• 한국통신학회논문지
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• 제33권5B호
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• pp.344-355
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• 2008

본 논문에서는 차등서비스 망의 성능 평가 문제를 다룬다. 성공적인 성능 평가를 위하여 적절한 트래픽 모델에 의하여 네트워크상의 실제 트래픽을 정확히 나타낼 수 있는 능력이 필수 요소이다. 실제 트래픽 측정의 성질에 대한 많은 연구 결과는 웹과 텔넷, P2P 트래픽을 포함하여 인터넷 트래픽에 대한 장기간-의존성을 증명하였다. 장기간 의존성은 자기유사성에 의하여 효과적으로 표현될 수 있다. 본 논문에서는 중첩된 On-Off 소스 모델, FFT-FGN 모델과 RMD 모델에 대한 특성 분석을 기반으로, 중첩된 On-Off 소스 모델을 이용하여 자기유사트래픽 발생기를 설계하고 구현한다. 생성된 트래픽의 자기유사성은 TCPdump 데이터의 패킷 도착 간격을 조사하여 확인하였다. 또한 구현된 트래픽 발생기를 차등서비스 망의 성능평가에 적용하여 On/Off 모델의 $\alpha$ 값에 대한 성능이 영향과, CBQ(Class-Based Queueing)에 의한 EF(Expedited Forwarding)/BE(Best Effort) 클래스 트래픽의 성능을 관찰한다.

• 한국항공운항학회지
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• 제22권3호
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• pp.8-14
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• 2014

Arrival management is a tool which provides efficient flow of traffic and reduces ATC workload by determining aircraft's sequence and schedules while they are in cruise phase. As a decision support tool, arrival management should advise on air traffic control service based on the understanding of human factor of its user, air traffic controller. This paper proposed a prediction model for air traffic controller sequencing strategy by analyzing the historical trajectory data. Statistical analysis is used to find how air traffic controller decides the sequence of aircraft based on the speed difference and the airspace entering time difference of aircraft. Logistic regression was applied for the proposed model and its performance was demonstrated through the comparison of the real operational data.

• 한국전자통신학회논문지
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• 제17권1호
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• pp.105-110
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• 2022

교통 표지 인식은 교통 관련 문제를 해결하는 데 중요한 역할을 한다. 교통 표지 인식 및 분류 시스템은 교통안전, 교통 모니터링, 자율주행 서비스 및 자율주행 차의 핵심 구성 요소이다. 휴대용 장치에 적용할 수 있는 경량 모델은 설계 의제의 필수 측면이다. 우리는 교통 표지 인식 시스템을 위한 잔여 블록이 있는 경량 합성곱 신경망 모델을 제안한다. 제안된 모델은 공개적으로 사용 가능한 벤치마크 데이터에서 매우 경쟁력 있는 결과를 보여준다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권9호
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• pp.3598-3614
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• 2020

With the increase of motor vehicles and tourism demand, some traffic problems gradually appear, such as traffic congestion, safety accidents and insufficient allocation of traffic resources. Facing these challenges, a model of Spatio-Temporal Dilated Convolutional Network (STDGCN) is proposed for assistance of extracting highly nonlinear and complex characteristics to accurately predict the future traffic flow. In particular, we model the traffic as undirected graphs, on which graph convolutions are built to extract spatial feature informations. Furthermore, a dilated convolution is deployed into graph convolution for capturing multi-scale contextual messages. The proposed STDGCN integrates the dilated convolution into the graph convolution, which realizes the extraction of the spatial and temporal characteristics of traffic flow data, as well as features of road occupancy. To observe the performance of the proposed model, we compare with it with four rivals. We also employ four indicators for evaluation. The experimental results show STDGCN's effectiveness. The prediction accuracy is improved by 17% in comparison with the traditional prediction methods on various real-world traffic datasets.

• Wind and Structures
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• 제24권3호
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• pp.287-306
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• 2017

In the present study, a new assessment simulation of ride safety based on a new wind-traffic-pavement-bridge coupled vibration system is developed considering stochastic characteristics of traffic flow and bridge surface. Compared to existing simulation models, the new assessment simulation focuses on introducing the more realistic three-dimensional vehicle model, stochastic characteristics of traffic, vehicle accident criteria, and bridge surface conditions. A three-dimensional vehicle model with 24 degrees-of-freedoms (DOFs) is presented. A cellular automaton (CA) model and the surface roughness are introduced. The bridge deck pavement is modeled as a boundless Euler-Bernoulli beam supported on the Kelvin model. The wind-traffic-pavement-bridge coupled equations are established by combining the equations of both the vehicles in traffic, pavement, and bridge using the displacement and interaction force relationship at the patch contact. The numerical simulation shows that the proposed method can simulate rationally useful assessment and prevention information for traffic, and define appropriate safe driving speed limits for vulnerable vehicles under normal traffic and bridge surface conditions.

• 대한산업공학회지
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• 제23권1호
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• pp.23-37
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• 1997

In this paper, performance analysis of video traffic shaper for Motion Picture Experts Group (MPEG) video traffic in on ATM network are investigated. Traffic shaping for MPEG video traffic is proposed as a traffic control function in ATM networks. The proposed shaper smoothes video traffics by controling the output rate of the buffer, which is placed in an MPEG source, according to I,B,P frame sequences of MPEG. In performance analysis of an video traffic shaper, a periodic botch arrival model is suggested to describe cell streams in a frame of MPEG video traffic. The queueing model which has periodic independent botch arrival and periodic deterministic service time is used to obtain the cell loss ratio, the mean cell delay, and the measure of smoothing effect. Simulation results are used to validate this queueing model. The cell loss performance of ATM multiplexer is measured by simulation study with real MPEG-1 data. From the viewpoint of traffic load, the cell loss ratio is observed to be considerably high, which is considered to result from the burstiness of MPEG video traffic. As a result, it is shown that the shaping decreases cell loss ratio of multiplexer. The results of this paper can be employed to establish a basic guideline in the implementation of a traffic control scheme and the design of ATM multiplexer for MPEG video traffic.

• 대한교통학회:학술대회논문집
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• 대한교통학회 1995년도 제27회 학술발표회
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• pp.84-98
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• 1995

Network-based model were developed to predict short term future traffic volume based on current traffic, historical average, and upstream traffic. It is presumed that upstream traffic volume can be used to predict the downstream traffic in a specific time period. Three models were developed for traffic flow prediction; a combination of historical average and upstream traffic, a combination of current traffic and upstream traffic, and a combination of all three variables. The three models were evaluated using regression analysis. The third model is found to provide the best prediction for the analyzed data. In order to balance the variables appropriately according to the present traffic condition, a heuristic adaptive weighting system is devised based on the relationships between the beginning period of prediction and the previous periods. The developed models were applied to 15-minute freeway data obtained by regular induction loop detectors. The prediction models were shown to be capable of producing reliable and accurate forecasts under congested traffic condition. The prediction systems perform better in the 15-minute range than in the ranges of 30-to 45-minute. It is also found that the combined models usually produce more consistent forecasts than the historical average.

• 응용통계연구
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• 제21권6호
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• pp.1037-1044
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• 2008

본 연구에서는 재무시계얼 자료의 변동성을 분석하는데 유용하게 쓰이는 멱변환 시계열 모형을 인터넷 트래픽 자료 특성 분석에 적용하여 효용성을 보이고자 한다. 트래픽의 특성인 장기기억(long memory)특성을 설명하기 위하여 멱변환 GARCH(PGARCH) 모형을 소개하고 기존의 GARCH 모형보다 더 유용함을 시뮬레이션과 실제 인터넷 트래픽 자료에 적합시켜 입증하였다.

• 한국정보시스템학회지:정보시스템연구
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• 제26권3호
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• pp.171-185
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• 2017

Purpose Recently, there has been an increase in attempts to analyze social phenomena, consumption trends, and consumption behavior through a vast amount of customer data such as web search traffic information and social buzz information in various fields such as flu prediction and real estate price prediction. Internet portal service providers such as google and naver are disclosing web search traffic information of online users as services such as google trends and naver trends. Academic and industry are paying attention to research on information search behavior and utilization of online users based on the web search traffic information. Although there are many studies predicting social phenomena, consumption trends, political polls, etc. based on web search traffic information, it is hard to find the research to explain and predict tourism demand and establish tourism policy using it. In this study, we try to use web search traffic information to explain the tourism demand for major cities in Gangwon-do, the representative tourist area in Korea, and to develop a nowcasting model for the demand. Design/methodology/approach In the first step, the literature review on travel demand and web search traffic was conducted in parallel in two directions. In the second stage, we conducted a qualitative research to confirm the information retrieval behavior of the traveler. In the next step, we extracted the representative tourist cities of Gangwon-do and confirmed which keywords were used for the search. In the fourth step, we collected tourist demand data to be used as a dependent variable and collected web search traffic information of each keyword to be used as an independent variable. In the fifth step, we set up a time series benchmark model, and added the web search traffic information to this model to confirm whether the prediction model improved. In the last stage, we analyze the prediction models that are finally selected as optimal and confirm whether the influence of the keywords on the prediction of travel demand. Findings This study has developed a tourism demand forecasting model of Gangwon-do, a representative tourist destination in Korea, by expanding and applying web search traffic information to tourism demand forecasting. We compared the existing time series model with the benchmarking model and confirmed the superiority of the proposed model. In addition, this study also confirms that web search traffic information has a positive correlation with travel demand and precedes it by one or two months, thereby asserting its suitability as a prediction model. Furthermore, by deriving search keywords that have a significant effect on tourism demand forecast for each city, representative characteristics of each region can be selected.

• 대한교통학회지
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• 제31권4호
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• pp.3-17
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• 2013

본 연구는 대규모 교통망에서 통행배정시 신호교차로에 의한 지체를 반영한 통행배정을 수행하여 보다 현실 모사가 가능한 통행배정기법을 개발 하는 것이다. 실제로 도시부나 단속류에서 발생하는 통행시간 및 비용의 증가 원인은 많은 부분이 교차로 지체에 의한 정지 혹은 혼잡에 의해 발생함에도 불구하고 기존의 통행배정 모형은 이를 반영하지 못하고 있었다. 본 연구에서 개발한 신호교차로 지체 반영 통행배정 모형은 기존의 통행배정모형과 한국도로 용량편람의 신호교차로 지체 산정 방법을 결합하여 구축하였다. 다양한 모의실험을 통해 이 모형이 실제 가로망에 적용이 가능한 모형임을 보였다. 따라서 본 모형은 대규모 지역에서의 교통정책 및 교통시설의 변화 등에 교차로 지체를 적용하여 분석할 수 있을 것으로 판단된다.