• Title/Summary/Keyword: traffic detection system

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Pilot Implementation of Intelligence System for Accident Prevention at Railway Level Crossing (철도건널목 지능화시스템 시범 구축)

  • Cho, Bong-Kwan;Ryu, Sang-Hwan;Hwang, Hyeon-Chyeol;Jung, Jae-Il
    • Proceedings of the KSR Conference
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    • 2010.06a
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    • pp.1112-1117
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    • 2010
  • The intelligent safety system for level crossing which employs information and communication technology has been developed in USA and Japan, etc. But, in Korea, the relevant research has not been performed. In this paper, we analyze the cause of railway level crossing accidents and the inherent problem of the existing safety equipments. Based on analyzed results, we design the intelligent safety system which prevent collision between a train and a vehicle. This system displays train approaching information in real-time at roadside warning devices, informs approaching train of the detected obstacle in crossing areas, and is interconnected with traffic signal to empty the crossing area before train comes. Especially, we present the video based obstacle detection algorithm and verify its performance with prototype H/W since the abrupt obstacles in crossing areas are the main cause of level crossing accidents. We identify that the presented scheme detects both pedestrian and vehicle with good performance. Currently, we demonstrate developed railway crossing intelligence system at one crossing of Young-dong-seon line of Korail with Sea Train cockpit.

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Implementation and Evaluation of Multiple Target Algorithm for Automotive Radar Sensor (차량용 레이더 센서를 위한 다중 타겟 알고리즘의 구현과 평가)

  • Ryu, In-hwan;Won, In-Su;Kwon, Jang-Woo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.16 no.2
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    • pp.105-115
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    • 2017
  • Conventional traffic detection sensors such as loop detectors and image sensors are expensive to install and maintain and require different detection algorithms depending on the night and day and have a disadvantage that the detection rate varies widely depending on the weather. On the other hand, the millimeter-wave radar is not affected by bad weather and can obtain constant detection performance regardless of day or night. In addition, there is no need for blocking trafficl for installation and maintenance, and multiple vehicles can be detected at the same time. In this study, a multi-target detection algorithm for a radar sensor with this advantage was devised / implemented by applying a conventional single target detection algorithm. We performed the evaluation and the meaningful results were obtained.

Study on the near-real time DNS query analyzing system for DNS amplification attacks (DNS 증폭 공격 탐지를 위한 근실시간 DNS 질의 응답 분석 시스템에 관한 연구)

  • Lee, Ki-Taek;Baek, Seung-Soo;Kim, Seung-Joo
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.25 no.2
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    • pp.303-311
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    • 2015
  • DNS amplification is a new type of DDoS Attack and nowadays the attack occurs frequently. The previous studies showed the several detection ways such as the traffic analysis based on DNS queries and packet size. However, those methods have some limitations such as the uncertainty of packet size which depends on IP address type and vulnerabilities against distributed amplification attack. Therefore, we proposed a novel traffic analyzing algorithm using Success Rate and implemented the query analyzing system.

Research of Vehicles Longitudinal Adaptive Control using V2I Situated Cognition based on LiDAR for Accident Prone Areas (LiDAR 기반 차량-인프라 연계 상황인지를 통한 사고다발지역에서의 차량 종방향 능동제어 시스템 연구)

  • Kim, Jae-Hwan;Lee, Je-Wook;Yoon, Bok-Joong;Park, Jae-Ung;Kim, Jung-Ha
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.5
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    • pp.453-464
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    • 2012
  • This is a research of an adaptive longitudinal control system for situated cognition in wide range, traffic accidents reduction and safety driving environment by integrated system which graft a road infrastructure's information based on IT onto the intelligent vehicle combined automobile and IT technology. The road infrastructure installed by laser scanner in intersection, speed limited area and sharp curve area where is many risk of traffic accident. The road infra conducts objects recognition, segmentation, and tracking for determining dangerous situation and communicates real-time information by Ethernet with vehicle. Also, the data which transmitted from infrastructure supports safety driving by integrated with laser scanner's data on vehicle bumper.

ECG Monitoring using High-Reliability Functional Wireless Sensor Node based on Ad-hoc network (고신뢰도 기능성 무선센서노드를 이용한 Ad-hoc기반의 ECG 모니터링)

  • Lee, Dae-Seok;Do, Kyeong-Hoon;Lee, Hoon-Jae
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.6
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    • pp.1215-1221
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    • 2009
  • A novel approach for electrocardiogram (ECG) analysis within a functional sensor node has been developed and evaluated. The main aim is to reduce data collision, traffic overload and power consumption in healthcare applications of wireless sensor networks(WSN). The sensor node attached on the patient's body surface around the heart can perform ECG analysis based on a QRS detection algorithm to detect abnormal condition of the patient. Data transfer is activated only after detected abnormality in the ECG. This system can reduce packet loss during transmission by reducing traffic overload. In addition, it saves power supply energy leading to more reliable, cheap and user-friendly operation in the WSN for ubiquitous health monitoring.

Overlap Removal and Background Updating for Associative Tracking of Multiple Vehicles (다중 차량 연관 추적을 위한 겹침 제거 및 배경영상 갱신)

  • Lim, Jun-Sik;Kim, Soo-Hyung;Lee, Chil-Woo;Lee, Myung-Eun
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.1
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    • pp.90-94
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    • 2010
  • In this paper, we propose a vehicle tracking method that can be applied in the intelligent traffic information system. The proposed method mainly consists of two steps: overlap removal and background updating. In order to remove overlap, we detect the overlap based on the location of the vehicle from successive images. Background updating is to calculate a background using statistical analysis of successive images. We collected a set of test images from the traffic monitoring system and experimented. The experimental results show more than 96% of tracking accuracy.

FCWA(Forward Collision Warning and Avoidance) algorithm using MMW Radar Sensor (레이더 센서를 이용한 종방향 충돌방지 및 회피 알고리즘)

  • 이태훈;유기정;박문수;홍석교
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.389-389
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    • 2000
  • The number of automobiles is rapidly increasing , as are the importance of the car as a way of transportation, and the variety of its uses. In these surroundings, a safety, one of the primary factors which must be considered in automotive engineering, demands a system that aids the driver's vision and perception. In this point of view, development of the more promoted system that complement the existing passive method which relies on just man's ability is the important issue of the advanced traffic system including ITS. In this paper, we provide an algorithm and implementation of a control system that warns the collisions ahead and avoids this situation, using informations about the host-car, target-car and surroundings. The warning is made by an algorithm that decides the degree of safely. With this degree of safely, the controller automatically controls a vehicle's speed to a proper level.

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Stop Object Method within Intersection with Using Adaptive Background Image (적응적 배경영상을 이용한 교차로 내 정지 객체 검출 방법)

  • Kang, Sung-Jun;Sur, Am-Seog;Jeong, Sung-Hwan
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.14 no.5
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    • pp.2430-2436
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    • 2013
  • This study suggests a method of detecting the still object, which becomes a cause of danger within the crossroad. The Inverse Perspective Transform was performed in order to make the object size consistent by being inputted the real-time image from CCTV that is installed within the crossroad. It established the detection area in the image with the perspective transform and generated the adaptative background image with the use of the moving information on object. The detection of the stop object was detected the candidate region of the stop object by using the background-image differential method. To grasp the appearance of truth on the detected candidate region, a method is proposed that uses the gradient information on image and EHD(Edge Histogram Descriptor). To examine performance of the suggested algorithm, it experimented by storing the images in the commuting time and the daytime through DVR, which is installed on the cross street. As a result of experiment, it could efficiently detect the stop vehicle within the detection region inside the crossroad. The processing speed is shown in 13~18 frame per second according to the area of the detection region, thereby being judged to likely have no problem about the real-time processing.

Track-Before-Detect Algorithm for Multiple Target Detection (다수 표적 탐지를 위한 Track-Before-Detect 알고리듬 연구)

  • Won, Dae-Yeon;Shim, Sang-Wook;Kim, Keum-Seong;Tahk, Min-Jea;Seong, Kie-Jeong;Kim, Eung-Tai
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.39 no.9
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    • pp.848-857
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    • 2011
  • Vision-based collision avoidance system for air traffic management requires a excellent multiple target detection algorithm under low signal-to-noise ratio (SNR) levels. The track-before-detect (TBD) approaches have significant applications such as detection of small and dim targets from an image sequence. In this paper, two detection algorithms with the TBD approaches are proposed to satisfy the multiple target detection requirements. The first algorithm, based on a dynamic programming approach, is designed to classify multiple targets by using a k-means clustering algorithm. In the second approach, a hidden Markov model (HMM) is slightly modified for detecting multiple targets sequentially. Both of the proposed approaches are used in numerical simulations with variations in target appearance properties to provide satisfactory performance as multiple target detection methods.

Efficient Tracking System for Passengers with the Detection Algorithm of a Stopping Vehicle (차량정차감지 알고리즘을 이용한 탑승자의 효율적 위치추적시스템)

  • Lee, Byung-Mun;Shin, Hyun-Ho;Kang, Un-Gu
    • Journal of Internet Computing and Services
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    • v.12 no.6
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    • pp.73-82
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    • 2011
  • The location-based service is emerging again to the public attention. The location recognition environment up-to-now has been studied with its focus only on a person, an object or a moving object. However, this study proposes a location recognition model that serves to recognize and track, in real time, multiple passengers in a moving vehicle. Identifying the locations of passengers can be classified into two classes: one is to use the high price terminal with GPS function, and the other is to use the economic price compact terminal without GPS function. Our model enables the simple compact terminal to provide effective location recognition under the on-boarding situation by transmitting messages through an interface device and sensor networks for a vehicle equipped with GPS. This technology reduces transmission traffic after detecting the condition of a vehicle (being parked or running), because it does not require transmission/receiving of information on the locations of passengers who are confined in a vehicle when the vehicle is running. Also it extends battery life by saving power consumption of the compact terminal. Hence, we carried out experiments to verify its serviceability by materializing the efficient tracking system for passengers with the detection algorithm of a stopping vehicle proposed in this study. Moreover, about 200 experiments using the system designed with this technology proved successful recognition on on-boarding and alighting of passengers with the maximum transmission distance of 12 km. In addition to this, the running recognition tests showed the test with the detection algorithm of a stopping vehicle has reduced transmission traffic by 41.6% compared to the algorithm without our model.