• Title/Summary/Keyword: 교통사고 판별

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Drowsy driving and seat belt detection using multiple deep learning networks (딥러닝 다중 네트워크를 이용한 졸음 운전감지 및 안전벨트 착용 여부 확인)

  • Rhyou, SeYeol;Yoo, JaeChern
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2021.01a
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    • pp.75-77
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    • 2021
  • 다양한 원인으로 매년 수많은 사람이 교통사고로 목숨을 잃거나 크게 다치곤 한다. 최근 교통사고 통계자료에 따르면 졸음운전으로 인한 교통사고가 음주운전이나, 과속보다도 높은 비중을 차지하고 있었다. 또한, 사고가 났을 때 안전벨트를 매지 않은 운전자나 동승객은 부상 정도가 훨씬 심각한 것으로 알려져 전 좌석에 안전벨트를 꼭 착용해야 하는 법도 제정되었다. 그런데도 많은 운전자 및 동승자가 안전벨트를 착용하지 않아 크게 부상을 당하는 사고는 줄지 않고 있다. 이러한 사고와 부상을 줄이기 위하여 본 논문에서는 다중 네트워크를 이용하여 운전자의 졸음 감지 및 운전자, 동승자의 안전벨트 착용 여부까지 실시간으로 판별하는 시스템을 설계하고 구현한다.

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Study on Incident Detection Algorithm using Neuro-Fuzzy Inference System (Neuro-Fuzzy 추론 시스템을 이용한 유고검지 알고리즘 연구)

  • Hong, Nam-Kwan;Choi, Jin-Woo;Lee, Seung-Heon;Yang, Young-Kyu
    • 한국HCI학회:학술대회논문집
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    • 2006.02a
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    • pp.1234-1239
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    • 2006
  • 신속하고 정확한 교통정보 서비스의 제공은 원활한 교통소통을 위하여 필수적인 요소이다. 특히, 교통사고, 도로보수 그리고 자연재해와 같은 유고가 발생할 경우, 운전자에게 즉시 통보해주어 우회할 수 있도록 조치하는 것이 필요하다. 이를 위하여 다양한 교통정보 수집기에서 수집된 교통정보를 바탕으로 실시간으로 유고상황을 판별하는 연구가 많이 진행되고 있다. 유고상황 분석은 다양한 환경요인으로 인해 판별이 어렵고, 최근에 활용되고 있는 인공지능 기법은 검지에 드는 시간 비용이 많다는 문제를 가지고 있다. 본 연구에서는 과거에 발생한 각종 돌발 상황을 분석하여 실시간으로 유고상황을 검지하는 것이 목적이다. 유고검지를 위해 GPS를 탑재한 probe car에서 수집된 차량속도와 온라인으로 제보된 유고정보를 ANFIS를 이용하여 분석 후 유고상태를 판별한다. 본 연구를 통해 실시간 도로 이용자들이 유고 발생 지역의 정보를 제공받고 그 상황에 신속하게 대처하게 함으로써 교통 혼잡 완화에 기여할 것으로 기대한다.

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Comparative Analysis of Elderly's and Non-elderly's Human Traffic Accident Severity (고령운전자와 비고령운전자의 인적교통사고 심각도 비교분석)

  • Lee, Sang Hyuk;Jeung, Woo Dong;Woo, Yong Han
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.11 no.6
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    • pp.133-144
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    • 2012
  • This study focused on estimating influential factors of traffic accidents and analyzing traffic accident severity of elderly and non elderly using traffic accident data. In order to reclassify elderly and non elderly traffic accident by a statistical method from entire traffic accident data, multiple discriminant analysis was applied. Also ordered logit model was applied for analyzing traffic accident severities using traffic accident severities as an independent variable and transportation facilities, road conditions and human characteristics as dependent variables. As results of the comparison between elderly and non elderly traffic accident, the traffic accident severity was affected by the age, types of traffic accidents, human characteristics and road conditions as well. Also, transportation facilities and road conditions affected to more elderly traffic accident than non elderly. Therefore, traffic accident severity would be decreased with the improvement of transportation facilities and road conditions for the elderly.

Acoustic Characteristic Analysis of the accident for Automatic Traffic Accident Detection at Intersection (교차로 교통사고 자동감지를 위한 사고음의 음향특성 분석)

  • Park, Mun-Soo;Kim, Jae-Yee
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.7 no.6
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    • pp.1142-1148
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    • 2006
  • Actually, a present traffic accident detection system is subsisting limitation of accurate distinction under the crowded condition at intersection because the system depend 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 fur improvement of traffic accident detection rate at intersection. The skid sound of traffic accident was 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 was showed sound pressure difference over 30[dB] higher than when there is no occurrence of traffic accident below 500[Hz].

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A Study on the Driver's License Renewal and Return Policy through the Recognition of the Elderly's Driving Pattern (고령자의 운전패턴 인식을 통한 운전면허증 갱신 및 반납 정책에 대한 연구)

  • Cho, Myeon-gyun
    • Journal of Digital Convergence
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    • v.16 no.10
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    • pp.213-222
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    • 2018
  • This study was conducted to derive the traffic accident risk index through the recognition of the elderly driver's driving pattern to reduce the traffic accident rate of elderly drivers and to reflect them in the renewal and return policy of driver's license accordingly. First, the traffic accident risk index is defined by analyzing the behavioral characteristics of older drivers to derive the major factors that lead to traffic accidents. Second, we present a method to measure the traffic accident risk index from the driving pattern of the elderly through the smart-phone, the camera and the distance sensor attached to the car. Finally, we derive three thresholds by computer simulation and determine the accident risk from the measured traffic accident risk index as four steps and suggest ways to ensure safe driving of older drivers. It is required to objectively assess the driving ability of an aged driver in accordance with the proposed method, and to induce the driver to reset the driver's license renewal cycle and voluntarily return the driver's license to minimize social costs due to increased traffic accidents.

지역교차로 교통사고 자동검지시스템 개선을 위한 교차로 제 음향특성의 해석

  • Cho, Eul-Soo;Go, Young-Gwon;Kim, Jae-Yee
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2008.05a
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    • pp.789-792
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    • 2008
  • Actually, The present traffic accident detection system is subsisting limitation of accurate distinction under the crowded condition at intersection because the system depend 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 over 30[dB] higher than when there is no occurrence of traffic accident below 500[Hz].

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Development of Computation Model for Traffic Accidents Risk Index - Focusing on Intersection in Chuncheon City - (교통사고 위험도 지수 산정 모델 개발 - 춘천시 교차로를 중심으로 -)

  • Shim, Kywan-Bho;Hwang, Kyung-Soo
    • International Journal of Highway Engineering
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    • v.11 no.3
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    • pp.61-74
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    • 2009
  • Traffic accident risk index Computation model's development apply traffic level of significance about area of road user group, road and street network area, population group etc.. through numerical formula or model by countermeasure to reduce the occurrence rate of traffic accidents. Is real condition that is taking advantage of risk by tangent section through estimation model and by method to choose improvement way to intersection from outside the country, and is utilizing being applied in part business in domestic. However, question is brought in the accuracy being utilizing changing some to take external model in domestic real condition than individual development of model. Therefore, selection intersection estimation element through traffic accidents occurrence present condition, geometry structure, control way, traffic volume, turning traffic volume etc. in 96 intersections in this research, and select final variable through correlation analysis of abstracted estimation elements. Developed intersection design model taking advantage of signal type, numeric of lane, intersection type, analysis of variance techniques through ANOVA analysis of three variables of intersection form with selected variable lastly, in signal crossing through three class intersection, distinction variable choice risk in model, no-signal crossing risk distinction analysis model and so on develop.

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A Study on Near-miss Incidents from Maritime Traffic Flow by Clustering Vessel Positions (선박위치 클러스터링을 활용한 해상교통 근접사고 산출에 관한 연구)

  • Kim, Kwang-Il;Jeong, Jung Sik;Park, Gyei-Kark
    • Journal of the Korean Institute of Intelligent Systems
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    • v.24 no.6
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    • pp.603-608
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    • 2014
  • In the maritime traffic environment, the near-miss between vessels is the situation approaching on collision course but collision accident is not occurred. In this study, in order to calculate the near-miss between navigating vessels, the discriminating equation using ship bumper theory and vessel position clustering methods are proposed. Applying proposed module to the vessel trajectories of the WANDO waterway, we assessment navigational risk factors of vessel type, navigational speed, meeting situation.

A Study about Establishment of Discrimination Model of Impact Factors of Big Traffic Accident -With Laws Violation Type- (대형교통사고 영향요인의 판별모델 구축에 관한 연구 -법규위반 유형을 중심으로-)

  • 오윤표;고상선
    • Journal of Korean Society of Transportation
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    • v.10 no.3
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    • pp.59-74
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    • 1992
  • The change of industrial structure, the expansion of economic scale, the elevation of national life level and rapid motorization bring about social problems that are traffic accident, traffic congestion, etc. Especially, big traffic accidents bring about the great number of dead and wounded person with damage of property. But there are no study results available mainly focused on the big traffic accident analysis. Accordingly, this study is essentially for the factor analysis of big accident types including laws violation and the assaulting driver's death using Quantification ll method.

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Proposal of a Black Ice Detection Method Using Infrared Camera and YOLO for Reducing of Traffic Accidents (교통사고 경감을 위한 적외선 카메라와 YOLO를 사용한 블랙아이스 탐지 방법 제안)

  • Kim, Hyunggyun;Jang, Minseok;Lee, Yonsik
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.416-421
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    • 2021
  • In case of the road slips due to heavy snow and the temperature drops below 0 degrees, black ice which mainly occurs on the road, bridges for vehicles, and tunnel entrances, is not recognized by the driver's view because the image of the asphalt is transmitted through it. So cars' slip situation occurs, which leads to a big traffic accident and a large amount of loss of life and property. This study proposes a method to check the road condition using an infrared camera and to identify black ice through deep learning.

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