• Journal of Korean Society for Geospatial Information Science
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• v.12 no.4 s.31
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• pp.53-60
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• 2004

Congestion index is needed for quantifying congestion level for various areas. So far, the index has been calculated based on multiple vehicle data for specified time interval. Such being the case, it was costly to build it and the usage of it was focused on policy development and evaluation rather than on traffic information provision. This study focuses on a development on a single vehicle based congestion index which can be a representative value for link congestion level and link speed information at the same time for dual purposes of traditional usages and information provision. A new term has been added for representing real time based arterial congestion level and it has been verified on a real time basis. The index was based on single vehicle GPS data and seemed to be cost effective in deriving the index. With the help of the index, the traffic information contents can be diversified in a constructive way in providing real time traffic information for ITS area and in using congestion level determination for traditional transportation areas.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.6
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• pp.15-22
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• 2012

A performance index of singalized intersections is a standard to optimize signal control variables and to manage traffic flow. Traffic delays is generally used to minimize the average delay time on intersections or networks, progression efficiency is used to improve travel speed of main cooridors or to provide transit signal priority. We manage traffic flows with only selecting one index between delays and progression according to the objective of traffic management and field characteristics. In real field, the driver's satisfaction is high in any performance criteria when the waiting time is shorter and the unnecessary stop in front of traffic is smaller. This paper aims to develop simulation model to represent real progression with concurrently considering delays and progression. In order to reflect an effect of level of traffic volumes and residual queues which don't be considered in prior progression model, we apply shockwave model with flow-density diagram. We derive Cell Transmission Model of Daganzo in order to develop the delay index and the progression index for the macroscopic simulation model. In order to validate the effect, we analysis traffic delays and progression efficiency with comparing this model to Transyt-7F and PASSER V.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.4D
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• pp.291-303
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• 2012

In order to lead safe driving, it is better to provide dynamic and detailed information on how the driver using the relevant road should behave as concerning movements of individual car rather than providing monotone and static information of reducing of speed to unspecified drivers. Assuming road and communication of highway where real-time collection and transfer of information on vehicles and road traffic status is possible, the purpose of this study was to provide real-time safe distance by considering road traffic condition such as road condition and driving condition, travel speed and distance between preceding/following vehicles. We intended to provide basic information about dangerous situation by defining different values of condition based column ($C_{condition}$) in accordance with the road surface condition, based on which Real-time Safety Distance Index(RSDI) is to be calculated comprehensively reflecting speed of preceding and following vehicles, distance between vehicles, vertical alignment and road surface condition on the scope of expression column ($C_n$). We intended to enable the driver to secure safety by providing the calculated Real-time Safety Distance Index (RSDI) so that the driver can intuitively sense and sufficiently cope with a dangerous situation where collision of vehicles may occur. The calculated RSDI value is comprised of 30 unit columns and will be provided to the driver being divided into risk evaluation grades of 3 predetermined steps, 'warning', 'dangerous' and 'normal'.

• Journal of Korea Multimedia Society
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• v.16 no.5
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• pp.610-618
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• 2013

The damaged district by flooding has been changed from mainly farmland to cities due to the weather phenomena which is different from the past. This has caused not only irreparable damage of people's lives and property but social infrastructures. There also exist serious damages such as isolation of drivers and traffic jam as the roads were flooded. In this study, we suggested a method to develop a flood risk index focused on not Si, Gun or Gu but roads. In addition, flood risk index in the roads just at the moment, when it rains quantitatively, will be provided by using real-time rainfall information provided by the Weather Center. Then it should be helpful to prevent people from being isolated by flooded roads in advance.

• International Journal of Highway Engineering
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• v.9 no.3
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• pp.21-28
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• 2007

We suggest a new spatial linear interpolation method to substitute linear interpolation method which widely used in transportation engineering to impute the missing daily traffic volume. We layout daily traffic volume which is time series data over the virtual lattice space to consider the spatial correlation. We used Moran Index to evaluate the spatial correlations among daily traffic volume in same week and same date traffic volume by week considering the circularity of daily traffic volume. For real application, we used daily traffic volume on November, 2004 provided by Korea Institute of Construction Technology(KICT) and transformed daily traffic volume to 4 times 7 virtual lattice space to reflect the spatial correlation. Finally we showed that the spatial linear interpolation method has good performance for missing data imputation based on MAPE, RMSE, and Theil's U criteria.

• Journal of Korean Society of Transportation
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• v.25 no.5
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• pp.173-182
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• 2007

An innovative feature of this study is to propose a methodology for evaluating safety performance in real time based on vehicle trajectory data extracted from video images. The essence of evaluating safety performance is to capture unsafe car-following events between individual vehicles traveling surveillance area. The proposed methodology applied two indices including real-time safety index (RSI) based on the concept of safe stopping distance and time-to-collision (TTC) to the evaluation of safety performance. It is believed that outcomes would be greatly utilized in developing a new generation of video images processing (VIP) based traffic detection systems capable of producing safety performance measurements. Relevant technical challenges for such detection systems are also discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3771-3792
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• 2021

With the rapid development of science and technology, several high-performance networks have emerged with various new applications. Consequently, financially or socially motivated attacks on specific networks have also steadily become more complicated and sophisticated. To reduce the damage caused by such attacks, administration of network traffic flow in real-time and precise analysis of past attack traffic have become imperative. Although various traffic analysis methods have been studied recently, they continue to suffer from performance limitations and are generally too complicated to apply in existing systems. To address this problem, we propose a method to calculate the correlation between the malicious and normal flows and classify attack traffics based on the corresponding correlation values. In order to evaluate the performance of the proposed method, we conducted several experiments using examples of real malicious traffic and normal traffic. The evaluation was performed with respect to three metrics: recall, precision, and f-measure. The experimental results verified high performance of the proposed method with respect to first two metrics.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.362-364
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• 2018

Predicting network traffic volume has become a popular topic recently due to its support in many situations such as detecting abnormal network activities and provisioning network services. Especially, predicting the volume of the next upcoming traffic from the series of observed recent traffic volume is an interesting and challenging problem. In past, various techniques are researched by using time series forecasting methods such as moving averaging and exponential smoothing. In this paper, we propose a long short-term memory neural network (LSTM) based network traffic volume prediction method. The proposed method employs the changing rate of observed traffic volume, the corresponding time window index, and a seasonality factor indicating the changing trend as input features, and predicts the upcoming network traffic. The experiment results with real datasets proves that our proposed method works better than other time series forecasting methods in predicting upcoming network traffic.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.51-62
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• 2008

An innovative feature of this study is to propose a methodology for evaluating safety performance in real time based on vehicle trajectory data extracted from video images. The essence of evaluating safety performance is to capture unsafe car-following and lane-changing events generated by individual vehicles traveling within video surveillance area. The proposed methodology derived three indices including real-time safety index(RSI) based on the concept of safe stopping distance, time-to-collision(TTC), and the collision energy based on the conservation of momentum. It is believed that outcomes would be greatly utilized in developing a new generation of video images processing(VIP) based traffic detection systems capable of producing safety performance measurements. Relevant technical challenges for such detection systems are also discussed.

• Convergence Security Journal
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• v.6 no.4
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• pp.67-73
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• 2006

The method which research a standardization from real time cyber threat is finding the suspicious indication above the attack against cyber space include internet worm, virus and hacking using analysis the event of each security system through correlation with the critical point, and draft a general standardization plan through statistical analysis of this evaluation result. It means that becomes the basis which constructs the effective cyber attack response system. Especially at the time of security accident occurrence, It overcomes the problem of existing security system through a definition of the event of security system and traffic volume and a concretize of database input method, and propose the standardization plan which is the cornerstone real time response and early warning system. a general standardization plan of this paper summarizes that put out of threat index, threat rating through adding this index and the package of early warning process, output a basis of cyber threat index calculation.