• 자동차안전학회지
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• 제13권4호
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• pp.106-113
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• 2021

In this study, The behavior of an autonomous vehicle in an intersection accident situation is predicted. Based on a representative intersection accident situation from actual intersection accident database, simulation was performed by applying the automatic emergency braking algorithm used in the autonomous driving system. Accident reconstruction was performed based on the accident report of the representative accident situation. After applying the autonomous driving system to the accident-related vehicle, the tendency of intersection accidents that may occur in autonomous vehicles was identified and analyzed.

• 자동차안전학회지
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• 제15권1호
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• pp.35-44
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• 2023

The purpose of this study is to predict how the actual accident changes by reconstructing the accident with an Autonomous Emergency Braking system (AEB) based on the actual accident of the LTAP-OD (Left Turn Crossing Path - Opponent Direction) intersection. A virtual AEB sensor was developed, and 150 head-on collision accident reports were secured to the insurance company to reconstruct the accident. As a result of the accident type analysis, a total of 13 types of head-on collision accidents were derived, and it is the LTAP-OD intersection accident with the highest frequency. In the LTAP-OD intersection accident, the simulation was conducted by applying the virtual AEB of each vehicle, the accident rate decreased by 90% or more when the AEB of the left-turn vehicle was applied, and the accident rate decreased by 50%. In addition, the most frequent collision types in LTAP-OD accidents were the front bumper on the driver's side of a vehicle going straight and the front bumper on the passenger's side of a vehicle turning left.

• 한국안전학회지
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• 제32권5호
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• pp.129-134
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• 2017

This study aims to develop the traffic accident models by circular intersection type using count data model. The number of accident, the number of fatal and injured persons(FSI), and EPDO are calculated from the traffic accident data of TAAS. The circular intersection accident models are developed through Poisson and negative binomial regression analysis. The main results of this study are as follows. First, the null hypotheses that there are differences in the number of traffic accidents, FSI and EPDO by type of circular intersections are rejected. Second, the scale of intersection(median, large), number of approach road, mean width and length of exit road, area of the circulating roadway and central island are selected as factors influencing the number of traffic accidents, FSI and EPDO in rotary. Third, the scale of intersection(median), guide signs(limited speed, direction, roundabout), number of approach road, entry angle, area of the intersection and central island are adopted as factors influencing the number of traffic accidents, FSI and EPDO in roundabout. Finally, transferring from rotary to roundabout could be expected to make the accident decrease.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.437-439
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• 2006

Actually, The present traffic accident detection system is subsisting limitation of accurate distinction under the crowded condition at intersection because the system defend upon mainly the image information at intersection and digital image processing techniques nearly all. To complement this insufficiency, this article aims to estimate the level of present technology and a realistic possibility by analyzing the acoustic characteristic of crash sound that we have to investigate for improvement of traffic accident detection rate at intersection. The skid sound of traffic accident is showed the special pattern at 1[kHz])${\sim}$3[kHz] bandwidth when vehicles are almost never operated in and around intersection. Also, the frequency bandwidth of vehicle crash sound is showed sound pressure difference oyer 30[dB] higher than when there is no occurrence of traffic accident below 500[Hz].

• 한국산학기술학회논문지
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• 제7권6호
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• pp.1142-1148
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• 2006

실제적으로, 현재의 교통사고 검지시스템은 주로 교차로에서의 영상정보와 디지털 영상처리기술에만 거의 의존하고 있기 때문에 교차로에서의 혼잡한 상황하에서는 정확한 판별의 제한이 잔존하고 있다. 이러한 문제점을 보완하기 위하여, 본 논문은 교차로에서의 교통사고 자동검지율의 향상을 위해 검토되어야 할 사고음의 음향특성을 분석함으로써 현재 기술수준과 실현가능성을 가늠해 보는 것을 목적으로 한다. 교차로 주변에 차량의 소통이 거의 없을 때는 자동차사고 스키드음은 1[KHz]$\sim$3[KHz] 대역에서 특정패턴을 보였다. 또한, 차량 충돌음의 주파수 대역은 500[Hz]이하에서 사고가 발생하지 않은 시점보다 높은 30[dB] 이상의 음압차이를 보였다.

• 제어로봇시스템학회논문지
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• 제10권6호
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• pp.501-509
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• 2004

The frequency of car accidents is very high at the intersection. Because of the state of a traffic signal, quarrels happen after accidents. At night many cars run away after causing an accident. In this case, accident analyses have been conducted by investigating evidences such as eyewitness accounts, tire tracks, fragments of the car or collision traces of the car. But these evidences that don't have enough objectivity cause an error in judgment. In the paper, when traffic accidents happen, the traffic accident detection system that stands on the basis of images and sounds detects traffic accidents to acquire abundant evidences. And, this system transmits 10 seconds images to the traffic center through the wired net and stores images to the Smart Media Card. This can be applied to various ways such as accident management, accident DB construction, urgent rescue after awaring the accident, accident detection in tunnel and in inclement weather.

• 한국안전학회지
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• 제32권3호
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• pp.123-129
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• 2017

This study deals with the traffic accident of truck at circular intersection. The purpose of this study is to develop the truck accident models based on type of accident and conflict. In pursuing the above, the study gives particular attentions to selecting the appropriate models among Poisson and Negative binomial models using statistical program LIMDEP 8.0. The traffic accident data from 2007 to 2014 are collected from TAAS data set of Road Traffic Authority. Such the dependent variable as number of truck accidents and the 24 independent variables as geometry, traffic volume and others are used. The main results are as follows. First, 5 Poisson models (${\rho}^2$ of 0.164~0.351) which are all statistically significant are selected. Second, the common variable based on type of accident and conflict is analyzed to be truck apron width. The specific variables are, however, evaluated to splitter island, area of splitter island, speed limit sign, truck apron, number approach road, circular intersection sign, speed hump and traffic volume. Finally, widening the truck apron width and improving the above specific variables are analyzed to be important for truck accident reduction at circular intersections.

• 한국전자통신학회논문지
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• 제11권8호
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• pp.783-792
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• 2016

본 논문은 교차로 영상기록장치 시스템으로서 교차로 구간 영상과 신호등 현시 영상을 수집하여 하나의 영상정보로 통합한 후 중앙센터로 전송하는 시스템이다. 시스템은 교차로 영상과 신호등 현시 영상을 획득하는 영상 획득 과정과 획득한 두 영상을 단일의 영상으로 통합하는 과정을 거쳐 중앙센터로 전송하고 기록하도록 구성되어 있다. 이 시스템을 활용하여 사고 발생시 유고정보를 신속히 전파하여 2차 사고를 예방하고 사고의 원인을 판단하는데 소요되는 시간과 분쟁을 줄일 수 있을 것으로 기대된다.

• 한국전자통신학회논문지
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• 제12권6호
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• pp.1189-1196
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• 2017

본 연구의 목적은 교차로 신호등 영상과 신호현시 영상을 하나의 영상정보로 통합 하여 중앙센터로 전송하는 방식이다. 시스템은 교차로 영상과 신호현시 영상을 수집하여 하나의 영상으로 통합하여 중앙센터에 전송 저장한다. 이 시스템은 사고발생시 사고정보를 즉시 전파하고 사고 원인을 규명하고 분쟁을 해결하는데 소요되는 시간을 줄임으로써 2차 사고를 예방하는데 효과적 일 것으로 예상된다.

• 한국안전학회지
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• 제29권5호
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• pp.154-159
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• 2014

This study deals with the pedestrian accidents of intersections in case of Cheongju. The objective is to develop the pedestrian accident models using Tobit regression model. In pursuing the above, the pedestrian accident data from 2007 to 2011 were collected from TAAS data set of Road Traffic Authority. To analyze the accident, Poisson, negative binomial and Tobit regression models were utilized in this study. The dependent variable were the number of accident by intersection. Independent variables are traffic volume, intersection geometric structure and the transportation facility. The main results were as follows. First, Tobit model was judged to be more appropriate model than other models. Also, these models were analyzed to be statistically significant. Second, such the main variables related to accidents as traffic volume, pedestrian volume, number of traffic island, crossing length and the pedestrian countdown signal systems were adopted in the above model.