• Proceedings of the Korean Information Science Society Conference
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• 2007.06d
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• pp.285-289
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• 2007

IEEE 802.11 프로토콜은 근거리 네트워크인 LAN(Local Area Network)을 대상으로 한다. 네트워크를 구성하는 하나의 BSS(Basic Service Set)는 보통 제한된 규모의 크기를 가지며 그 안에 속한 스테이션(station)의 수는 수십 개 내외로 가정한다. 하지만 지능형 교통 시스템과 같은 대규모의 네트워크에서 하나의 AP(Access Point)가 담당하는 BSS의 크기는 수 Km에 달하며 그 안에 속한 스테이션의 수도 수백개에 달한다. 이러한 고속 이동성과 대규모의 스테이션 수를 특징으로 하는 네트워크를 지원하기 위해 기존의 802.11 프로토콜은 적합하지 않다. 본 논문에서는 대규모 고속 이동 스테이션들이 존재하는 네트워크를 지원할 수 있는 802.11 기반의 그룹화 메커니즘을 제안한다. 하나의 BSS 내에서 경쟁하는 스테이션의 수를 그룹화 하여 경쟁의 정도를 완화함으로써 성능을 개선한다. 기존의 802.11 프로토콜 성능을 수학적 모델로 평가하였던 [1]과 제안한 그룹화 메커니즘을 도입하였을 경우의 성능을 수학적으로 비교 분석한 결과 그룹화를 통해 최대 187%의 성능 향상을 가져올 수 있음을 보였다.

• Journal of IKEEE
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• v.22 no.4
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• pp.1099-1103
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• 2018

Platooning of vehicles is an efficient traffic management model that improves traffic flow and fuel consumption. Especially, it is necessary to reduce computational load and networking overhead in automated connected vehicle systems. Because it is important to maintain the size of the platoon group appropriately for efficient platoon operation, this study proposed a dynamic grouping scheme for platooning in an automated vehicle system. The proposed scheme is analyzed by a mathematical model based on Markov chain. From the performance evaluation, it was confirmed that the proposed scheme appropriately controls the size of the platoon group.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.145-146
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• 2021

본 연구에서는 카메라의 촬영 시점에 의해서 발생되는 원근감이 광학 흐름 생성에 어떠한 영향을 주는지 살펴보고 광학 흐름 기반 이상행동 탐지 솔루션의 성능을 고도화하기 위해 기존 광학 흐름 영상으로부터 소실점 기반 가중치 행렬을 계산하여 원근감에 따른 광학 흐름 정도를 평활하는 기법에 대해서 연구한다. 카메라의 뷰포인트에 따라 원근감의 발생 정도나 객체의 크기 및 움직임의 정도가 달라지게 되며, 이는 원본 영상 프레임을 광학 흐름의 크기와 방향성으로 표현하는 영상 변환 네트워크를 가진 생성적 적대 신경망을 학습할 때 정상적인 행동 패턴의 범위를 결정짓는 데 방해가 될 수 있다. 이러한 문제를 해결하기 위하여 데이터셋의 배경으로부터 소실점을 추출하고 원근감에 따라 결정되는 광학 흐름의 크기를 평활하는 기법을 개발하여 기존 모델의 성능과 비교하였으며, 프레임 단위의 정확도 성능이 5.75% 향상된 것으로 확인되었다.

• Journal of Korean Society of Transportation
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• v.17 no.4
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• pp.71-84
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• 1999

The purpose of this study is to construct a dynamic traffic analysis model using the existing traffic flow theory in order to develope a dynamic traffic assignment technique. In this study the dynamic traffic analysis model was constructed using Daganzo's CELL TRANSMISSION THEORY which was considered more suitable to dynamic traffic assignment than the other traffic flow theories. We developed newly the diverging split module, the cost update module and the link cost function and defined the maximum waiting time decision function that Daganzo haven't defined certainly at his Papers. The output that resulted from the simulation of the dynamic traffic analysis model with test network I and II was shown at some tables and figures, and the analysis of the bottleneck and the HOV lane theory showed realistic outputs. Especially, the result of traffic assignment using the model doesn't show equilibrium status every time slice but showed that the average travel cost of every path maintains similarly in every time slice. It is considered that this model can be used at the highway operation and the analysis of traffic characteristics at a diverging section and the analysis of the HOV lane effect.

• Journal of the Korean Society of Hazard Mitigation
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• v.6 no.2 s.21
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• pp.25-35
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• 2006

Recently seismic fragility analysis method has been widely used for the seismic probabilistic risk assessment of infrastructures such as nuclear power plants, buildings and bridges because of its probabilistic characteristics. Furthermore, this technique has been applied to large-scale social systems consisted of each infrastructures by combing GIS. In this paper, the applicability of this technique to domestic infrastructural systems was studied. The transportation network was selected as one of these domestic infrastructural systems. Example studies were peformed about Changwon city. Nonlinear time history analysis, with a maximal likelihood approach were conducted to establish the fragility curves of each infrastrucures (bridges). GIS analysis was also applied to the analysis of whole infrastructural systems. The results show that it is very useful to predict seismic probabilistic risk assessment of this domestic transportation network. However, it also shows that further studies such as more suitable damage criterion to domestic structure and precise nonlinear analysis techniques should be developed to predict more precise results.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.2
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• pp.321-327
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• 2023

With the development of artificial intelligence, the prediction system has become one of the essential technologies in our lives. Despite the growth of these technologies, traffic congestion at intersections in the 21st century has continued to be a problem. This paper proposes a system that predicts intersection traffic jams using a Convolutional LSTM (Conv-LSTM) algorithm. The proposed system models data obtained by learning traffic information by time zone at the intersection where traffic congestion occurs. Traffic congestion is predicted with traffic volume data recorded over time. Based on the predicted result, the intersection traffic signal is controlled and maintained at a constant traffic volume. Road congestion data was defined using VDS sensors, and each intersection was configured with a Conv-LSTM algorithm-based network system to facilitate traffic.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2779-2784
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• 2015

The prediction of the accurate traffic information can provide an optimal route from the place of departure to a destination, therefore, this makes it possible to obtain a saving of time and money. To predict traffic information, we use a Bayesian network method based on probability model in this paper. Existing researches predicting the traffic information based on a Bayesian network generally used to study the data for all time. In this paper, however, only data corresponding to same time and day of the week to predict selectively will be used for learning. In fact, the experiment was carried out for 14 links zone in Seoul, also, the accuracy of the prediction results of the two different methods should be tested with MAPE (Mean Absolute Percentage Error) which is commonly used. In view of MAPE, experimental results show that the proposed method may calculate traffic prediction value with a higher accuracy than the method used to learn the data for all time zones.

• Electronics and Telecommunications Trends
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• v.26 no.5
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• pp.112-122
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• 2011

CPS(Cyber-Physical Systems)는 고수준의 신뢰성을 기반으로 네트워크를 통해 물리 시스템을 실시간 제어하기 위한 임베디드 시스템이며 무인 주차, 항공, 스마트 그리드와 같이 다양한 의료, 군사, 교통, 로봇제어 분야에 활용 가능한 기술이다. 이러한 환경에서 시스템들 간의 실시간적이고 신뢰성 높은 데이터 통신을 제공하기 위하여 발행/구독 모델에 기반한 실시간 데이터 통신 미들웨어 표준인 DDS(Data Distribution Service)를 사용한다. 그러나, DDS는 임베디드 기기 또는 모바일 기기들이 동적으로 구성된 네트워크에 자유로운 참여, 탈퇴가 가능한 상황에서 실시간 데이터 통신에는 적합하지만 전송되는 데이터 도청, 재전송 등과 같은 다양한 네트워크 공격에는 취약하다. 따라서, 본 고에서는 DDS 보안상의 취약점과 보안강화를 위한 접근 방법에 대해 기술하고, 이후에 DDS 통신채널 보호를 위한 상용제품의 접근법과 안전 통신채널 제공을 위한 멀티캐스트 인증, 암호화에 관련된 접근방법에 대해 기술한다.

• Journal of Korean Society of Transportation
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• v.22 no.5
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• pp.123-137
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• 2004

The study on traffic assignment is actively being performed which reflect networks status using time. Its background is increasing social needs to use traffic assignment models in not only hardware area of road network plan but also software area of traffic management or control. In addition, multi-class traffic assignment model is receiving study in order to fill a gap between theory and practice of traffic assignment model. This model is made up of two, one of which is multi-driver class and the other multi-vehicle class. The latter is the more realistic because it can be combined with dynamic model. On this background, this study is to build multidynamic model combining the above-mentioned two areas. This has been a theoretic pillar of ITS in which dynamic user equilibrium assignment model is now made an issue, therefore more realistic dynamic model is expected to be built by combining it with multi-class model. In case of multi-vehicle, FIFO would be violated which is necessary to build the dynamic assignment model. This means that it is impossible to build multi-vehicle dynamic model with the existing dynamic assignment modelling method built under the conditions of FIFO. This study builds dynamic network model which could relieve the FIFO conditions. At the same time, simulation method, one of the existing network loading method, is modified to be applied to this study. Also, as a solution(algorithm) area, time dependent shortest path algorithm which has been modified from existing shortest path algorithm and the existing MSA modified algorithm are built. The convergence of the algorithm is examined which is built by calculating dynamic user equilibrium solution adopting the model and algorithm and grid network.

• Journal of Korean Society of Transportation
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• v.27 no.3
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• pp.81-90
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• 2009

The safety management of a road network comprises four basic inter-related components：identification of sites(black spot) requiring safety investigation, diagnosis of safety problems, selection of feasible treatments for potential treatment candidates, and prioritization of treatments given limited budgets(Persaud, 2001). Identification process of selecting black spot is very important for efficient investigation of sites. In this study, the accident prediction model for EB method was developed by using accident data and geometric conditions of black spots selected from four-leg signalized intersections in In-cheon City for three years (2004-2006). In addition, by comparing the rank nomination technique using EB method to that by using accident counts, we managed to show the problems which the existing method have and the necessity for developing rational prediction model. As a result, in terms of total number of accidents, both the counts predicted by existing non-linear regression model and that by EB method have high good of fitness, but EB method, considering both the accident counts by sites and total number of accident, has better good of fitness than non-linear poison model. According to the result of the comparison of ranks nominated for treatment between two methods, the rank for treatment of almost sites does not change but SeoHae intersection and a few other intersections have significant changes in their rank. This shows that, with the technique proposed in the study, the RTM problem caused by using real accident counts can be overcome.