• Title/Summary/Keyword: Traffic Accident Detection

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An Implementation of Traffic Accident Detection System at Intersection based on Image and Sound (영상과 음향 기반의 교차로내 교통사고 검지시스템의 구현)

  • 김영욱;권대길;박기현;이경복;한민홍;이형석
    • Journal of Institute of Control, Robotics and Systems
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    • v.10 no.6
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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.

An In-Tunnel Traffic Accident Detection Algorithm using CCTV Image Processing (CCTV 영상처리를 이용한 터널 내 사고감지 알고리즘)

  • Baek, JungHee;Min, Joonyoung;Namkoong, Seong;Yoon, SeokHwan
    • KIPS Transactions on Software and Data Engineering
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    • v.4 no.2
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    • pp.83-90
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    • 2015
  • Almost of current Automatic Incident Detection(AID) algorithms involve the vulnerability that detects the traffic accident in open road or in tunnel as the traffic jam not as the traffic accident. This paper proposes the improved accident detection algorithm to enhance the detection probability based on accident detection algorithms applied in open roads. The improved accident detection algorithm provides the preliminary judgment of potential accident by detecting the stopped object by Gaussian Mixture Model. Afterwards, it measures the detection area is divided into blocks so that the occupancy rate can be determined for each block. All experimental results of applying the new algorithm on a real incident was detected image without error.

Detection Algorithm of Crossroad Traffic Accident Using the Sequence of Traffic Lights (신호등 주기를 이용한 교차로 교통사고감지 알고리즘)

  • Jeong, Sung-Hwan;Lee, Joon-Whoan
    • The KIPS Transactions:PartB
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    • v.16B no.1
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    • pp.17-24
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    • 2009
  • This paper suggests the background image and the algorism of detecting an accident at crossroads by using the sequence of traffic light at crossroads, which is installed within the crossroads, in order to detect an accident within crossroads. A method of using the existing image contains a problem that the accident-detection ratio gets lower in a situation that noise occurs loudly given using new accident model, the confused situation, or sound source. This study used the accident detection by developing a filter of using the property of histogram in the sequence of traffic light at crossroads and the background image, in order to reduce misjudgment of an accident caused by external shadow, vehicle stoppage, vehicle headlight, and externally environmental influence. As a result of experimenting by acquiring 15 actual accident images in order to examine the performance of the suggested algorism, the accident was detected in all the 15 videos. Even as for a new accident model, the accident within crossroads could be detected.

A Study on the Acoustic Characteristic Analysis for Traffic Accident Detection at Intersection (교차로 교통사고 자동감지를 위한 사고음의 음향특성 분석)

  • Park, Mun-Soo;Kim, Jae-Yee;Go, Young-Gwon
    • Proceedings of the KIEE Conference
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    • 2006.10c
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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].

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A Traffic Accident Detection and Analysis System at Intersections using Probability-based Hierarchical Network (확률기반 계층적 네트워크를 활용한 교차로 교통사고 인식 및 분석 시스템)

  • Hwang, Ju-Won;Lee, Young-Seol;Cho, Sung-Bae
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.10
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    • pp.995-999
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    • 2010
  • Every year, traffic accidents and traffic congestion have been rapidly increasing, Although the roadway design and signal system have been improved to relieve traffic accidents, traffic casualties and property damage do not decrease. This paper develops a real-time traffic accident detection and analysis system (RTADAS): In the proposed system, we aim to precisely detect traffic accidents at different design and flow of intersections, However, because the data collected from intersections have uncertainty and complicated causal dependency between them, we construct probability-based networks for correct accident detection.

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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Traffic Accident Detection Based on Ego Motion and Object Tracking

  • Kim, Da-Seul;Son, Hyeon-Cheol;Si, Jong-Wook;Kim, Sung-Young
    • Journal of Advanced Information Technology and Convergence
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    • v.10 no.1
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    • pp.15-23
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    • 2020
  • In this paper, we propose a new method to detect traffic accidents in video from vehicle-mounted cameras (vehicle black box). We use the distance between vehicles to determine whether an accident has occurred. To calculate the position of each vehicle, we use object detection and tracking method. By the way, in a crowded road environment, it is so difficult to decide an accident has occurred because of parked vehicles at the edge of the road. It is not easy to discriminate against accidents from non-accidents because a moving vehicle and a stopped vehicle are mixed on a regular downtown road. In this paper, we try to increase the accuracy of the vehicle accident detection by using not only the motion of the surrounding vehicle but also ego-motion as the input of the Recurrent Neural Network (RNN). We improved the accuracy of accident detection compared to the previous method.

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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Vehicle-Level Traffic Accident Detection on Vehicle-Mounted Camera Based on Cascade Bi-LSTM

  • Son, Hyeon-Cheol;Kim, Da-Seul;Kim, Sung-Young
    • Journal of Advanced Information Technology and Convergence
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    • v.10 no.2
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    • pp.167-175
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    • 2020
  • In this paper, we propose a traffic accident detection on vehicle-mounted camera. In the proposed method, the minimum bounding box coordinates the central coordinates on the bird's eye view and motion vectors of each vehicle object, and ego-motions of the vehicle equipped with dash-cam are extracted from the dash-cam video. By using extracted 4 kinds features as the input of Bi-LSTM (bidirectional LSTM), the accident probability (score) is predicted. To investigate the effect of each input feature on the probability of an accident, we analyze the performance of the detection the case of using a single feature input and the case of using a combination of features as input, respectively. And in these two cases, different detection models are defined and used. Bi-LSTM is used as a cascade, especially when a combination of the features is used as input. The proposed method shows 76.1% precision and 75.6% recall, which is superior to our previous work.

Development of the Algorithm for Traffic Accident Auto-Detection in Signalized Intersection (신호교차로 내 실시간 교통사고 자동검지 알고리즘 개발)

  • O, Ju-Taek;Im, Jae-Geuk;Hwang, Bo-Hui
    • Journal of Korean Society of Transportation
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    • v.27 no.5
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    • pp.97-111
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    • 2009
  • Image-based traffic information collection systems have entered widespread adoption and use in many countries since these systems are not only capable of replacing existing loop-based detectors which have limitations in management and administration, but are also capable of providing and managing a wide variety of traffic related information. In addition, these systems are expanding rapidly in terms of purpose and scope of use. Currently, the utilization of image processing technology in the field of traffic accident management is limited to installing surveillance cameras on locations where traffic accidents are expected to occur and digitalizing of recorded data. Accurately recording the sequence of situations around a traffic accident in a signal intersection and then objectively and clearly analyzing how such accident occurred is more urgent and important than anything else in resolving a traffic accident. Therefore, in this research, we intend to present a technology capable of overcoming problems in which advanced existing technologies exhibited limitations in handling real-time due to large data capacity such as object separation of vehicles and tracking, which pose difficulties due to environmental diversities and changes at a signal intersection with complex traffic situations, as pointed out by many past researches while presenting and implementing an active and environmentally adaptive methodology capable of effectively reducing false detection situations which frequently occur even with the Gaussian complex model analytical method which has been considered the best among well-known environmental obstacle reduction methods. To prove that the technology developed by this research has performance advantage over existing automatic traffic accident recording systems, a test was performed by entering image data from an actually operating crossroad online in real-time. The test results were compared with the performance of other existing technologies.