• International Journal of Highway Engineering
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• v.12 no.4
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• pp.47-51
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• 2010

A vehicle classification data is essential for traffic road planning and pavement. In this study, the vehicle height, vehicle criteria for classification applied to measure the height of the car driving has devised a way to install equipment. It is capable of measuring the vehicle height was confirmed to field experiments, the measurement system is obtained to the vehicle length and height data. In this experiment, results showed the accuracy of 88.6% compared to classification data using the discriminant function obtained from video replaying. The height of vehicle applying the classification criteria can be utilized to determine the vehicle class.

• Journal of Korean Society of Transportation
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• v.24 no.3 s.89
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• pp.39-50
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• 2006

This study aims to introduce a basic principle to improve the incident detection algorithm using traffic flow diagrams that can classify traffic states with a high reliability on the basis of the analysis of traffic flow characteristics under the recurrent or incident congestions. It is tried to newly classify the traffic states with the speed-flow and speed-occupancy diagrams. This is because McMaster algorithm has a tendancy on not identifying the traffic states exactly using the flow-occupancy diagram. In this study it shows that the classification of traffic states is applicable to use speed-occupancy relationship Therefore, it is necessary to determine some parameters to correctly classify the areas representing the traffic states and it may be possible to develop a new algorithm to detect the incident with a high reliability.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.9 s.351
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• pp.128-134
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• 2006

Traffic information protocol in DMB is very different from existing analog broadcasting and wireless communication network. In this paper, we examined whether traffic information protocol of Europe Broadcasting Union(TPEG) is applicable to domestic DMB. Also, we proposed a division of classification on kinds of franc information, and related data that it is required to transmit traffic information of TPEG form. We composed of experiment equipment and studied whether is expressed traffic informations as like accident, event, traffic condition and CCTV image on car navigation system. The results obtained it can be given expression to phrases from TPEG streaming data and to link with electronics map by decoding TPEG straming data. Also it can be expressed CCTV and graphic image which is composed of TPEG form.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1630-1636
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• 2022

The results of current method of traffic sign detection gets hindered by environmental conditions and the traffic sign's condition as well. Therefore, in this paper, we propose a method of improving detection performance of damaged traffic signs by utilizing Hopfield Network and Fuzzy Max-Min Neural Network. In this proposed method, the characteristics of damaged traffic signs are analyzed and those characteristics are configured as the training pattern to be used by Fuzzy Max-Min Neural Network to initially classify the characteristics of the traffic signs. The images with initial characteristics that has been classified are restored by using Hopfield Network. The images restored with Hopfield Network are classified by the Fuzzy Max-Min Neural Network onces again to finally classify and detect the damaged traffic signs. 8 traffic signs with varying degrees of damage are used to evaluate the performance of the proposed method which resulted with an average of 38.76% improvement on classification performance than the Fuzzy Max-Min Neural Network.

• Journal of applied mathematics & informatics
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• v.9 no.2
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• pp.879-890
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• 2002

In this paper we consider open queueing system with a Poisson arrival process which have a finite upper bound on the arrival rate for which the system is stable. Interpolation approximations for quantities of interest, such as moments of the sojourn time distribution, have previously been developed for such systems, utilizing exact light and heavy traffic limits. These limits cannot always be easily computed for complex systems. Thus we consider an interpolation approximation where all of the relevant information is estimated via simulation. We show that all the relevant information can in fact be simultaneously estimated in a single regenerative simulation at any arrival rate. In addition to light and heavy traffic limits, both the quantity of interest and its derivative (with respect to the arrival rate) are estimated at the arrival rate of the simulation. All of the estimates are then combined, using a least squares procedure, to provide an interpolation approximation.

• Journal of Korean Society of Transportation
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• v.14 no.2
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• pp.7-29
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• 1996

Traffic flow characteristics is analysed on eight multi-lane roads which are unsignalized in urban areas. Data of traffic flow rates by classification and average speed were gathered every ten minutes interval for twenty-four hours. Machine (NC-90A) was used to acquire the field data. The major purpose of this study is to build up speed-density models on urban arterial roads. Five different kinds of models were tested. Those models are Greenshields' model, Greenberg's model, modified Greenberg's model, Underwood's model and Drake's model. The modified Greenberg's model fits best at six points and the Greenshield's model fits best two points out of eight points. The breakpoint(Kb) of modified Greenberg's model is between 10 and 32 pcphpl. Capacity drawn from speed-volume relationships were appeared to be arround 2,000 and 2,200 pcphpl at the Hannam Bridge and the Hannam Overpass and 1,100 and 1,700 pcphpl at Namsan Tunnel(No1) and the beginning point of Gyeong-Bu Expressway.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.587-590
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• 2004

In this paper proposed a HMM(Hidden Martov Model)-based segmentation method which is able to model shadows as well as foreground and background regions. Shadow of moving objects often obstruct visual tracking. We propose an HMM-based segmentation method which classifies in real time oath objects. In the case of traffic monitoring movies, the effectiveness of the proposed method has been proven through experimental results

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2160-2168
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• 2015

The SSL/TLS, one of the most popular encryption protocol, was developed as a solution of various network security problem while the network traffic has become complex and diverse. But the SSL/TLS traffic has been identified as its protocol name, not its used services, which is required for the effective network traffic management. This paper proposes a new method to generate service signatures automatically from SSL/TLS payload data and to classify network traffic in accordance with their application services. We utilize the certificate publication information field in the certificate exchanging record of SSL/TLS traffic for the service signatures, which occurs when SSL/TLS performs Handshaking before encrypt transmission. We proved the performance and feasibility of the proposed method by experimental result that classify about 95% SSL/TLS traffic with 95% accuracy for every SSL/TLS services.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.5
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• pp.407-414
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• 2020

SVM (Support vector machine) analysis was performed after applying a deep learning technique based on an Inception-based model (GoogLeNet). The accuracy of automatic image classification was analyzed using an SVM with multiple virtual grid sizes. Six classes were selected from a standard land cover map. Cars were added as a separate item to increase the classification accuracy of roads. The virtual grid size was 2-5 m for natural areas, 5-10 m for traffic areas, and 10-15 m for building areas, based on the size of items and the resolution of input images. The results demonstrate that automatic classification accuracy can be increased by adopting an integrated approach that utilizes weighted virtual grid sizes for different classes.

• Journal of Information Processing Systems
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• v.2 no.1
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• pp.52-57
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• 2006

One of the important functions of an Intelligent Transportation System (ITS) is to classify vehicle types using a vision system. We propose a method using machine-learning algorithms for this classification problem with 3-D object model fitting. It is also necessary to detect road lanes from a fixed traffic surveillance camera in preparation for model fitting. We apply a background mask and line analysis algorithm based on statistical measures to Hough Transform (HT) in order to remove noise and false positive road lanes. The results show that this method is quite efficient in terms of quality.