• 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.

• Journal of the Korean Society for Railway
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• v.14 no.2
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• pp.116-120
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• 2011

For the train positioning system currently applied in high-speed MAGLEV train systems, it is classified into absolute positioning systems which discontinuously detect train positions, and relative positioning systems which continuously detect train positions. In this paper we analyze the configuration model and the numerical model of the absolute positioning system applied in TRANSRAPID which is a representative high-speed MAGLEV train, and design the two configuration models specific to the recognition structures of absolute positioning systems. We also verify the compatibility of the design models of absolute positioning system through simulation using MATLAB and propose the optimal configuration model of absolute positioning systems for high-speed MAGLEV train system.

• Journal of the Korean Society for Railway
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• v.15 no.6
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• pp.604-608
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• 2012

Traditionally, the track circuits have been used for the purpose of train locating. However, the recent train control systems like a CBTC(Communications Based Train Control) do not utilize the track circuits to minimize the amount of ground signal devices. Therefore, there are increasing concerns over the system that can locate the position of train exactly without using the track circuits. Then, the contactless locating methods are added to ensure safety when the shunting sensitivity of the track circuit becomes low for the existing sections equipped with the track circuits. In this paper, a prototype of train locating device has been designed and tested, which utilizes the current phase difference upon magnetic field variation. The results show improved features of this method over the conventional track circuits method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.2
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• pp.34-44
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• 2007

Many urban cities deployed ITS technologies to improve the efficiency of traffic operation and management including a real-time franc control system (i.e., COSMOS). The system adopted loop detector system to collect traffic information such as volume, occupancy time, degree of saturation, and queue length. This paper investigated the applicability of detector information within COSMOS to represent the congestion level of the links. Initially, link travel times obtained from the field study were related with each of detector information. Results showed that queue length was highly correlated with link travel time, and direct link travel time estimation using the spot speed data produced high estimation error rates. From this analysis, a procedure was proposed to estimate congestion level of the links using both degree of saturation and queue length information.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.2
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• pp.14-23
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• 2015

This study was intended to evaluate the feasibility of the vehicle detector using a coil sensor. For the evaluation, the research team built a test environment for the detector consisting of a oscillation circuit, data collecting circuit, data monitoring and saving circuit, etc. As the result of the frequency analysis of the detector from the test environment, it was verified for the detector using a coil sensor to generate stable frequencies. In addition, the ease of construction and management was tested by comparing the size of cutting areas, consumption of installation materials, and installation time for a traditional loop detector and the detector using a coil sensor. As a result, the installation of the detector using a coil sensor requires less size of cutting areas, consumption of installation materials, and installation time.

• 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.

• Journal of Digital Contents Society
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• v.3 no.1
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• pp.1-9
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• 2002

This paper is proposed to algorithm for measuring traffic information automatically, for example, volume count, speed and occupancy rate, from CCTV camera images installed on highway, add to function of image detectors which can be collected the traffic information. Recently the method of traffic informations are counted in lane one by one, but this manner is occurred critical errors by occlusion frequently in case of passing larger vehicles(bus, truck etc.) and is impossible to measure in the 8 lanes of highway. In this paper, installed the detection area include with all lanes, traffic informations are collected using tracking algorithm with passing vehicles individually in this detection area, thus possible to detect all of 8 lanes. The experiment have been conducted two different real road scenes for 20 minutes. For the experiments, the images are provided with CCTV camera which was installed at Kiheung Interchange upstream of Kyongbu highway, and video recording images at Chungkye Tunnel. For image processing, images captured by frame-grabber board 30 frames per second, $640{\times}480$ pixels resolution and 256 gray-levels to reduce the total amount of data to be interpreted.

• 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.

• Journal of Korean Society of Transportation
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• v.23 no.5 s.83
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• pp.123-134
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• 2005

This research aims at developing a new method which can replace the existing method. known as the quality factor(Q factor) method by an L-R-C test for use in the performance test of inductive loop detectors(ILD) being installed and maintained. In this study, a sensor to detect a magnetic field in terms of frequency and intensity, a method to collect field data, the method of analysis, and the method of diagnosis were developed. An automatic diagnosis system which was developed to overcome those drawbacks has the following features : First, field data is collected automatically by a test vehicle equipped with magnetic field sensors that is running can be said to along the roadway and. thus, the new system completely overcome the roadway and, thus, the new system can be said to completely overcome the inefficiency of the existing method second, since the magnetic fold generated from the ILD is the final output of the whole system of ILD, the existing problem has been solved. third. since each of the detection area by height is collected by the magnetic sensors installed by height. a basic for the identification of the vehicle types to be detectable and the setting of adjustment factors has been made. For the automatic diagnosis system developed during in this study, a reliability test was carried out by comparing vehicle times of ILD installed ideally.