• Title/Summary/Keyword: vehicle accidents

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A Study on the Classification of the Car Accidents Types based on the Negligence Standards of Auto Insurance (자동차보험 과실기준 기반 자동차사고유형 체계화에 관한 연구)

  • Park, Yohan;Park, Wonpil;Kim Seungki
    • Journal of Auto-vehicle Safety Association
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    • v.13 no.4
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    • pp.53-59
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    • 2021
  • According to the Korean Traffic Accident Analysis System (TAAS), more than 200,000 traffic accidents occur every year. Also, the statistics including auto insurance companies data show 1.3 million traffic accidents. In the case of TAAS, the types of traffic accidents are simply divided into four; frontal collision, side collision, rear collision, and rollover. However, more detailed information is needed to assess for advanced driver assist systems at intersections. For example, directional information is needed, such as whether the vehicle in the car accident way in a straight or a left turn, etc. This study intends to redefine the type of accident with the more clear driving direction and path by referring to the Negligence standards used in automobile insurance accidents. The standards largely divide five categories of car-to-car/motorcycle /pedestrian/cyclist, and highway, and the each category is classified into dozens of types by status of the traffic signal, conflict situations. In order to present more various accident types for auto insurance accidents, the standards are reclassified driving direction and path of vehicles from crash situations. In results, the car-to-car accidents are classified into 33 accident types, car-to-pedestrian accidents have 19 accident types, car-to-motorcycle accidents have 38 accident types, and car-to-cyclist accidents are derived into 26 types.

Study on Effectiveness of Accident Reduction Depending on Autonomous Emergency Braking System (AEB 장치에 대한 사고경감 효과 연구)

  • Choi, JunYoung;Kang, SeungSu;Park, EunAh;Lee, KangWon;Lee, SiHun;Cho, SooKang;Kwon, YoungGil
    • Journal of Auto-vehicle Safety Association
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    • v.11 no.2
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    • pp.6-10
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    • 2019
  • This paper describes effectiveness of accident reduction on vehicles equipped with AEB using accident data occurring in Korea. During the statistical period, we used the number of vehicles which are covered by auto insurance and the number of accidents. To maximize the reduction effect of accidents caused by the driver's carelessness, the analysis was limited to Physical Damage Coverage that covers the cost of repairing or replacing the damaged vehicle caused by the driver's fault. Due to Personal Information Protection Law, it was not capable of comparing the same vehicle using Vehicle Identification Number in this study. Instead of that, we used it as a similar vehicle, so there are limits to the comparison and analysis results. As a result of this study, we have found that the effect of reducing accidents was different depending on the vehicle class, but it was generally concluded that the number of accidents decreased when the vehicle was equipped with an AEB system. Domestic research on the AEB effect of reducing accidents is not active yet. Therefore, it is absolutely essential to analyze the effects according to various conditions such as driver's age, occupation and gender as well as expanding the study models in the future.

Development of a Drowsiness Detection System using a Histogram for Vehicle Safety (자동차 안전을 위한 히스토그램 이용 졸음 감지 시스템 개발)

  • Kang, Su Min;Huh, Kyung Moo;Joo, Young-Bok
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.2
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    • pp.102-107
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    • 2015
  • In this paper, we propose a technique of drowsiness detection using a histogram for vehicle safety. The drowsiness of vehicle drivers is often the main cause of many vehicle accidents. Therefore, the checking of eye images in order to detect the drowsiness status of a driver is very important for preventing accidents. In our suggested method, we analyse the changes of a histogram of eye region images which are acquired using a CCD camera. We develop a drowsiness detection system using this histogram change information. The experimental results show that the proposed method enhances the accuracy of detecting drowsiness to nearly 97%, and can be used to prevent accidents due to driver drowsiness.

Severity Analysis for Vulnerable Pedestrian Accident Utilizing Vehicle Recorder Database of Taxi (택시 영상DB를 활용한 교통약자 보행자 사고의 심각도 분석)

  • Chung, JaeHoon;Sul, Jaehoon;Choi, SungTaek;Rho, JeongHyun;Lee, Jisun
    • Journal of the Korean Society of Safety
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    • v.29 no.3
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    • pp.98-106
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    • 2014
  • This study proposes severity analysis for pedestrian accidents by improving variables which were used for general severity analysis. The existing variables were collected based on the interviews with policeman or witnesses and evidence of accidents. Therefore, existing variables were subjective and had several measurement errors. In order to improve such problems, this study collected variables from vehicle recorder of taxi which recorded the moment of accidents. As a result, explanatory power of independent variables was enhanced and the complete objective variables could be collected. After collecting variables, ordered probit model was developed by utilizing vehicle recorder database. Fitness of ordered probit model was 0.23. Vehicle speed and pedestrian's eye direction variables were the most critical factors for severity of pedestrian accident. In addition, severity analysis for vulnerable pedestrian was carried out. As a result, it was revealed that vehicle speed, pedestrian's eye direction and safety zone variables affected the severity of pedestrian accidents most. Particularly, vehicle speed variable is the most important factor. Consequently, driver's defensive driving and compliance to the regulations are the priority to reduce severity of pedestrian accidents and prevent pedestrian accident.

Analysis for Traffic Accident of the Bus with Advanced Driver Assistance System (ADAS) (첨단안전장치 장착 버스의 사고사례 분석)

  • Park, Jongjin;Choi, Youngsoo;Park, Jeongman
    • Journal of Auto-vehicle Safety Association
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    • v.13 no.3
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    • pp.78-85
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    • 2021
  • Recently a traffic accident of heavy duty vehicles under the mandatory installation of ADAS (Advanced Driver Assistance System) is often reported in the media. Heavy duty vehicle accidents are normally occurring a high number of passenger's injury. According to report of Insurance Institute for Highway Safety, FCW (Forward Collision Warning) and AEB (Automatic Emergency Braking) were associated with a statistically significant 12% reduction in the rate of police-reportable crashes per vehicle miles traveled, and a significant 41% reduction in the rear-end crash rate of large trucks. Also many countries around the world, including Korea, are studying the effects of ADAS installation on accident reduction. Traffic accident statistics of passenger vehicle for business purpose in TMACS (Traffic safety information Management Complex System in Korea) tends to remarkably reduce the number of deaths due to the accident (2017(211), 2018(170), 2019(139)), but the number of traffic accidents (2017(8,939), 2018(9,181), 2019(10,095)) increases. In this paper, it is introduced a traffic accident case that could lead to high injury traffic accidents by being equipped with AEB in a bus. AEB reduces accidents and damage in general but malfunction of AEB could occur severe accident. Therefore, proper education is required to use AEB system, simply instead of focusing on developing and installing AEB to prevent traffic accidents. Traffic accident of AEB equipped vehicle may arise a new dispute between a driver's fault and vehicle defect. It is highly recommended to regulate an advanced event data recorder system.

A Study on the Installation of a Barrier to Prevent Large-Scale Traffic Accidents in Tunnel

  • Baek, Se-Ryong;Yoon, Jun-Kyu;Lim, Jong-Han
    • International journal of advanced smart convergence
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    • v.8 no.4
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    • pp.161-168
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    • 2019
  • Traffic accidents in tunnel can lead to large traffic accidents due to narrow and dark road characteristics. Therefore, special care of the driver is required when is driving in a tunnel. However, accidents can happen at any time. In the event of an accident, a narrow road structure may lead to a second accident. Therefore, all facilities installed inside the tunnel should be allowed to minimize damage in the event of an accident. We confirmed the safety of the collision target through the action of the sedan, Sport Utility Vehicle (SUV) and truck when the vehicle crashed into a stairway installed on the tunnel emergency escape route, and when a concrete barrier or guard rail was installed in front of the stairway. The behavior of the vehicle has resulted in a total of three results: rollover or rollover, change of speed and angle of the vehicle after collision. The sedan and SUV were the most secure when colliding with the guardrail, but considering the truck as a whole, concrete barriers were judged to be the most suitable for minimizing damage from the first accident and reducing the risk of the second accident.

Research on the Investigation of ΔV (Delta-V) for the Quality Improvement of Korean In-Depth Accident Study (KIDAS) Database (한국형 실사고 심층조사 데이터베이스 질향상을 위한 차량속도(ΔV) 측정방법에 관한 연구)

  • Choo, Yeon Il;Lee, Kang Hyun;Kong, Joon Seok;Lee, Hee Young;Jeon, Joon Ho;Park, Jong Jin;Kim, Sang Chul
    • Journal of Auto-vehicle Safety Association
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    • v.12 no.2
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    • pp.40-46
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    • 2020
  • Modern traffic accidents are a complex occurrence. Various indicators are needed to analyze traffic accidents. Countries that have been investigating traffic accidents for a long time accumulate various data to analyze traffic accidents. The Korean In-Depth Accident Study (KIDAS) database collected damaged vehicles and severity of injury caused by Collision Deformation Classification code (CDC code), Abbreviated Injury Scale (AIS), and Injury Severity Score (ISS). As a result of the investigation, data relating to the injuries of the occupants can be easily obtained, but it was difficult to analyze human severity based on the information of the damaged vehicle. This study suggests a method to measure the speed change at the time of an accident, which is one of the most important indicators in the vehicle crash database, to help advance KIDAS research.

Improvement on Accident Statistic Analysis and Response of Hazardous Chemical Transport Vehicle (유해화학물질 운송차량 사고 통계분석 및 사고대응 개선방안)

  • Jeon, Byeong-han;Kim, Hyun-sub
    • Journal of the Society of Disaster Information
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    • v.14 no.1
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    • pp.59-64
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    • 2018
  • In the trend of increasing awareness of chemical accidents, hazardous chemical transport vehicle accidents are occurring every year. In this study, we analyzed improvement of accident prevention and countermeasures through statistical analysis of hazardous chemical transport vehicle accidents. A total of 383 chemical accidents between January 2014 and December 2017 were analyzed. During this period, number of transportation accidents was 83 cases, accounting for 21.67% of total chemical accidents. In the current system, despite the direct handling of hazardous chemical, it is out of regulation of damage prediction unlike the workplace. In order to effectively respond to actual accident, information on damage prediction is required and should be shared with related ministry. And it should be developed to real-time monitoring of hazardous chemical transport vehicle through integrated control tower.

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.

Development of an Automobile Black Box for Reconstruction Analysis of Collision Accidents (충돌사고 재구성 해석을 위한 차량 블랙박스의 개발)

  • 이원희;한인환
    • Transactions of the Korean Society of Automotive Engineers
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    • v.12 no.2
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    • pp.205-214
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    • 2004
  • This paper presents design concepts, specifications and performances of a newly developed Black Box, the reconstruction analysis tool with the records, and results of validation tests. The Black Box can detect crash accidents automatically, and record the vehicle's motion and driver's maneuvers during a pre-defined time period before and after the accident. The items of the Black Box included the acceleration, yaw-rate, vehicle speed, engine RPM, braking application, steering and several digital inputs for recording driver's maneuvers. To detect the accident-related-crash, it is important to understand characteristics of the crash signal, which are much different from those of normal driving. Therefore, analytical considerations should be taken in designing pre-filtering circuits and selecting appropriate parameters for identifying crash accidents. And, it is necessary to select proper combination of motion sensors and design proper pre-filtering circuits in order to describe the vehicle's motion. The analysis algorithms were developed and implemented which can perform accurate detection of crash accidents, simulating pre-crash trajectories, and calculating parameters for reconstruction analysis of crash accidents. The developed Black Box was installed on passenger cars and several types of validation tests were conducted. Through the tests, the accuracy of the recorded data and usefulness of the analysis tool for reconstruction have been validated.