• 한국IT서비스학회:학술대회논문집
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• 2007.11a
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• pp.604-608
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• 2007

현재 정보통신 기술의 발달에 상응하여 지능형 교통 시스템(ITS)은 네트워크 기반으로 실시간 교통 정보를 제공하기 위해 CCTV, GPS, VDS, 루프 검지기, 영상 검지기 등과 같은 다양한 방법으로 교통 정보 수집이 이루어지고 있다. 또한 정확한 정보 제공을 위해 정보의 수집 및 가공에 대한 많은 연구들이 진행되고 있다. 본 논문에서는 텔레매틱스 기반의 효율적인 교통정보 수집을 위해 RFID 태그 정보를 이용하여 교통정보를 수집하여 보다 정확한 실시간 차량 정보를 제공하는 RFID 기반의 차량점보수집 시스템 모델을 제시하고자 한다.

• Journal of Korean Society of Transportation
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• v.16 no.3
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• pp.101-111
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• 1998

현재 고속도로 교통관리시스템(FTMS)에 사용되고 있는 차량 검지기는 주로 루프 식 검지기가 이용되고 있으나, 유지관리에 많은 어려움이 있다. 본 연구에서는 이러한 문제 점을 갖고 있는 루프 검지기를 대체하기 위한 대체 검지기를 개발하는데 그 목적이 있다. 자기 검지기 신뢰도 평가는 현장 실험으로 이루어지며 비디오 촬영 및 루프 검지기, test car를 이용하여 교통량·속도·점유율의 기준자료를 마련하고 자기 검지기 자료와 비교·분석 및 통계적 검정을 실시하였다. 1차 실험과 2차 실험의 결과, 교통량과 속도는 실측자료와 유사했으나 점유율은 실측치와 다소 차이가 발생함을 보였다. 향후 점유율에 대한 보정이 이루어진다면 현재 사용중인 루프 검지기를 대체할 수 있을 것으로 기대된다.

• Journal of KIISE:Software and Applications
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• v.33 no.5
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• pp.489-498
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• 2006

In this paper, we suggested a vehicle classification algorithm using pattern recognition method. At present, Inductive Loop Detector is rarely used for vehicle classification because of its low accuracy. To improve the accuracy, we suggest a new algorithm for Loop Detector using neural networks. In the developed algorithm, the inputs to the neural networks are the variation rate of frequency and occupancy-time. The output is classified vehicles. The developed algorithm was assessed at test sites and the recognition rate was 91.3percent. The results verified that the proposed algorithm improves the vehicle classification accuracy compared to the conventional method based on Loop Detector.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.1
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• pp.15-27
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• 2013

While the vehicle detector is collected from a variety of information was mainly used as a real-time data. Recently scheme of application for archived traffic data has become increasingly important. In this background, this research were conducted on the improvement of the preprocessing for archived traffic data application. The purpose of improving specific preprocessing was reflect transportation phenomena by traffic data. As evaluation result, improvement preprocessing was close to the actual value than exist preprocessing.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.5
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• pp.33-52
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• 2008

This research intended to study a vehicle detection method for traffic volume, speed, stoping, parking activity, etc. using real time image processing and to propose the more accurate, environment adaptive image processing algorithm. The new method was compared with an existing commercialized image processing system, 'A' Product, for performance reliability tests. Also, the new method improved and developed the comparative advantage image processing algorithm. With regard to the test results, the algorithm over-counted one more vehicle, while 'A' product missed four vehicles during the test period. The first test results were used to improve the performance of this algorithm, and it's performance was improved though the second test in various and complicated traffic environment to yield superior performance.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.36-54
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• 2017

The purpose of this paper is to develop a multi-sensor fusion-based traffic information acquisition system with robust to environmental changes. it combines the characteristics of each sensor and is more robust to the environmental changes than the video detector. Moreover, it is not affected by the time of day and night, and has less maintenance cost than the inductive-loop traffic detector. This is accomplished by synthesizing object tracking informations based on a radar, vehicle classification informations based on a video detector and reliable object detections of a infrared range finder. To prove the effectiveness of the proposed system, I conducted experiments for 6 hours over 5 days of the daytime and early evening on the pedestrian - accessible road. According to the experimental results, it has 88.7% classification accuracy and 95.5% vehicle detection rate. If the parameters of this system is optimized to adapt to the experimental environment changes, it is expected that it will contribute to the advancement of ITS.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.709-711
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• 1998

본 연구에서는 도로 교통 정보검출을 위하여 사용되는 검지기 가운데 비매설형 차량검지 기술에 대한 분석을 통하여 국내환경에 적합한 검지기술의 기본 기능을 설정하였다. 분석된 검지기는 15개의 국내외 검지시스템으로 검지 성능 분석과 국내 적용시 발생되는 문제점을 파악하여 설계시 필요한 기본 계획을 설정하였다.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.423-425
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• 1998

영상검지기를 이용하여 도로상에서 이동중인 차량의 움직임을 탐지하고 분석하는 방법은 지능형교통시스템의 많은 분야에 적용되어질 수 있다. 영상분석으로 움직이는 물체를 탐지하는 방법에는 영상차를 이용하는 방법과 영상차를 이용하지 않는 방법으로 분류할 수 있다. 영상차를 이용하는 방법에서는 영상간의 차영상을 기반으로 하여 물체를 탐지하는 방법은 일반적이고 보편적인 방법이나 시간에 따른 배경영상의 왜곡과 물체의 정체현상에 많은 문제점을 지니고 있다. 그리고 영상차를 이용하지 않는 방법은 영상내의 분석으로 물체를 탐지하는 방법이고, 영상간의 정보를 사용하지 않으므로 영상차에 의한 문제점은 발생되지 않는다. 기존에 연구되어진 영상차를 이용하지 않는 방법은 물체의 형태를 고려하지 않고 단지 이동점의 좌표분석으로 차량의 움직임을 측정하고 있다. 본 논문에서는 영상차를 이용하지 않으며 영상내의 형태정보 분석과 색상정보를 고려하여 기존의 영상검지기가 지니는 문제점을 개선하여 정밀한 차량 추적에 대한 가능성을 알 수 있었다.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.9-21
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• 2022

In this paper, we developed a 100% detection system for entering and leaving vehicles by improving the detection rate of existing detection cameras based on the LiDAR sensor, which is one of the core technologies of the 4th industrial revolution. Since the currently operating parking lot depends only on the recognition rate of the license plate number of about 98%, there are various problems such as inconsistency in the entry/exit count, inability to make a reservation in advance due to inaccurate information provision, and inconsistency in real-time parking information. Parking status information should be managed with 100% accuracy, and for this, we built a parking lot entrance/exit detection system using LIDAR. When a parking system is developed by applying the LIDAR sensor, which is mainly used to detect vehicles and objects in autonomous vehicles, it is possible to improve the accuracy of vehicle entry/exit information and the reliability of the entry/exit count with the detected sensing information. The resolution of LIDAR was guaranteed to be 100%, and it was possible to implement so that the sum of entering (+) and exiting (-) vehicles in the parking lot was 0. As a result of testing with 3,000 actual parking lot entrances and exits, the accuracy of entering and exiting parking vehicles was 100%.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.5
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• pp.125-135
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• 2012

This paper proposes the new object detection system with two laser-scanners and a camera for classifying the objects and predicting the location of objects on road street. This detection system could be applied the new C-ITS service such as ADAS(Advanced Driver Assist System) or (semi-)automatic vehicle guidance services using object's types and precise position. This study describes the some examples in other countries and feasibility of object detection system based on a camera and two laser-scanners. This study has developed the heterogenous sensor's fusion method and shows the results of implementation at road environments. As a results, object detection system at roadside infrastructure is a useful method that aims at reliable classification and positioning of road objects, such as a vehicle, a pedestrian, and obstacles in a street. The algorithm of this paper is performed at ideal condition, so it need to implement at various condition such as light brightness and weather condition. This paper should help better object detection and development of new methods at improved C-ITS environment.