• Journal of Korea Multimedia Society
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• v.22 no.2
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• pp.128-135
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• 2019

This paper presents a deep learning-based object detection method for recognizing vehicles in images acquired through cameras installed on ceiling of underground parking lot. First, we present an image enhancement method, which improves vehicle detection performance under dark lighting environment. Second, we present a new CNN-based multiscale classifiers for detecting vehicles in images acquired through cameras with fisheye lens. Experiments show that the presented vehicle detector has better performance than the conventional ones.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.11 no.8
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• pp.1346-1354
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• 2000

본 논문에서는 기존의 루프감지기와 호환성이 있는 레이더 기술을 이용한 차량감지기를 개발하였다. 24 ㎓의 FMCW 고도계와 도플러 속도계 기술을 이용하여 도로상의 차량 길이와 속도정보를 알아낼 수 있는 비매설형의 차량감지기이다. 신호처리에는 DAQ 보드를 사용하였고, 응용소프트웨어인 LabView로 프로그래밍 하였다. 기존의 루프 감지기와 연결된 교통정보 네트웍과의 호환성을 위해 RS-232C 표준인터페이스를 이용하여 VDS(Vehicle Detector System)로 차량데이터를 전송하였다. 속도와 차량길이 정보의 정확도에 있어서 기존 루프감지기보다 약 10% 정도 향상되었음이 측정되었다.

• 한국ITS학회:학술대회논문집
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• 2008.11a
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• pp.301-308
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• 2008

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.1
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• pp.67-75
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• 2011

This paper presents a new test technique for evaluating performance of vehicle detectors with interval estimation, not the conventional point estimation, for presenting statistical confidence interval. The methodology is categorized into three parts; sampling plan, analysis on the characteristic of evaluation indices, and the expression of evaluation results. Even though many statistical sampling plans exist, stratified random sampling is regarded as the most appropriate one, considering the detector performance characteristics that varies with traffic, illumination, and meteorological conditions. No magic bullet exists for evaluation index for detector evaluation, hence the characteristics of evaluation indices were thoroughly analyzed and a reasonable process for choosing the best evaluation index is proposed. Finally, the methodology to express the result of detector evaluation for the entire evaluation period and individual analysis interval is represented, respectively. To overcome the existing drawbacks in point estimation, interval estimation by which statistical confidence interval can be represented is introduced for enhancing statistical reliability of traffic detector evaluation. This research can make vehicle detector scheme improve one step forward.

• Journal of Korean Society of Transportation
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• v.17 no.4
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• pp.111-124
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• 1999

The Purpose of this thesis is to develop a vehicle classification algorithm using single Magnetometer detector during presence time of vehicle detection and is to examine a held application from field test. We collected data using Magnetometer detector on freeway and used digital data to change voltage values according to magnetic flux density in analysis. We collected these datum during the presence time and then obtained characteristics from wave form in these datum. Based on these characteristics, We used the following three methods for this a1gorithm :1. Template Matching Method,2. Neural Network Method using Back-propagation Algorithm 3. Complex Method using changed slope points and mixing method 1, 2. Of course, Before processing of over three methods, These data were processed normalizing by 20, 40 of size in only X axis and moving average by 0, 3, 4, 5 of size. Vehicle classification were Processed in three steps ; 2, 3, 5 types classification. In 2 types vehicle classification, recognition rate is 83% by template matching method.

• Journal of Multimedia Information System
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• v.5 no.3
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• pp.155-162
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• 2018

Nowadays, the tracking technology of Quadrant Detector will become actual by new micro devices. Based on the past filed data of the reception experiment with COMETS satellite, we have studied on new device (AD8302, phase difference detector) was acquired and suspect its abilities. In 1998, we have developed a Quadrant Detector for mobile to track a weak signal from satellite on Ka band of COMETS. The Quadrant Detector is comprised of four dedicated feed components for reception under an environment of Nakagami - Rician fading, and one transmission and reception feed component. We were successful in receiving a 23 GHz beacon signal from ICE transponder of the COMETS and succeeded in tracking the satellite from a moving vehicle at speeds of approximately 10 ~ 20 Km/h on paved roads. In 2018, with new device AD8302, we have verified new QD system and performed a simulation, based on the past filed experiment. This new device shall be improving the tracking abilities from mobile body on the earth to the multimedia satellite.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.2
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• pp.1-9
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• 2020

A smart factory is a key industrial application introduced by the 4^th industrial revolution. The automatic guided vehicle (AGV) is one of the technology realizing smart factory, but the development cost is high due to its early stage of technology. Although developing a low-cost AGV requires a lot of data, it has limited data acquisition capability because of the limited storage and the AGV movement. Hence, we propose a development environment using Bluetooth to collect data and design a lane detector. The proposed lane detector shows a high lane detection ratio regardless of light variation and a shade.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.6
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• pp.102-108
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• 2002

This paper handles the design of a real time traffic data acquisition system using loop detector and piezo-electric sensor to acquire the vehicle information EISA compatible parallel I/O interface card is designed to sample 30 I/O channels at variable rates for raw traffic data acquisition. The control software is designed to generate the traffic data informations from the raw data. The traffic data information provides vehicle length, speed, number of axles, etc. Vehicle types are detected and categorized into eleven types from the vehicle length, axles positions and axle counts information. The traffic information is formed into packet and transferred to the remote hosts through serial communications for ITS applications.

• 한국ITS학회:학술대회논문집
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• 2003.11a
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• pp.230-233
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• 2003

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.12
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• pp.2355-2373
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• 2011

Vision-based vehicle detector systems are becoming increasingly important in ITS applications. Real-time operation, robustness, precision, accurate estimation of traffic parameters, and ease of setup are important features to be considered in developing such systems. Further, accurate vehicle detection is difficult in varied complex traffic environments. These environments include changes in weather as well as challenging traffic conditions, such as shadow effects and jams. To meet real-time requirements, the proposed system first applies a color background to extract moving objects, which are then tracked by considering their relative distances and directions. To achieve robustness and precision, the color background is regularly updated by the proposed algorithm to overcome luminance variations. This paper also proposes a scheme of feedback compensation to resolve background convergence errors, which occur when vehicles temporarily park on the roadside while the background image is being converged. Next, vehicle occlusion is resolved using the proposed prior split approach and through reasoning for rule-based tracking. This approach can automatically detect straight lanes. Following this step, trajectories are applied to derive traffic parameters; finally, to facilitate easy setup, we propose a means to automate the setting of the system parameters. Experimental results show that the system can operate well under various complex traffic conditions in real time.