• Title/Summary/Keyword: Accident risk management algorithm

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Characteristics of Ship Movements in a Fairway

  • Kim, Eun Kyung;Jeong, Jung Sik;Park, Gyei-Kark;Im, Nam Kyun
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.12 no.4
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    • pp.285-289
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    • 2012
  • In a coastal area, all of the vessels are always exposed to the potential risk, taking into the maritime accident statistics account over the last decades. To manage vessels underway safety, the characteristics of ship movements in a fairway should be recognized by VTS system or VTS operators. The IMO has already mandated the shipboard carriage of AIS since 2004, as stated in SOLAS Chapter V Regulation 19. As a result, the static and dynamic information of AIS data has been collected for vessel traffic management in the coastal areas and used for VTS. This research proposes a simple algorithm of recognizing potentially risky ships by observing their trajectories on the fairway. The static and dynamic information of AIS data are collected and the curvature for the ship trajectory is surveyed. The proposed algorithm finds out the irregularity of ship movement. The algorithm effectively monitors the change of navigation pattern from the curvature analysis of ship trajectory. Our method improves VTS functions in an intelligent way by analyzing the navigation pattern of vessels underway.

Study on Fatality Risk of Older Driver and Traffic Accident Cost (고령운전자 연령구간별 사망사고 발생위험도와 사고비용 분석 연구)

  • Choi, Jaesung
    • Journal of the Korean Society of Safety
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    • v.33 no.4
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    • pp.111-118
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    • 2018
  • Korea is facing a surge in the aging population, showing that population aged 65 and above will be accounted for 42.5% of the total population in 2065 with the emphasis on the over-80 population consisting of 19.2%. In response to this abrupt change in population structure, the number of traffic fatality accident referring to older driver as aged 65+ years had been increasing from 605 fatalities in 2011 to 815 fatalities in 2015 resulting in increases in 34.7% in oppose to happening to decreases in 17.2% about non-older driver. With Logit analysis based on Newton-Raphson algorithm utilizing older driver's traffic fatality data for the 2011-2015 years, it was found that the likelihood of an accident resulting in a fatality for super older driver aged 80 years and above considerably increased compared to other older driver with aging classification: 2.24 times for violation of traffic lane, 2.04 times for violation of U-turn, 1.48 times for violation of safety distance, 1.35 times for violation of obstacle of passing; also average annual increase of traffic accident cost related to super older driver was fairly increased rather than other older driver groups. Hence, this study proposes that improving and amending transport safety system and Road Traffic Act for super older driver needs to be urgently in action about license management, safe driving education, etc. when considering the increase of over-80 population in the near future. Also, implementing a social agreement with all ages and social groups to apply with advanced driver assistance system for older driver groups will be able to become a critical factor to enhance safe driving over the face of the country.

Classification of Characteristics in Two-Wheeler Accidents Using Clustering Techniques (클러스터링 기법을 이용한 이륜차 사고의 특징 분류)

  • Heo, Won-Jin;Kang, Jin-ho;Lee, So-hyun
    • Knowledge Management Research
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    • v.25 no.1
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    • pp.217-233
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    • 2024
  • The demand for two-wheelers has increased in recent years, driven by the growing delivery culture, which has also led to a rise in the number of two-wheelers. Although two-wheelers are economically efficient in congested traffic conditions, reckless driving and ambiguous traffic laws for two-wheelers have turned two-wheeler accidents into a significant social issue. Given the high fatality rate associated with two-wheelers, the severity and risk of two-wheeler accidents are considerable. It is, therefore, crucial to thoroughly understand the characteristics of two-wheeler accidents by analyzing their attributes. In this study, the characteristics of two-wheeled vehicle accidents were categorized using the K-prototypes algorithm, based on data from two-wheeled vehicle accidents. As a result, the accidents were divided into four clusters according to their characteristics. Each cluster showed distinct traits in terms of the roads where accidents occurred, the major laws violated, the types of accidents, and the times of accident occurrences. By tailoring enforcement methods and regulations to the specific characteristics of each type of accident, we can reduce the incidence of accidents involving two-wheelers in metropolitan areas, thereby enhancing road safety. Furthermore, by applying machine learning techniques to urban transportation and safety, this study adds to the body of related literature.

A Study on Developing the Compliance for Infringement Response and Risk Management of Personal Information to Realize the Safe Artificial Intelligence Services in Artificial Intelligence Society (지능정보사회의 안전한 인공지능 서비스 구현을 위한 개인정보 침해대응 및 위기관리 컴플라이언스 개발에 관한 연구)

  • Shin, Young-Jin
    • Journal of Convergence for Information Technology
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    • v.12 no.5
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    • pp.1-14
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    • 2022
  • This study tried to suggest crisis management compliance to prevent personal information infringement accidents that may occur in the process because the data including personal information is being processed in the artificial intelligence (AI) service process. To this end, first, the AI service provision process is divided into 3 processes such as service planning/data design and collection process, data pre-processing and purification process, and algorithm development and utilization process. And 3 processes are subdivided into 9 stages following to personal information processing stages to infringe personal information. All processes were investigated with literature and experts' Delphi. Second, the investigated personal information infringement factors were selected through FGI, Delphi, etc. for experts. Third, a survey was conducted with experts on the severity and possibility of each personal information infringement factor, and the validity and adequacy of the 94 responses were verified. Fourth, to present appropriate risk management compliance for personal information infringement factors in AI services, a method for calculating the risk level of personal information infringement is prepared by utilizing the asset value of personal information, personal information infringement factors, and the possibility of infringement accidents. Through this, the countermeasures for personal information infringement incidents were suggested according to the scored risk level.