• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.2
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• pp.74-88
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• 2020

A Cooperative Intelligent Transportation System (CITS) provides useful information on upcoming hazards in order to prevent vehicle collisions. In addition, the availability of individual vehicle travel information obtained from the CITS infrastructure allows us to identify the level of road safety in real time and based on analysis of the indicators representing the crash potential. This study proposes a methodology to derive road safety content, and presents evaluation results for its applicability in practice, based on simulation experiments. Both jerk and Stopping Distance Index (SDI) were adopted as safety indicators and were further applied to derive road section safety information. Microscopic simulation results with VISSIM show that 5% and 20% samples of jerk and SDI are sufficient to represent road safety characteristics for all vehicles. It is expected that the outcome of this study will be fundamental to developing a novel and valuable system to monitor the level of road safety in real time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.7
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• pp.3220-3226
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• 2011

In order to monitor internal risk factors such as fire, terror, etc. on the subway station, the surveillance systems using CCTV and various kinds of sensors have been implemented and recently, introduction of surveillance systems using an advanced IT technology, sensor network technology is tried on several areas. Since 2007, Korean government has made an effort to develop the intelligent surveillance and monitoring system, which can monitor fire, intrusion, passenger congestion, health-state of structure, etc., by using wireless sensor network technology and intelligent video analytic technique. For that purpose, this study carried out field wireless communication environment test on Chungmuro Station of Seoul Metro on the basis of ZigBee that is considered as a representative wireless sensor network before field application of the intelligent integrated surveillance system being developed, arranged and analyzed and ZigBee based wireless communication environment test results on the platform and waiting room of Chungmuro Station on this paper. Results of wireless spectrum analysis on the platform and waiting room showed that there is no radio frequency overlapped with that of ZigBee based sensor network and no frequency interference with adjacent frequencies separated 10MHz or more. As results of wireless data transmission test using ZigBee showed that data transmission is influenced by multi-path fading effect from the number and flow rate of passengers on the platform or the waiting room rather than effects from entrance and exit of the train to/from the platform, it should be considered when implementing the intelligent integrated surveillance system on the station.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.3
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• pp.57-66
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• 2007

Weaving is defined as the crossing of two or more traffic streams traveling in the same general direction along a significant length of highway without the aid of traffic control devices. Compared with other freeway sections, perturbation is easy to happen at weaving section. Because there are a lot of lane-changing maneuvers at the weaving section, traffic is subject to turbulence in excess of that normally presents on freeway basic section. This turbulence causes operational problems and its impact must be considered. The purpose of this paper is to perform a basic study on flow characteristics by lane, which can be achieved through analyzing breakdown phenomenon in the microscopic approach. The study made use of data derived from the aerial photography for the microscopic analysis. This research produced the 30-second interval data such as flows, speeds, and densities for the macroscopic analysis and derived the vehicular data to draw time-space diagram for the microscopic analysis. The paper analyzed the traffic characteristics using flows, speeds and densities variation and investigated the conditions of breakdown occurrence with the time-space diagrams. The breakdown phenomenon was identified at weaving section and the propagation from free flow to synchronized flow was observed in this study. In the future, the findings help develop the traffic operational algorithm to manage the traffic congestion under ubiquitous circumstance since the conditions of breakdown Phenomenon can be understood more.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.4
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• pp.11-23
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• 2011

The objective of this paper is to develop a daily pattern clustering algorithm using historical traffic data that can reliably detect under various traffic flow conditions in urban streets. The developed algorithm in this paper is categorized into two major parts, that is to say a macroscopic and a microscopic points of view. First of all, a macroscopic analysis process deduces a daily peak/non-peak hour and emphasis analysis time zones based on the speed time-series. A microscopic analysis process clusters a daily pattern compared with a similarity between individuals or between individual and group. The name of the developed algorithm in microscopic analysis process is called "Two-step speed clustering (TSC) algorithm". TSC algorithm improves the accuracy of a daily pattern clustering based on the time-series speed variation data. The experiments of the algorithm have been conducted with point detector data, installed at a Ansan city, and verified through comparison with a clustering techniques using SPSS. Our efforts in this study are expected to contribute to developing pattern-based information processing, operations management of daily recurrent congestion, improvement of daily signal optimization based on TOD plans.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.11 no.4
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• pp.89-96
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• 2002

This paper aims to develop an intelligent model for predicting top-bead width for the robotic GMA(Gas Metal Arc) welding process using BP(Back-propagation) neural network and multiple regression analysis. Firstly, based on experimental data, the basic factors affecting top-bead width are identified. Then BP neural network model and multiple regression models of top-bead width are established. The modeling methods and procedure are explained. The developed models are then verified by data obtained from the additional experiment and the predictive behaviors of the two kind of models are compared and analysed. Finally the modeling methods, predictive behaviors md the advantages of each models are discussed.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.96-98
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• 2005

This paper describes a monitoring system that monitors power quality and undesirable accidents when distributed generations are connected to the power grid. Prior to develop and operate a physical monitoring system, we constitute a simulation device to simulate the monitoring processes for the situations. The simulation system consists of the server and the client that connected by communication line. This system has various functions to monitor the power quality and the connection situation. Those functions are generation, transmission, acquisition and analysis of the simulated power data. This research seems very important to get the reliable and intelligent connection algorithm through the result of simulated monitoring system. Also hereafter, as this system uses the remote monitoring system through network and constitute the data base(DB), it will play an important role in building the automation of power system efficiently and systematically.

• Asia pacific journal of information systems
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• v.13 no.2
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• pp.23-46
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• 2003

This paper proposes an analysis methodology that enables the establishment of improved customer satisfaction via decision support system using customer satisfaction index data and customer database of a company. The proposed methodology establishes rational future goal of a company by applying DEA, finds potential customers which correspond to demographic features of the previous target group, and improve quality factors which distinguish the quality-satisfaction-group from the quality-dissatisfaction-group through the use of machine learning tools, SOM and C4.5. Finally, we illustrate the effectiveness of our research methodology using actual data of a camera company.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.147-149
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• 2006

We designed an intelligent intrusion detection scheme that works based on target system's operational states and doesn't depend on humans' analysis. As a prior work, we presents a scheme to describe computer system's operational states. For this, Hidden Markov Model is used. As input to modeling, huge amount of system audit trail including data on events occurred in target system connected to network and target system's resource usage monitoring data is used. We can predict system's future state based on current events' sequence using developed model and determine whether it would be in daniel or not.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.413-416
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• 2007

Use ot Intelligent devices that work on the ANSI/EIA 709.1 protocol is increasing. In this study an ANSI/EIA 709.1 protocol analyzer that can monitor and analyze the packets on LonWorks network is designed and developed. The device is based on TMS320LF2407A processor for decoding data packets, and uses XScale processor for sending data to the application program on PC. The application program has various analysis features as well as basic monitoring function. The developed device can be used for debugging purposes in development of any kind of LonWorks devices, and also it is useful in maintenance of LonWorks network or Lon Works devices.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.3
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• pp.309-330
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• 2009

In this paper, we introduce the architecture of Genetic Algorithm(GA) based Feed-forward Polynomial Neural Networks(PNNs) and discuss a comprehensive design methodology. A conventional PNN consists of Polynomial Neurons, or nodes, located in several layers through a network growth process. In order to generate structurally optimized PNNs, a GA-based design procedure for each layer of the PNN leads to the selection of preferred nodes(PNs) with optimal parameters available within the PNN. To evaluate the performance of the GA-based PNN, experiments are done on a model by applying Medical Imaging System(MIS) data to a multi-variable software process. A comparative analysis shows that the proposed GA-based PNN is modeled with higher accuracy and more superb predictive capability than previously presented intelligent models.