• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.5
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• pp.38-48
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• 2010

Adverse weather (e.g. strong winds, snow and ice) will probably appear as a more serious and frequent threat to road traffic than in clear climate. Another consequence of climate change with a natural disastrous on road traffic is respond to traffic accident more the large and high-rise bridge zone, tunnel zone, inclined plane zone and de-icing zone than any other zone, which in turn calls for continuous adaption of monitoring procedures. Accident mitigating measures against this accident category may consist of intense winter maintenance, the use of road weather information systems for data collection and early warnings, road surveillance and traffic control. While hazard from reduced road friction due to snow and ice may be eliminated by snow removal and de-icing measures, the effect of strong winds on road traffic are not easily avoided. The purpose of the study described here, was to design of amber information the relationship between traffic safety, weather, user information on road weather and driving conditions in local-scale Geographic. The most applications are the optimization of the amber information definition, improvements to road surveillance, road weather monitoring and improved accuracy of user information delivery. Also, statistics on wind gust, surface condition, vehicle category and other relevant parameters for wind induced accidents provide basis for traffic control, early warning policies and driver education for improved road safety at bad weather-exposed locations.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.55-69
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• 2017

Recently, the IoT (Internet of Things) environment is being developed rapidly through network which is linked to intellectual objects. Through the IoT, it is possible for human to intercommunicate with objects and objects to objects. Also, the IoT provides artificial intelligent service mixed with knowledge of situational awareness. One of the industries based on the IoT is a car industry. Nowadays, a self-driving vehicle which is not only fuel-efficient, smooth for traffic, but also puts top priority on eventual safety for humans became the most important conversation topic. Since several years ago, a research on the recognition of the surrounding environment for self-driving vehicles using sensors, lidar, camera, and radar techniques has been progressed actively. Currently, based on the WAVE (Wireless Access in Vehicular Environment), the research is being boosted by forming networking between vehicles, vehicle and infrastructures. In this paper, a research on the recognition of a traffic signs on highway was processed as a part of the awareness of the surrounding environment for self-driving vehicles. Through the traffic signs which have features of fixed standard and installation location, we provided a learning theory and a corresponding results of experiment about the way that a vehicle is aware of traffic signs and additional informations on it.

• Journal of Intelligence and Information Systems
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• v.11 no.3
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• pp.25-43
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• 2005

In modern automated container terminals, automated guided vehicle (AGV) systems are considered a viable option for the horizontal tansportation of containers between the stacking yard and the quayside cranes. AGVs in a container terminal move rather freely and do not follow fixed guide paths. For an efficient operation of such AGVs, however, a sophisticated traffic management system is required. Although the flexible routing scheme allows us to find the shortest possible routes for each of the AGVs, it may incur many coincidental encounters and path intersections of the AGVs, leading to collisions or deadlocks. However, the computational cost of perfect prediction and avoidance of deadlocks is prohibitively expensive for a real time application. In this paper, we propose a traffic control method that predicts and avoids some simple, but at the same time the most frequently occurring, cases of deadlocks between two AGVs. More complicated deadlock situations are not predicted ahead of time but detected and resolved after they occur. Our method is computationally cheap and readily applicable to real time applications. The efficiency and effectiveness of our proposed methods have been validated by simulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.6
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• pp.1292-1305
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• 2013

Along with the strengthening vehicle environmental regulations and the growing needs for the energy consumption reduction technology, the researches on the engine idle stop system, have been briskly carried out around the automobile manufacturers before the development of alternative energy. Furthermore, there is a movement to disseminate the environment friendly idle stop system by combining the system to the generalized smart key system to not only increase purchasing but also provide the convenience and save the energy as well. In this paper, we designed and implemented the idle stop system algorithm for the aftermarket smart key system with the OBD-II interface. The implemented start stop system is capable of controlling two independent systems, the smart key system and intelligent idle stop system, on a single ECU. In addition, the implemented start stop system standardizes the communication interface with the vehicles to reduce the time required for installing the start stop system to the various vehicles, and satisfies every standard response time limit for the vehicle status request signals.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.11B
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• pp.1346-1356
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• 2011

Transportation has been playing important role in our society by providing for people, freight, and information. However, it cuts its own throat by causing car accidents, traffic congestion, and air pollution. The main cause of these problems is a noticeable growth in the number of vehicles. The easiest way to mitigate these problems is to build new road infrastructures unless resources such as time, money, and space are limited. Therefore, there is a need to manage the existing road infrastructures effectively and safely. In this paper, we propose a road reservation scheme that provides fast and safe response for emergency vehicles using ubiquitous sensor network. Our idea is to allow emergency vehicle to reserve a road on a freeway for arriving to the scene of the accident quickly and safely. We evaluate the performance by three reservation method (No, Hop, and Full) to show that emergency vehicles such as ambulances, fire trucks, or police cars can rapidly and safely reach their destination. Simulation results show that the average speed of road reservation is about 1.09 ~ 1.20 times faster than that of non-reservation at various flow rates. However, road reservation should consider the speed of the emergency vehicle and the road density of the emergency vehicle processing direction, as a result of Hop Reservation and Full Reservation performance comparison analysis. We confirm that road reservation can guarantee safe driving of emergency vehicles without reducing their speed and help to mitigate traffic congestion.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.113-123
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• 2012

Recently, various attempts have been made to apply Intelligent Transportation System under various environments and conditions. Consequently, an accurate license plate recognition regardless of vehicle location and viewing angle is required. In this paper, we propose a novel license plate recognition system which exploits a) the format of license plates to remove false candidates of license plates and to extract characters in license plates and b) the characteristics of Hangul for accurate character recognition. In order to eliminate false candidates of license plates, the proposed method first aligns the candidates of license plates horizontally, and compares the position and the shape of objects in each candidate with the prior information of license plates provided by Korean Ministry of Construction & Transportation. The prior information such as aspect ratio, background color, projection image is also used to extract characters in license plates accurately applying an improved local binarization considering luminance variation of license plates. In case of recognizing Hangul in license plates, they are initially grouped according to their shape similarity. Then a super-class method, a hierarchical analysis based on key feature points is applied to recognize Hangul accurately. The proposed method was verified with high recognition rate regardless of background image, which eventually proves that the proposed LPR system has high performance regardless of the vehicle location or viewing angle.

• 전자공학회논문지 IE
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• v.44 no.1
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• pp.27-32
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• 2007

This study was to suggest the predictive model of propagation, considering the effect by the multipath waves produced by the sending and receiving vehicles' left/right reflectors and the adjacent vehicles when the communication between the vehicles on the one-way two-lanes road in the urban city with a lot of traffic jams. Then, the radius of curved road was 600[m], the length of curved roads $52.4\sim471.2[m]$, and the bridge's pier of road was $5o\sim45o$. Also, it was simulated by changing the receiving vehicle located on the curved road's gap from minimum 3.3[m] to maximum 29.5[m], corresponding to the change of distance of the bridge's pier of road and curved road. As a result of this research above, in case of $5o\sim15o$ bridge's pier of road, it was within l[dB] regardless of the receiving vehicle's position on the curved road in case of propagation path loss. In case of $15o\sim45o$, it was approximately $1\sim8[dB]$ as the bridge's pier of road is changed. And, in case of propagation path, it found out that it was changed to $0.4\sim120[m]$ according to the change of bridge's pier of road. Then, the delay time of propagation was 400[nsec] as it produced 120[m] in the difference of propagation path.

• Journal of the Korean Society for Railway
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• v.19 no.4
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• pp.456-467
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• 2016

Wireless Access in Vehicular Environments (WAVE) communication technology, which provides vehicleto-vehicle and vehicle-to-infrastructure communication and offers safe and convenient service, has been developed for application to an Intelligent Transport System (ITS). This paper provides field test results on a study of the feasibility of WAVE technology application to railway communication systems. A test railway communication system based on WAVE technology has been built along the Daebul line and a newly developed EMU. Field tests have been carried out according to the communication function requirements for LTE - R. The test results show that the railway communication system based on WAVE technology meets the functional requirements: maximum transmission length is 730m, maximum transfer delay is 5.69ms, and maximum interruption time is 1.36s; other tests including throughput test, video data transmission test, VoIP data test, and channel switching test also produced results that meets the functional requirements. These results suggest that WAVE technology can be applied to the railway communication system, enabling Vehicle-to-Wayside communication.

• Journal of Broadcast Engineering
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• v.27 no.6
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• pp.936-939
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• 2022

As air combat system technologies developed in recent years, the development of air defense systems is required. In the operating concept of the anti-aircraft defense system, selecting an appropriate armament for the target is one of the system's capabilities in efficiently responding to threats using limited anti-aircraft power. Much of the flying threat identification relies on the operator's visual identification. However, there are many limitations in visually discriminating a flying object maneuvering high speed from a distance. In addition, as the demand for unmanned and intelligent weapon systems on the modern battlefield increases, it is essential to develop a technology that automatically identifies and classifies the aircraft instead of the operator's visual identification. Although some examples of weapon system identification with deep learning-based models by collecting video data for tanks and warships have been presented, aerial vehicle identification is still lacking. Therefore, in this paper, we present a model for classifying fighters, helicopters, and drones using a convolutional neural network model and analyze the performance of the presented model.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.1
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• pp.6-11
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• 2011

This paper proposes a new collision risk assessment system for pedestrians's safety. Monte Carlo Simulation (MCS) method is a one of the most popular method that rely on repeated random sampling to compute their result, and this method is also proper to get the results when it is unfeasible or impossible to compute an exact result. Nevertheless its advantages, it spends much time to calculate the result of some situation, we apply not only MCS but also Neural Networks in this problem. By Monte carlo method, we make some sample data for input of neural networks and by using this data, neural networks can be trained for computing collision probability of whole area where can be measured by sensors. By using this trained networks, we can estimate the collision probability at each positions and velocities with high speed and low error rate. Computer simulations will be shown the validity of our proposed method.