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

The Korea Institute of Intelligent Transport Systems (한국ITS학회)
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Analysis of Crash Potential by Vehicle Interactions Using Driving Simulations

주행 시뮬레이션을 이용한 차량간 상호작용에 따른 사고발생가능성 분석

  • Kim, Yunjong (Dept. of Transportation and Logistics Eng., Hanyang University) ;
  • Oh, Cheol (Dept. of Transportation and Logistics Eng., Hanyang University) ;
  • Park, Subin (Dept. of Transportation and Logistics Eng., Hanyang University) ;
  • Choi, Saerona (Transportation Safety Research & Development Institute, Korea Transportation Safety Authority)
  • 김윤종 (한양대학교 교통.물류공학과) ;
  • 오철 (한양대학교 교통.물류공학과) ;
  • 박수빈 (한양대학교 교통.물류공학과) ;
  • 최새로나 (한국교통안전공단 교통안전연구개발원)
  • Received : 2018.01.02
  • Accepted : 2018.03.06
  • Published : 2018.04.30
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Abstract

Intentional aggressive driving (IAD) is a very dangerous driving behavior that threatens to attack the adjacent vehicles. Most existing studies have focused on the independent driving characteristics of attack drivers. However, the identification of interactions between the offender and the victim is necessary for the traffic safety analysis. This study established multi-agent driving simulation environments to systematically analyze vehicle interactions in terms of traffic safety. Time-to-collision (TTC) was adopted to quantify vehicle interactions in terms of traffic safety. In addition, a exponential decay function was further applied to compare the overall pattern of change in crash potentials when IAD events occurred. The outcome of this study would be useful in developing policy-making activities to enhance traffic safety by reducing dangerous driving events including intentional aggressive driving.

공격운전은 상대방 운전자에 대한 공격 의지를 가지고 위협을 가하는 매우 위험한 운전행태이다. 기존 연구의 경우 공격운전자에 대한 주행특성 및 유발요인 등 공격운전자를 초점으로 한 연구가 대부분인 것으로 나타났다. 그러나 공격운전을 안전성 관점에서 분석하기 위해서는 공격운전 가해자와 피해자간의 상호작용에 대한 분석이 필요하다. 따라서 본 연구에서는 Multi-Agent 주행시뮬레이션 환경을 구축하여 공격운전 가해자와 공격운전 피해자간의 차량간격 및 상대속도를 통해 상호작용을 분석하였다. 공격운전 가해자와 피해자의 가감속 패턴을 파악하고 차간거리를 통해 TTC(Time-to-Coillison)를 도출하였다. 또한 도출된 TTC를 EDF(Exponential Decay Function)를 통해 사고발생가능성으로 전환하여 일반운전과 공격운전의 사고발생가능성을 분석하였다. 분석결과, 공격운전 시 일반운전에 비해 사고발생가능성이 높은 것으로 나타났다. 본 연구결과를 통해 공격운전의 위험성을 경고하며, 공격운전 관리방안 수립을 위한 기초연구로 활용될 수 있을 것으로 기대된다.

Keywords

References

  1. Allen B. L., Shin B. T. and Cooper P. J.(1978), Analysis of Traffic Conflicts and Collisions (No. HS-025 846).
  2. Bogdan S. R., Mairean C. and Havarneanu C. E.(2016), "A meta-analysis of the association between anger and aggressive driving," Transportation research part F: traffic psychology and behaviour, vol. 42, pp.350-364. https://doi.org/10.1016/j.trf.2016.05.009
  3. Duan J., Li Z. and Salvendy G.(2013), "Risk illusions in car following: Is a smaller headway always perceived as more dangerous?," Safety science, vol. 53, pp.25-33. https://doi.org/10.1016/j.ssci.2012.09.007
  4. Habtemichael F. and Picado-Santos L.(2013), "Sensitivity analysis of VISSIM driver behavior parameters on safety of simulated vehicles and their interaction with operations of simulated traffic," In 92nd Annual Meeting of the Transportation Research Board, Washington, DC., January.
  5. Habtemichael F. G. and de Picado Santos L.(2014), "Crash risk evaluation of aggressive driving on motorways: microscopic traffic simulation approach," Transportation research part F: traffic psychology and behaviour, vol. 23, pp.101-112. https://doi.org/10.1016/j.trf.2013.12.022
  6. Hayward J. C.(1972), Near miss determination through use of a scale of danger.
  7. Hyden C.(1987), "The development of a method for traffic safety evaluation: The Swedish Traffic Conflicts Technique," Bulletin Lund Institute of Technology, Department, no. 70.
  8. Kim S. J., Jung C. S. and Jang S. Y.(2016), "A Study on Preparing Measures for Reducing Aggressive Driving and Road Rage by Analysing Mechanism of How the Driving Behavior Determinants and Dangerous Driving Behavior Factors Affect Aggressive Driving and Road Rage: Targeting Traffic Law Violator and Assaulter of a Traffic Accident," Journal of Korean Society of Transportation, vol. 34, no. l, pp.15-28. https://doi.org/10.7470/jkst.2016.34.1.015
  9. Minderhoud M. M. and Bovy P. H.(2001), "Extended time-to-collision measures for road traffic safety assessment," Accid. Anal. Prev. vol. 33, no. 1, pp.89-97. https://doi.org/10.1016/S0001-4575(00)00019-1
  10. National Highway Traffic Safety Administration(2009), Aggressive driving enforcement. Strategies for implementing best practices.
  11. Oh C. and Kim T.(2010), "Estimation of rear-end crash potential using vehicle trajectory data," Accident Analysis & Prevention, vol. 42, no. 6, pp.1888-1893. https://doi.org/10.1016/j.aap.2010.05.009
  12. Oh J. S. and Lee S. C.(2012), "Discriminating Risky Drivers Using Driving Behavior Determinants," Korean J. Psychological Social Issues, vol. 18, no. 3, pp.415-433.
  13. Sin Y. G., Ryu J. B. and Gang S. C.(2007), "Predicting Aggressive Driver Behavior Using a Driving Simulator (RTSA-DS)," Journal of Korean Society of Transportation, vol. 25, no. 3, pp.45-54.
  14. Xiong Z. and Olstam J.(2015) "Orchestration of driving simulator scenarios based on dynamic actor preparation and automated action planning," Transportation Research Part C: Emerging Technologies, vol. 56, pp.120-131. https://doi.org/10.1016/j.trc.2015.02.008
  15. Yan X., Xue Q., Ma L. and Xu Y.(2014), "Driving-simulator-based test on the effectiveness of auditory red-light running vehicle warning system based on time-to-collision sensor," Sensors, vol. 14, no. 2, pp.3631-3651. https://doi.org/10.3390/s140203631
  16. Yannis G., Golias J. and Antoniou C.(2004), "Combining traffic simulation and driving simulator analyses for Advanced Cruise Control system impact identification," In Proceedings of the 83rd Annual Meeting of the Transportation Research Board, January, pp.11-14.