is hazard traffic flow caused by merge, diverge and accidents. Therefore, the hazard traffic flow, which appears in a continuous flow such as a freeway, can be said to be important information for the driver to prevent accidents. This study tried to classify hazard traffic flows, such as the speed change point and the section where the speed difference by lane, using individual vehicle information. The homogeneous segment of speed was classified using spatial separation based on geohash and space mean speed that can indicate the speed difference of individual vehicles within the same section and the speed deviation between vehicles. As a result, I could extract the diverging influence segment and the hazard traffic flow segment that can provide dangerous segments information of freeways.

국내 고속도로 교통사고 건수는 2020년 기준 약 4천건으로, 비반복적 정체와 높은 주행속도로 인해 다른 도로 대비 교통사고 발생 건수 당 사망자 수는 약3.7배에 달한다. 고속도로의 사고 유형은 측면충돌 및 추돌사고가 대부분을 차지하며, 주요 요인 중 하나는 분·합류부, 사고 등으로 야기되는 위험 교통류라고 할 수 있다. 따라서, 고속도로와 같은 연속류에서 나타나는 위험 교통류는 운전자에게 사고 방지를 위한 중요한 정보라고 할 수 있다. 본 연구에서는 개별차량 정보를 이용하여 속도의 변화 지점과 차로별 속도 차이가 발생하는 구간 등 위험 교통류를 분류하고자 하였다. 지오해시 기반으로 공간을 분리하였으며, 동일 구간 내에서 개별 차량의 속도 차이를 나타낼 수 있는 공간평균속도와 차량간 속도 편차를 이용하여 속도의 동질 구간을 분류하였다. 그 결과 고속도로 위험 구간 정보를 제공할 수 있는 분류부 영향권 구간과 위험 교통류 구간을 추출하였다.

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References

  1. Do C.(2009), The Principles of Transportation Engineering (3rd ed.), Seoul: Chong-Mun-Kak, pp.53-59.
  2. Garber N. J. et al.(2002), Traffic & Highway Engineering (3rd ed.), Cengage Learning, p.175.
  3. Kim S. and Ryu J.(2011), "Development of Impulse Propagation Model between Lanes through Temporal-Spatial Analysis," Journal of Korean Society of Transportation, vol. 29, no. 3, pp.123-137.
  4. Kim Y. and Lee S.(2006), "Dynamic O-D Trip estimation Using Real-Time Traffic Data in congestion," The Journal of the Korea Institute of Intelligent Transportation System, vol. 5, no. 1, pp.1-12.
  5. KoROAD(2021), Traffic Accident Analysis System, http://taas.koroad.or.kr/
  6. Kwak H. C.(2013), Real-Time Prediction of Crash Risk by Freeway Segment Types and Traffic Flow State, Doctoral Dissertation, The Graduate School Seoul National University, Korea.
  7. Lee S., Ahn W. and Kang H.(2010), "A Study on Forecasting Traffic Congestion Using IMA (Integrated Moving Average) of Speed Sequence Array," Journal of Civil and Environmental Engineering Research, vol. 30, no. 2D, pp.113-118.
  8. MOCT(2013), Highway Capacity Manual, pp.78-91.
  9. Tian J., Jiang R., Li G., Treiber M., Jia N. and Ma S.(2016), "Cellular automaton model simulating spatiotemporal patterns, phase transitions and concave growth pattern of oscillations in traffic flow," Transportation Research Part B: Methodological, vol. 93, pp.560-575. https://doi.org/10.1016/j.trb.2016.08.008
  10. Vukovic T.(2016), Hilbert-Geohash-Hashing Geographical Point Data Using the Hilbert Space-Filling Curve, Master's Thesis, NTNU, Trondheim, Norway.
  11. Zheng S., Jiang R., Jia B., Tian J. and Gao Z.(2020), "Impact of Stochasticity on Traffic Flow Dynamics in Macroscopic Continuum Models Show less," Journal of the Transportation Research Board, vol. 2674, no. 10, pp.690-704. https://doi.org/10.1177/0361198120937704