• 제목/요약/키워드: Traffic Camera

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Measures to Reduce Traffic Accidents in School Zones using Artificial Intelligence

  • Park, Moon-Soo;Park, Dea-woo
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2022년도 춘계학술대회
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    • pp.162-164
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    • 2022
  • Efforts are being made to prevent traffic accidents within the child protection zone. Efforts are being made to prevent accidents by enacting safety facilities and laws to prevent traffic accidents in the school zone. However, traffic accidents in school zones continue to occur. If the driver can know the situation in the child protection zone in advance, accidents can be reduced. In this paper, we design a camera that eliminates blind spots in school zones and a number recognition camera system that can collect pre-traffic information. Design a LIDAR system that recognizes vehicle speed and pedestrians. Design an LED guidance system that delivers information to drivers without smart devices. We study time series analysis and artificial intelligence algorithms that collect and process pedestrian and vehicle information recognized by cameras and LIDAR. In the artificial intelligence traffic accident prevention system learned by deep learning, before entering the school zone, the school zone information is sent to the driver through the Force Push Service and the school zone information is delivered to the driver on the LED sign. try to reduce accidents.

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영상검지 카메라를 이용한 도로상의 차량흐름 계측방안 연구 (The Development of Camera Detection System for the Measurement Road Traffic Data)

  • 김희식;김진만
    • 한국안전학회지
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    • 제18권4호
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    • pp.23-27
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    • 2003
  • To improve the road transportation safety, the road traffic data is monitored by applying an image detection system. The road traffic safety is analysed using image processing techniques. For more accurate measurement, the coordinate matching of real road data to image is one of the most essential parts of the image detection technique. The road image is skewed at the input screen, because the video camera is installed at the roadside. A fast and precise algorithm for the coordinate matching is developed to convert image coordinates into road coordinates.

경적음의 도플러 효과를 이용한 교통사고분석 (Traffic Accident Analysis using Doppler Effect of the Horn)

  • 최영수;김종혁;윤용문;박종찬;박하선
    • 자동차안전학회지
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    • 제12권4호
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    • pp.70-77
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    • 2020
  • In this study, we estimate the vehicle speed by analyzing the acoustic data recorded in a single microphone of a surveillance camera. The frequency analysis of the acoustic data corrects the Doppler effect, which is a characteristic of the moving sound source, and reflects the geometric relationship according to the location of the sound source and the microphone on the two-dimensional plane. The acoustic data is selected from the horn sound that is mainly observed in an urgent situation among various sound sources that may occur in a traffic accident, and the characteristics of the monotone source are considered. We verified the reliability of the proposed method by time domain acoustic analysis and actual vehicle evaluation. This method is effective and can be used for traffic accident analysis in the blind spot of the camera using a single microphone built into the existing surveillance camera.

차량 블랙박스 카메라를 이용한 도시부 교통상태 추정 (Estimation of Urban Traffic State Using Black Box Camera)

  • 조해찬;윤여환;여화수
    • 한국ITS학회 논문지
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    • 제22권2호
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    • pp.133-146
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    • 2023
  • 도심지역의 교통 상태는 효과적인 교통 운영과 교통 제어를 수행하는 데 필수 요소이다. 하지만 교통 상태를 얻기 위해서 수많은 도로 구간에 교통 센서를 설치하는 것은 막대한 비용이 든다. 이를 해결하기 위해서 시장침투율이 높은 센서인 차량 블랙박스 카메라를 이용하여 교통 상태를 추정하는 것이 효과적이다. 하지만 기존의 방법론은 객체 추적 알고리즘이나 광학 흐름과 같이 계산 복잡도가 높고, 연속된 프레임이 있어야 연산을 수행할 수 있다는 단점이 존재한다. 이에 본 연구에서는 심층학습 모델로 차량과 차선을 탐지하고, 차선 사이의 공간을 관심 영역으로 설정하여 해당 영역의 교통밀도를 추정하는 방법을 제안하였다. 이 방법론은 객체 탐지 모델만을 이용해서 연산량이 적고, 연속된 프레임이 아닌 샘플링된 프레임에 대해 교통 상태를 추정할 수 있다는 장점이 있기에, 보유하고 있는 컴퓨팅 자원에 맞는 교통 상태 추정이 가능하다. 또, 도심지역에서 운행하는 서로 다른 특성의 2개의 버스 노선에서 수집한 블랙박스 영상을 검증한 결과, 교통밀도 추정 정확도가 90% 이상인 것을 확인하였다.

교통 정체 예방을 위한 자동 신호등 제어시스템 개발 (Development of Auto Traffic Light Control System for Prevention of Traffic Jam)

  • 백광무;신지환;박무훈
    • 융합신호처리학회논문지
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    • 제15권4호
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    • pp.148-154
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    • 2014
  • 본 논문에서는 교차로에 설치된 한 대의 카메라를 활용하여 각 도로로 유입, 유출 되는 교통량을 동시에 측정할 수 있도록 하였으며 그 데이터를 기반으로 영상처리를 통해 신호등을 자동으로 제어하는 새로운 시스템을 제안한다. 또한 왕복 8차선 교차로의 교통량을 한 대의 카메라로 모니터링 가능하게 하여 차선 1개당 1대의 카메라 또는 루프 코일을 사용하던 기존 방식보다 효율적으로 광범위한 교통량 흐름을 통계적으로 모니터링 할 수 있도록 고안하였다. 실시간으로 배경영상이 업데이트되므로 불규칙적인 조건을 갖는 실 상황에서도 자동차 객체가 효율적으로 검지되도록 하였으며 관심영역 설정으로 보다 정확도 높은 교통량 측정을 가능하게 하였다. 본 논문에서 제안한 신호등 자동제어 알고리즘을 이용하여 정체가 일어나기 전에 각 도로간 교통량을 조절함으로써 교통 정체로 발생하는 운전자의 시간 낭비 및 에너지 낭비를 예방할 수 있다.

웹 카메라 시스템의 구현과 트래픽 측정에 관한 연구 (A Study on the Implementation of Web-Camera System and the Measurement of Traffic)

  • 안영민;진현준;박노경
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2001년도 봄 학술발표논문집 Vol.28 No.1 (A)
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    • pp.187-189
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    • 2001
  • In this study, the Web Camera System is implementation and simulated on two different architectures. In the one architecture, a Web-server and Camera-server are implemented on the same system, and the system transfers motion picture which compressed to JPEG file to users on the WWW(World Wide Web). In the other architecture, the Web-server and Camera-server are implemented on different systems, and the motion picture is transferred from the Camera-server to Web-server, and finally to users. In order to compare system performance between two architecture, data traffic is measured and simulated in the unit of byte per second and frame per second.

딥러닝 데이터 활용한 신호등 색 인식 알고리즘 개발 (Development of Color Recognition Algorithm for Traffic Lights using Deep Learning Data)

  • 백서하;김종호;이경수
    • 자동차안전학회지
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    • 제14권2호
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    • pp.45-50
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    • 2022
  • The vehicle motion in urban environment is determined by surrounding traffic flow, which cause understanding the flow to be a factor that dominantly affects the motion planning of the vehicle. The traffic flow in this urban environment is accessed using various urban infrastructure information. This paper represents a color recognition algorithm for traffic lights to perceive traffic condition which is a main information among various urban infrastructure information. Deep learning based vision open source realizes positions of traffic lights around the host vehicle. The data are processed to input data based on whether it exists on the route of ego vehicle. The colors of traffic lights are estimated through pixel values from the camera image. The proposed algorithm is validated in intersection situations with traffic lights on the test track. The results show that the proposed algorithm guarantees precise recognition on traffic lights associated with the ego vehicle path in urban intersection scenarios.

Traffic Safety Recommendation Using Combined Accident and Speeding Data

  • Onuean, Athita;Lee, Daesung;Jung, Hanmin
    • Journal of information and communication convergence engineering
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    • 제18권1호
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    • pp.49-54
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    • 2020
  • Speed enforcement is one of the major challenges in traffic safety. The increasing number of accidents and fatalities has led governments to respond by implementing an intelligent control system. For example, the Korean government implemented a speed camera system for maintaining road safety. However, many drivers still engage in speeding behavior in blackspot areas where speed cameras are not provided. Therefore, we propose a methodology to analyze the combined accident and speeding data to offer recommendations to maintain traffic safety. We investigate three factors: "section," "existing speed camera location," and "over speeding data." To interpret the results, we used the QGIS tool for visualizing the spatial distribution of the incidents. Finally, we provide four recommendations based on the three aforementioned factors: "investigate with experts," "no action," "install fixed speed cameras," and "deploy mobile speed cameras."

야간 영상에서의 빛 번짐 현상을 이용한 교통신호등 인식 (Traffic Light Recognition Based on the Glow Effect at Night Image)

  • 김민기
    • 한국멀티미디어학회논문지
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    • 제20권12호
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    • pp.1901-1912
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    • 2017
  • Traffic lights at night are usually framed in the image as bright regions bigger than the real size due to glow effect. Moreover, the colors of lighting region saturate to white. So it is difficult to distinguish between different traffic lights at night. Many related studies have tried to decrease the glow effect in the process of capturing images. Some studies drastically decreased the shutter time of the camera to reduce the adverse effect by the glow. However, this makes the video too dark. This study proposes a new idea which utilizes the glow effect. It examines the outer radial region of traffic light. It presents an algorithm to discriminate the color of traffic light by the analysis of the outer radial region. The advantage of the proposed method is that it can recognize traffic lights in the image captured by an ordinary black box camera. Experimental results using seven short videos show the performance of traffic light recognition reporting the precision of 96.4% and the recall of 98.2%. These results show that the proposed method is valid and effective.

고속도로변 폐쇄회로 카메라 영상에서 트래킹에 의한 교통정보수집 알고리즘 (An Algorithm for Collecting Traffic Information by Vehicle Tracking Method from CCTV Camera Images on the Highway)

  • 이인정;민준영;장영상
    • Journal of Information Technology Applications and Management
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    • 제11권4호
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    • pp.169-179
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    • 2004
  • There are many inductive loop detectors under the highways in Korea. Among the other detectors, some are image detectors. Almost all image detectors are focused one or two lane of the road and are measuring traffic information. This paper proposes to an algorithm for detecting traffic information automatically from CCTV camera images installed on the highway. The information which is counted in one lane or two contains some critical errors by occlusion frequently in case of passing larger vehicles. In this paper, we use a tracking algorithm in which the detection area include all lanes, then the traffic informations are collected from the vehicles individually using difference images in this detection area. This tracking algorithm is better than lane by lane detecting algorithm. The experiment have been conducted two different real road scenes for 20 minutes. For the experiments, the images are provided with CCTV camera which was installed at Kiheung Interchange upstream of Kyongbu highway, and video recording images at Chungkye Tunnel. For image processing, images captured by frame-grabber board 30 frames per second, 640${\times}$480 pixels resolution and 256 gray-levels to reduce the total amount of data to be Interpreted.

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