• 전기의세계
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• v.22 no.1
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• pp.35-41
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• 1973

An automatic point traffic control method is recommended for more idealistic traffic flow over coarse road netowrks. The automatic control apparatus recommended, consists of a transceiver, amplifier, digital-to-analog converter, signal light controller for emergency and steady state, and digital counter as monitor. The transmitter sends a signal to the target vy means of Microwave-FM-CW and a diode detector picks up the echo signal. Thus the operation of the entire system will be carried out through an open loop state. Some factors necessary for an ideal detector system are rapid response, longevity and stability. An analytical method of the Doppler effect substitutes the conventional frequency deviation into the amplitude of detector output. The changing rate of amplitude is proportional to the voltage of the detector output. Some induced formula from Maxwell's radiation field theory ensures this new method, and, new method, and proves the fact with an experimental data presentation. Stability depends upon Klystron as an oscillator and a diode as a detector. the transceiver installation affects on the response and sensitivity of the system. In accordance with the detector output, several targets are easily classified by amplitudes on the scope. The traffic flow, i.e., target movement which is analyzed by the amplitude method, is shown through the scope and indicates it on the digital counter. The best efficiency for the amplitude analysis can be attained through use of an antenna having the highest sensitivity.

• ETRI Journal
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• v.41 no.5
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• pp.560-573
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• 2019

Two supervised learning algorithms, a basic neural network and a long short-term memory recurrent neural network, are applied to traffic including DDoS attacks. The joint effects of preprocessing methods and hyperparameters for machine learning on performance are investigated. Values representing attack characteristics are extracted from datasets and preprocessed by two methods. Binary classification and two optimizers are used. Some hyperparameters are obtained exhaustively for fast and accurate detection, while others are fixed with constants to account for performance and data characteristics. An experiment is performed via TensorFlow on three traffic datasets. Three scenarios are considered to investigate the effects of learning former traffic on sequential traffic analysis and the effects of learning one dataset on application to another dataset, and determine whether the algorithms can be used for recent attack traffic. Experimental results show that the used preprocessing methods, neural network architectures and hyperparameters, and the optimizers are appropriate for DDoS attack detection. The obtained results provide a criterion for the detection accuracy of attacks.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.3
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• pp.1-11
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• 2010

Traffic broadcasting is using a usual traffic information announcement when giving its information to users on the road and for the provision of information useful to drivers, a clear criteria of how to judge with information from informers needs to be established from the perspective of users. In this study, to give some available criteria for current announcement which often causes confusion, cognitive characteristics were investigated and analyzed based on judgment criteria which are commonly felt by correspondents, participants in traffic broadcasting and drivers. The result requires the provision of information that is relied on an average speed where drivers feel little cognitive difference and found a classification where a smooth traffic flow is more than 60km/h, going slow 40~60km/h and congested state less than 40km/h respectively. And from the study of 35 traffic information announcement for different traffic situations, 8 cases of smooth state and 9 cases of congested state were clearly classified but the rest 18 cases of comment were ambiguously perceived by drivers and which requires the necessity of a announcement that uses directly the word of 'smooth', 'slow', and 'congestion' in the actual expression of slow driving. The future study should be focused on the establishment of more definite criteria by representation of nearly real traffic flow, provision of traffic information announcement and the analysis of cognitive response through car dynamic simulators and the kinds.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.95-104
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• 2018

Using network betweenness centrality we attempt to analyze the characteristics of Seoul metropolitan subway lines. Betweenness centrality highlights the importance of a node as a transfer point between any pairs of nodes. This 'transfer' characteristic is obviously of paramount importance in transit systems. For betweenness centrality, both traditional betweenness centrality measure and weighted betweenness centrality measure which uses monthly passenger flow amount between two stations are used. By comparing traditional and weighted betweenness centrality measures of lines characteristics of passenger flow can be identified. We also investigated factors which affect betweenness centrality. It is the number of passenger who get on or get off that significantly affects betweenness centrality measures. Through correlation analysis of the number of passenger and betweenness centrality, it is found out that Seoul metropolitan subway system is well designed in terms of regional distribution of population. Four measures are proposed which represent the passenger flow characteristics. It is shown they do not follow Power-law distribution, which means passenger flow is relatively evenly distributed among stations. It has been shown that the passenger flow characteristics of subway networks in other foreign cities such as Beijing, Boston and San Franciso do follow power-law distribution, that is, pretty much biased passenger flow traffic characteristics. In this study we have also tried to answer why passenger traffic flow of Seoul metropolitan subway network is more homogeneous compared to that of Beijing.

• Journal of Korean Society of Transportation
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• v.29 no.4
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• pp.7-15
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• 2011

Emerged in early 1990s, so called 'Quick service' industry that provides faster delivery of small parcels than regular mail service accelerated use of motorcycles. As the economic grows, use of large bicycles (more than 250CC displacement) for leisure purpose has also rapidly increased. Traffic crash data clearly shows the increasing trend in motorcycle crashes. The ratio of motorcycle involved crashes out of total has increased from 5.7% in 2005 to 8.3% in 2008, and similar trend can be found in fatalities ratio as well. In this study, we assess the level of risk when motorcycles operate on motorways by analyzing traffic rule violation ratio, lane change behaviour, driving speed behaviors of motorcycles in Uninterrupted Traffic Flow Facilities and using PC-CRASH simulation we also calculate car shock impulses occurred when an accident happens. Analysis result shows that the motorcycle is different from the car in terms of lane change timing and average speed, and also shows motorcycle drivers tends to conduct more improper driving behavior particularly when traffic is congested. The results from this study could be usefully applied when the law enforcement agent decides whether bicycles shall be allowed to use motorways. The result could be also utilized as fundamental information for further study of bicycles' driving behavior.

• Journal of the Korean Society of Safety
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• v.30 no.6
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• pp.122-131
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• 2015

Recently, starting with the deep underground road construction plan in Seobu Expressway, Korea, there area many studies on deep underground roads to be newly built. However, there is an extreme lack of safety standards, which does not consider traffic conditions and road driving characteristics. Therefore, this study reviewed safety elements to reflect in the deep underground road planning by analyzing driving stability of longitudinal tunnels with road environments, which resemble deep underground roads. For comprehensive analysis, the characteristics and causes of the accidents that have occurred in seven longitudinal tunnels with a length of 2km or over in Gangwon area, were collected. Specifically, geometric structures and facilities of each tunnel were investigated. Also, the present state of facility installation and the changes in driving speed of vehicles passing through each tunnel were observed to analyze the causes for the traffic accidents in each tunnel and accident reduction alternatives. It was revealed that the most frequent accidents in the tunnels resulted from the changes of traffic flow due to the abrupt speed reduction of forward vehicles, or the failure in speed control of following vehicles during the traffic congestion situation. Moreover, installing facilities such as plane and longitudinal curves, median strips and marginal strips seem to induce consistent driving speed. These results mean that for accident prevention, speed management must be preceded and there is a need to develop and introduce safety facilities actively to control the driving flow of forward and following vehicles.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.4
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• pp.13-27
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• 2021

In this study, the impact of traffic flow on the market penetration rate of autonomous vehicles(AV) was analyzed using the data for the year 2020 of the Yongin IC~Yangji IC section of Yeongdong Expressway. For this analysis, a microscopic traffic simulation model VISSIM was utilized. To construct the longitudinal control of the AV, the Intelligent Driver Model(IDM) was built and applied, and the driving behavior was verified by comparison with a normal vehicle. An examination of the study results of mobility and safety according to the market penetration rate of the AV, showed that the network's mobility improves as the market penetration rate increases. However, from the point of view of safety, the network becomes unstable when normal vehicles and AVs are mixed, so there should be a focus on traffic management for ensuring safety in mixed traffic situations.

• Journal of Korean Port Research
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• v.14 no.1
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• pp.66-75
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• 2000

From the traffic analysis, and model constructions and verifications for speed prediction on the freeway ramp junctions with 70mph speed limit, the following results were obtained : ⅰ) The traffic flow distribution showed a big difference depending on the time periods. Especially, more traffic flows were concentrated on the freeway junctions in the morning peak period when compared with the afternoon peak period. ⅱ) The occupancy distribution was also shown to be varied by a big difference depending on the time periods. Especially, the occupancy in the morning peak period showed over 100% increase when compared with the 24hours average occupancy, and the occupancy in the afternoon peak period over 25% increase when compared with the same occupancy. ⅲ) The speed distribution was not shown to have a big difference depending on the time periods. Especially, the speed in the morning peak period showed 10mph decrease when compared with the 24hours'average speed, but the speed did not show a big difference in the afternoon peak period. ⅳ) The analyses of variance showed a high explanatory power between the speed predictive models(SPM) constructed and the variables used, especially the upstream speed. ⅴ) The analysis of correlation for verifying the speed predictive models(SPM) constructed on the ramp junctions were shown to have a high correlation between observed data and predicted data. Especially, the correlation coefficients showed over 0.95 excluding the unstable condition on the diverge section. ⅵ) Speed predictive models constructed were shown to have the better results than the HCM models, even if the speed limits on the freeway were different between the HCM models and speed predictive models constructed.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.1
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• pp.88-93
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• 2020

Recently, SDN technology is applied to real communication business, users are getting bigger, and as the amount of data flowing in the network increases, interest in network data flow management is increasing. During this process, it must be ensured that the confidentiality, integrity, availability, and traceability of the data on the network being transmitted. In addition, it is necessary to develop an environment for observing the flow of data in real time on a network required in various fields and visually confirming the control. In this paper, first, Mininet is applied to construct a network topology and various environment attributes. Second, we added OpenDayLight in Mininet environment to develop a simulation environment to visually check and control network traffic flow in network topology.

• Journal of Korean Society of Transportation
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• v.17 no.2
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• pp.179-191
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• 1999

To device effective freeway traffic flow control strategies and freeway traffic information dissemination strategies, it is very important to estimate real physical queue length on the freeway. Shock wave theory and queueing theory have limitation to be used to estimate the queue length. The primary objective of this study is to develop a reliable method for estimating the physical queue length and level of congestion. Queueing propagation processes were analysed by using such traffic data as main line traffic volume, ramp volume, density. speed, and physical queue length collected by video photographing on Olympic Freeway. As a result of analysis, it has been confirmed that the real queue length can be estimated by using the traffic counts arriving the congested region and passing a bottleneck location. Further more, a reliable method for estimating the level of congestion could be developed on the basis of real-time traffic counts.