• Title/Summary/Keyword: 차량검지시스템

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교차로 사고음 검지시스템의 방해음향 조사연구

  • Kang, Hee-Koo;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.805-808
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    • 2008
  • In this paper, it was performed the analysis on various intersection acoustic patterns for detection rate improvement of accident sound detection system : an acoustic pattern analysis on general traffic noise, an acoustic pattern analysis on engine noise, an acoustic pattern analysis on obstruct factors for accident sound detection system. There are remarkable differences between the acoustic patterns of traffic noise and accident sound, and we most consider the acoustic patterns when we compose the accident traffic detection system by acoustic because there is error range of 20[dB] according to the volume of traffic in intersection.

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A Study on the Performance Improvement for Automated Accident Detection System (지능형 교통시스템 성능개선에 관한 연구)

  • Choi, Ho-Jin;Kim, Jin-Suk
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2010.07a
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    • pp.137-140
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    • 2010
  • 교통사고의 발생은 교통 혼잡의 주요 원인으로 작용되어 교통사고에 의한 직 간접적 손해비용까지 지출되고 있다. 따라서 교통사고를 사전에 예방하거나 사고가 발생한 후 신속하게 처리할 수 있는 실시간 교통사고 대처 시스템이 요구되고 있다. 즉, 교통사고 자동검지 시스템의 필요성은 가 피해자의 구분에 활용하는 것 이외에 신속한 인명구조와 사고처리 등의 교차로 유고관리가 가능하며, 교통사고로 발생할 수 있는 교통 혼잡을 최소화 할 수 있다. 본 논문에서는 다양한 형태의 충돌 및 추돌 사고를 검지하는 시스템의 성능을 개선하기 위한 것으로 영상 또는 소리라는 매체에 기반을 둔 시스템에서 자동 검지의 한계성을 도출하고 개선하고자 하였다. 테스트 베드를 기반으로 자동검지 실패의 원인을 분석하고 그 원인에 따른 오인식의 문제점을 개선하여 운전자 단독사고로 인하여 차량 추적이 불가능한 경우, 소리 없이 발생한 사고, 야간에 발생한 사고 등의 문제점들을 극복함과 동시에 성능을 개선하는데 그 목적이 있다.

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A Study on Extracting Traffic Information Using Spatio-Temporal Image Analysis (시공간 영상분석에 의한 교통정보 산출기법에 관한 연구)

  • 이대호;박영태
    • Proceedings of the IEEK Conference
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    • 1999.06a
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    • pp.635-638
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    • 1999
  • 도로 위에 설치된 카메라에서 검지 영역의 데이터를 입력받아 통과 차량수, 도로 점유율, 차량속도, 차간 거리 등의 교통정보를 실시간으로 산출하는 기법은 지능형 교통정보 시스템(ITS)의 핵심 분야이다. 본 논문에서는 검지영역의 시공간 영상 분석에 의해 다양한 기상 조건과 그림자 등의 환경의 변화에 민감하지 않은 교통정보 산출기법을 제안한다.

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A Study on the Possibility of Using the Aerial-Based Vehicle Detection System for Real-Time Traffic Data Collection (항공 기반 차량검지시스템의 실시간 교통자료 수집에의 활용 가능성에 관한 연구)

  • Baik, Nam Cheol;Lee, Sang Hyup
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.32 no.2D
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    • pp.129-136
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    • 2012
  • In the US, Japan and Germany the Aerial-Based Vehicle Detection System, which collects real-time traffic data using the Unmanned Aerial Vehicle (UAV), helicopters or fixed-wing aircraft has been developed for the last several years. Therefore, this study was done to find out whether the Aerial-Based Vehicle Detection System could be used for real-time traffic data collection. For this purpose the study was divided into two parts. In the first part the possibility of retrieving real-time traffic data such as travel speed from the aerial photographic image using the image processing technique was examined. In the second part the quality of the retrieved real-time traffic data was examined to find out whether the data are good enough to be used as traffic information source. Based on the results of examinations we could conclude that it would not be easy for the Aerial- Based Vehicle Detection System to replace the present Vehicle Detection System due to technological difficulties and high cost. However, the system could be effectively used to make the emergency traffic management plan in case of incidents such as abrupt heavy rain, heavy snow, multiple pile-up, etc.

Development of Vehicle Detection System by Using Motion Vector of Corner Point (특징점의 모션벡터를 이용한 차량 검지 시스템 개발)

  • Han, Sang-Hoon
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.1 s.45
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    • pp.261-267
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    • 2007
  • The research about Intelligence Transport Systems(ITS) is actively studied for the traffic problem solution recently. Also, the various methods to detect vehicles moving in the roads are studied. This research using image processing technology is to give the drivers the road information quickly by developing Vehicle Detection System that detects through traffics. Purpose or this research is developing efficient algorithm to facilitate hardware composition. We use morphology method to extract corner points in the images captured by CCD camera. Also, the proposed algorithm detects vehicle's moving area by using motion vectors between corner points. The experiments of the proposed algorithm whose processing time was shortened show good results in vehicle detection on the live road images.

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Design of a Vehicle Detector for Transport Information System (교통 정보 시스템을 위한 차량 검지기 설계)

  • Kang, Kyung-Hoon;Jung, Sung-Tae;Lee, Sang-Seol;Kum, Ki-Jung;Nam, Kung-Moon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2001.04b
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    • pp.855-858
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    • 2001
  • 본 논문에서는 교통 정보 제공 시스템에서 기본적으로 필요로 하는 신뢰성 있는 교통데이터 획득을 위한 교통 영상검지기를 ASIC을 이용하여 효과적으로 구현할 수 있는 구조를 제안한다. 본 논문의 교통 영상검지기에서는 먼저 저가의 CMOS 이미지 센서를 이용하여 영상을 획득한다. 그 다음에 영상을 여러 개의 블록으로 분할하고 블록 매칭 기법을 이용하여 각 블록의 모션 벡터, 즉 각 블록이 다음 프레임에서 어느 방향으로 얼마만큼의 거리를 이동했는지를 추적한다. 그 다음에는 블록들의 모션 벡터로부터 자동차의 속도와 크기를 추출한다. 본 논문의 교통 검지기는 실시간으로 시내 도로나 고속도로에서 실시간으로 교통 정보를 검지할 수 있을 뿐만 아니라 보정이 필요 없어 설치가 매우 간편하다.

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Regional Traffic Information Acquisition by Non-intrusive Automatic Vehicle Identification (비매설식 자동차량인식장치를 이용한 구간교통정보 산출 방법 연구)

  • Kang Jin-Kee;Son Youngtae;Yoon Yeo-Hwan;Byun Sangchul
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.1 no.1
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    • pp.22-32
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    • 2002
  • This paper describes about non-burial AVI (Automatic Vehicle Identification) system using general vehicle as probe car for obtaining more accurate traffic information while conserving road pavement surface. Existing spot traffic detectors have their own limits of not obtaining right information owing to its mathematical method. Burial AVI systems have some defects, causing traffic jam, needing much maintenance cost because of frequent cutting of loop and piezo-electric sensors. Especially, they have hard time to make right detection, when it comes to jamming time. Therefore, in this paper, we propose non-burial AVI system with laser trigger unit. Proposed non-burial AVI system is developed to obtain regional traffic information from normal Passing vehicle by automatic license number recognition technology. We have adapted it to national highway section between Suwon city and Pyong$\~$Taek city(9.5km) and get affirmative results. Vehicle detection rate of laser trigger unit is more than 95$\%$, vehicle recognition rate is 87.8$\%$ and vehicle matching rate is about 14.3$\%$. So we regard these as satisfying results to use the system for traffic information service. We evaluate proposed AVI system by regulation of some institutions which are using similar AVI system and the proposed system satisfies all conditions. For future study, we have plan of detailed research about proper lane number from all of the target lanes, optimal section length, information service period, and data fusion method for existing spot detector.

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Efficient Video Image Processings for Real-Time Traffic Infomation Collection (실시간 교통정보 수집을 위한 효율적인 비디오 영상 처리)

  • Kim, Eui-Chul;Na, In-Seop;Kim, Soo-Hyung;Lim, Kyoung-Tea
    • Proceedings of the Korea Information Processing Society Conference
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    • 2007.11a
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    • pp.47-49
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    • 2007
  • 교통정보수집 시스템이란 CCTV나 웹캠을 통해 얻어진 영상을 토대로 차선별, 혹은 주행방향별 교통량과 통과 차량들의 속도를 실시간으로 측정하는 시스템이다. 차선별로 각각 두 개의 라인을 설정하고 이를 이용하여 차선별 속도와 교통량을 측정한다. 이 때 차선별로 설정된 두 라인에 해당하는 영역에 대해서 배경 값을 지속적으로 갱신한다. CCTV와 웹캠을 이용하여 수집한 영상을 실험에 사용한 결과 평균 86.2%의 차선별 주행차량 검지율을 보였으며, 검지된 차량들을 차선별 방향별로 구분하여 평균 속도를 측정하였다.

On-Line Departure time based link travel time estimation using Spatial Detection System (구간검지체계를 이용한 On-Line 출발시각기준 링크 통행시간 추정 (연속류를 중심으로))

  • Kim, Jae-Jin;No, Jeong-Hyeon;Park, Dong-Ju
    • Journal of Korean Society of Transportation
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    • v.24 no.2 s.88
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    • pp.157-168
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    • 2006
  • Spatial detection system such as AVI, GPS, and Beacon etc. can provide spatial travel time only after a vehicle Passes through a road section. In this context, majority of the existing studies on the link travel time estimation area has focused on the arrival time-based link travel time estimation. rather than departure time-based link travel time estimation. Even if some of the researches on this area have developed departure time-based link travel time estimation algorithms, they are limited in that they are not applicable in a real-time mode. The objective of this study is to develop an departure time-based link travel time estimation algorithm which is applicable in a real-tine mode. Firstly, this study discussed the tradeoff between accuracy and timeliness of the departure time-based on-line link travel time estimates. Secondly, this study developed an departure time-based on-line link travel time estimation algorithm which utilizes the Baysian inference logic. It was found that the proposed approach could estimate departure time-based link travel times in a real-time context with an acceptable accuracy and timeliness.

Highway Incident Detection and Classification Algorithms using Multi-Channel CCTV (다채널 CCTV를 이용한 고속도로 돌발상황 검지 및 분류 알고리즘)

  • Jang, Hyeok;Hwang, Tae-Hyun;Yang, Hun-Jun;Jeong, Dong-Seok
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.2
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    • pp.23-29
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    • 2014
  • The advanced traffic management system of intelligent transport systems automates the related traffic tasks such as vehicle speed, traffic volume and traffic incidents through the improved infrastructures like high definition cameras, high-performance radar sensors. For the safety of road users, especially, the automated incident detection and secondary accident prevention system is required. Normally, CCTV based image object detection and radar based object detection is used in this system. In this paper, we proposed the algorithm for real time highway incident detection system using multi surveillance cameras to mosaic video and track accurately the moving object that taken from different angles by background modeling. We confirmed through experiments that the video detection can supplement the short-range shaded area and the long-range detection limit of radar. In addition, the video detection has better classification features in daytime detection excluding the bad weather condition.