• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.211-218
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• 2021

A recent spread of personal mobility devices such as electric kickboards has brought about a rapid increase in accident cases. Such vehicles are susceptible to falling accidents due to their low dynamic stability and lack of outer protection chassis. This paper presents the development of an automatic emergency braking system and a safe starting system as driving assistance devices for electric kickboards. The braking system employed artificial intelligence to detect nearby threaening objects. The starting system was developed to disable powder to the motor until when the driver's boarding is confirmed. This study is meaningful in that it proposes the convergence technology of advanced driver assistance systems specialized for personal mobility devices.

• Journal of Advanced Navigation Technology
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• v.25 no.3
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• pp.203-210
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• 2021

In many metropolitan cities around the world, ground and underground transportation networks are saturated due to urbanization. In addition, regulations on carbon emissions to prevent global warming are becoming stricter, and eVTOL, which will be operating in complex cities, is gaining popularity as the next generation of eco-friendly transportation. In this study, the hover lift efficiency and disc loading of eVTOLs for each type were calculated by classifying eVTOLs into following types: multicopter, lift+cruise, and vectored thrust. In addition, using the aerodynamic analysis programs OpenVSP, Fluent and Javaprop, the specific battery energy required for the smooth operation of eVTOL, which will be realized in the near future, was calculated and analyzed base on reports published by Uber and airworthiness authorities of each country.

• Convergence Security Journal
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• v.12 no.1
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• pp.27-33
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• 2012

VANET(Vehicular Ad-hoc Network) is a kind of ad hoc networks consist of intelligence vehicular ad nodes, and has become a hot emerging research project in many fields. It provide traffic safety, cooperative driving and etc. but has also some security problems that can be occurred in general ad hoc networks. Also, in VANET, vehiculars sho uld be able to authenticate each other to securely communicate with network-based infrastructure, and their location s and identifiers should not be exposed from the communication messages. This paper explains V2I authentication pr otocol using a hash function that preserves the user privacy. In addition, we analyze the security stability of the V2I authentication protocol using Casper in the formal verification technique. As a result, V2I authentication protocol us ing hash function prove a stability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.2
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• pp.344-352
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• 2003

An effective algorithm for implementation of which detects moving object from image sequences. predicts the direction of it. and drives the camera in real time is proposed. In static camera, for robust motion detection from a dynamic background scene, the proposed algorithm performs statistical modeling of moving objects and background, and trains the statistical modeling of moving objects and background, and trains the statistical feature of background with the initial parts of sequence which have no moving objects. Active camera moving objects are segmented by following procedure, an improved order adaptive lattice structured linear predictor is used. The proposed algorithm shows robust object tracking results in the environment of static or active camera. It can be used for the unmanned surveillance system, traffic monitoring system, and autonomous vehicle.

• Convergence Security Journal
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• v.11 no.6
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• pp.37-44
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• 2011

VANET(Vehicular Ad-hoc Network) is a kind of ad hoc networks consist of intelligence vehicular ad nodes, and has become a hot emerging research project in many field. It provide traffic safety, cooperative driving and etc. but has also some security problems that can be occurred in general ad hoc networks. Also, in VANET, vehicles shoul d be able to authenticate each other to securely communicate with network-based infrastructure, and their locations and identifiers should not be exposed from the communication messages. This paper proposes V2I(Vehicular to Infra structure) authentication protocol that anonymity and untraceability of vehicular using Error Correcting Code that ge nerate encoding certification using generation matrix. The proposed scheme based on ECC resolves overhead problems of vehicular secure key management of KDC.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.11a
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• pp.143-144
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• 2023

해양수산부가 구축한 초고속 해상무선통신망(LTE-Maritime)은 연안으로부터 최대 100km 해역을 항해하는 선박들에게 지능형 해상교통정보서비스(e-Nav)를 제공하기 위한 기반 통신 인프라다. 선박에서 e-Nav 서비스를 제공받기 위해 LTE-M. 무선설비는 선내 고정 설치되어 유선으로 연결된 표시장치와 연동이 필요하다. 이는 공간이 협소하고 밀폐된 소형선박에 설치의 어려움뿐 아니라 선내 센서를 비롯한 다양한 IoT 기기 등과의 연결성에 제약을 줄 수 있다. 또한 선박이 육상의 LTE-M. 기지국과 멀리 떨어질 경우, 다운링크에 비해 업링크 통신품질이 상대적으로 취약해져 긴급 조난 신호를 비롯한 위험상황의 전달에 문제가 발생될 수 있다. 본 연구에서는 LTE-M. 망의 무선설비 다각화 사업으로 추진·개발된 소형선용 WiFi 및 업링크 향상용 무선설비의 실해역 성능 시험 방안을 고찰하여, 선내 WiFi 무선 품질을 평가하기 위한 성능 지표를 비롯해 업링크 통신속도 개선 등을 확인하기 위한 상호운용성 성능 시험 방안을 제시하고자 한다.

• Journal of Advanced Navigation Technology
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• v.10 no.4
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• pp.394-399
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• 2006

In this paper, we investigated performance for 5.8GHz dedicated short range communication system using OFDM which will be applied to Intelligent transportation system services. The maximum speed of a vehicle in DSRC channel is very fast as 180km/h, so a service time is very short to serve a various traffic information if hand-off is not occurred. Therefore higher bit rate is required to proved advanced and intelligent service to the drivers of various vehicle and the data transmission rate of the next generation DSRC system if being promoted over 10Mbps. The signals received in Clarke & Gans channel have been simulated using the computer simulator.

• Journal of Internet Computing and Services
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• v.11 no.4
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• pp.59-72
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• 2010

WIM(Weigh-In-Motion) is the system measuring the weight of the vehicle with a high-speed. In the existing WIM system, vehicle weight is measured based on the constant speed and the error ratio has 10%. However, because of measuring the driving pattern, that is abnormal driving pattern which is like the acceleration and down-shift of the drivers, it has the error ratio which is bigger than the real. In order to it reduces the error ratio of WIM system, the improved WIM system needs to find the abnormal driving pattern. In order to reducing the error ratio of these WIM systems, the improved WIM system can find abnormal driving patterns. In this paper, the improved WIM system which analyzes the abnormality driving pattern influencing on the error ratio of WIM system of an existing and minimizes the error span is designed. The improved WIM system has the multi step loop structure of adding the loop sensor to an existing system. In addition, the measure function defined as an intrinsic is improved and the weight measured by the abnormal driving pattern is amended. The analysis of experiment result improved WIM system can know the fact that the error span reduces by 8% less than in the existing the maximum average sampling error 22.98%.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.29-35
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• 2021

License plate recognition plays a key role in intelligent transportation systems. Therefore, it is a very important process to efficiently detect the number and character areas. In this paper, we propose a method to effectively detect license plate number area by applying deep learning and semantic image segmentation algorithm. The proposed method is an algorithm that detects number and text areas directly from the license plate without preprocessing such as pixel projection. The license plate image was acquired from a fixed camera installed on the road, and was used in various real situations taking into account both weather and lighting changes. The input images was normalized to reduce the color change, and the deep learning neural networks used in the experiment were Vgg16, Vgg19, ResNet18, and ResNet50. To examine the performance of the proposed method, we experimented with 500 license plate images. 300 sheets were used for learning and 200 sheets were used for testing. As a result of computer simulation, it was the best when using ResNet50, and 95.77% accuracy was obtained.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.1 no.1
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• pp.41-51
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• 2002

As Advanced Traveler Information System(ATIS) is the kernel of the Intelligent Transportation System, it is very important how to manage data from traffic information collectors on a road and have at borough grip of the travel time's change quickly and exactly for doing its part. Link travel time can be obtained by two method. One is measured by area detection systems and the other is estimated by point detection systems. Measured travel time by area detection systems has the limitation for real time information because it Is calculated by the probe which has already passed through the link. Estimated travel time by point detection systems is calculated by the data on the same time of each. section, this is, it use the characteristic of the various cars of each section to estimate travel time. For this reason, it has the difference with real travel time. In this study, Artificial Neural Networks is used for estimating link travel time concerned about the relationship with vehicle detector data and link travel time. The method of estimating link travel time are classified according to the kind of input data and the Absolute value of error between the estimated and the real are distributed within 5$\~$15minute over 90 percent with the result of testing the method using the vehicle detector data and AVI data of Namsan Tunnel $\#$1. It also reduces Time lag of the information offered time and draws late delay generation and dissolution.