• Title/Summary/Keyword: Intentional aggressive driving

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Development of a Methodology for Detecting Intentional Aggressive Driving Events Using Multi-agent Driving Simulations (Multi-agent 주행 시뮬레이션을 이용한 운전자 주행패턴을 반영한 공격운전 검지기법 개발)

  • KIM, Yunjong;OH, Cheol;CHOE, Byongho;CHOI, Saerona;KIM, Kiyong
    • Journal of Korean Society of Transportation
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    • v.36 no.1
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    • pp.51-65
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    • 2018
  • Intentional aggressive driving (IAD) is defined as a hazardous driving event that the aggressive driver intentionally threatens neighbor drivers with abrupt longitudinal and lateral maneuvering. This study developed a methodology for detecting IAD events based on the analysis of interactions between aggressive driver and normal driver. Three major aggressive events including rear-close following, side-close driving, and sudden deceleration were analyzed to develop the algorithm. Then, driving simulation experiments were conducted using a multi-agent driving simulator to obtain data to be used for the development of the detection algorithm. In order to detect the driver's intention to attack, a relative evaluation index (Erratic Driving Index, EDI) reflecting the driving pattern was derived. The derived IAD event detection algorithm utilizes both the existing absolute detection method and the relative detection method. It is expected that the proposed methodology can be effectively used for detecting IAD events in support of in-vehicle data recorder technology in practice.

Analysis of Crash Potential by Vehicle Interactions Using Driving Simulations (주행 시뮬레이션을 이용한 차량간 상호작용에 따른 사고발생가능성 분석)

  • Kim, Yunjong;Oh, Cheol;Park, Subin;Choi, Saerona
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.17 no.2
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    • pp.98-112
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    • 2018
  • 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.