• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.57-71
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• 2009

Due to increasing interest in dispersion of traffic flows through providing traffic information, there has been much research of driver behavior and effectiveness of diversion. In this paper the authors intend to analyze how a diversion was determined and its effects through correlation analysis between diversion rates estimated by actual surveys and the traffic conditions. Through speed-flow analysis, the diversion mechanism was found. When travel speed decreased, detour volume increased. Then when the traffic volume was decreased through an increase of diversion and traffic conditions got better, the detour volume decreased again. In addition, the authors found negative correlation between the diversion rate and travel speed through correlation analysis. It shows that there were various relationships between diversion rates and traffic conditions according to congestion level and direction of traffic. Finally, it is suggested that the regression equation for calculating the diversion rate with the traffic flows, travel speed, and travel time as variables has a coefficient of determination of 38.5%. It means that traffic conditions on expressways take about 40% of driver's decision-making for diversion.

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.1
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• pp.33-41
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• 2014

Unlike the existing regression analysis, this study anticipated future marine traffic volume using time series analysis and artificial neural network model. Especially, it tried to anticipate future marine traffic volume by applying predictive value through time series analysis on artificial neural network model as an additional input variable. This study used monthly observed values of Incheon port from 1996 to 2013. In order for the verification of the forecasting of the model, value for 2013 is anticipated from the built model with observed values from 1996 to 2012 and a proper model is decided by comparing with the actual observed values. Marine traffic volume of Incheon port showed more traffic than average for May and November by 5.9 % and 4.5 % respectably, and January and August showed less traffic than average by 8.6 % and 4.7 % in 2015. Thus, it is found that Incheon port has difference in monthly traffic volume according to the season. This study can be utilized as a basis to reflect the characteristics of traffic according to the season when investigating marine traffic field observation.

• Proceedings of the KOR-KST Conference
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• 1995.02a
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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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.23-30
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• 2006

The variation in the traffic volume on any given roads is the reflection of its user's economic activities and life patterns. And traffic volume flows in every hour usually take different charateristics depending on the location and the function of the roads. This study produced the Monthly Adjustment Factor, Weekly Adjustment Factor and Design hourly Factor, each of which is the index indicating the traffic volume charaterirstics on the highways leading to the recreation areas in the mountainous and seaside tourist sites. Applying these results, it might be possible to calculate the optimal AADT (Annual Average Daily Traffic) and DHV (Design Hour Volume), also be a help to establish a traffic management policy. Finally, it hopes to promote new version of KHCM (Korea Highway Capacity Manual) which includes traffic volume characteristics on recreation areas.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.60-75
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• 2019

Nowadays, interest in safety of pedestrians who are relatively weak when compared with vehicles increases. Also, concern for pedestrian accidents on crosswalks increases. For these reasons, scrambled crosswalks which are considered to contribute pedestrian safety by reducing conflicts between vehicles and pedestrians are actively discussed and there are also a few intersections where they are actually installed. However, scrambled crosswalks must include all-red phase for all vehicle traffic flows, which inevitably leads to increase of lost time per cycle. Therefore, evaluation in terms of efficiency should be done before installation of scrambled crosswalks. This research suggests installation criteria for scrambled crosswalks so that it is possible to judge whether installation of scrambled crosswalks is appropriate only by surveying vehicle traffic volume and pedestrian traffic volume. This research derives optimum cycle length from signal optimization models which considers both vehicle traffic volume and pedestrian traffic volume. From this optimum cycle length, this research compares total delay time before and after installation of scrambled crosswalks. From an analysis, two research results are derived. Firstly, there is critical traffic volume above which installation of scrambled crosswalks can not efficient. Secondly, appropriate areas for installation of scrambled crosswalks are different by each signal intersection or by each signal system and those difference vary. From these results, this research suggests installation criteria for scrambled crosswalks which consists of two steps. The delay time of the pedestrians may be increased after the diagonal crosswalk is installed, but it may be desirable to install in consideration of the appropriate traffic level to ensure safety.

• Journal of KIISE:Information Networking
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• v.35 no.6
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• pp.474-481
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• 2008

Scanning worm increases network traffic load and result in severe network congestion because it is a self-replicating worm and send copies of itself to a number of hosts through the Internet. So an early detection system which can automatically detect scanning worms is needed to protect network from those attacks. Although many studies are conducted to detect scanning worms, most of them are focusing on the method using packet header information. The method using packet header information has long detection delay since it must examine the header information of all packets entering or leaving the network. Therefore we propose an algorithm to detect scanning worms using network traffic characteristics such as variance of traffic volume, differentiated traffic volume, mean of differentiated traffic volume, and product of mean traffic volume and mean of differentiated traffic volume. We verified the proposed algorithm by analyzing the normal traffic captured in the real network and the worm traffic generated by simulator. The proposed algorithm can detect CodeRed and Slammer which are not detected by existing algorithm. In addition, all worms were detected in early stage: Slammer was detected in 4 seconds and CodeRed and Witty were detected in 11 seconds.

• Journal of Fisheries and Marine Sciences Education
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• v.19 no.2
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• pp.278-287
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• 2007

Since traffic congestion ratio at any given port fluctuates on the number of arriving and departing vessels, the total tonnage of freight volume being handled, and the number of berth in operation and other factors, there exists a need to numerically analyze the waterway traffic volume. However, there are no effective regulations in regards to the waterway traffic analysis prior to expansion of a port facility. The current analysis requires the traffic analysis in relation only to the width of the waterway, which clearly falls short of achieving a comprehensive evaluation study that could be used in consideration of port expansion.This study provides five scenarios to execute a comprehensive evaluation study and base for the sensitivity study by analyzing the scenarios. As a result of the sensitivity analysis, the A, B, and C scenarios varies the average arrival ratio of the berth shows 1.1, 1.19, and 1.28 times of delays respectively. Also, The D and E scenarios take place malfunctions of pier shows 1.21 and 1.53 times of delays respectively. Therefore, various strategies of harbor development and method of harbor management are needed for the flexible correspondence to the environmental changes such as the excessive increasing of the freight volume and often taking place of malfunctioning.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.773-794
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• 2021

Prediction of vehicle traffic volume is very important in planning municipal administration. It may help promote social and economic interests and also prevent traffic congestion costs. Traffic volume as a time-varying trajectory is considered as functional data. In this paper we study three functional regression models that can be used to predict an unseen trajectory of traffic volume based on already observed trajectories. We apply the methods to highway tollgate traffic volume data collected at some tollgates in Seoul, Chuncheon and Gangneung. We compare the prediction errors of the three models to find the best one for each of the three tollgate traffic volumes.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.33-40
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• 2004

This study aims to provide guidelines for the selection of on-street parking spot on local streets considering conditions of surrounding area and characteristics of traffic generation. This guideline provides the method which determine required roadway width for planning and design of local streets. It is necessary to identify factors for the location selection analysis. This research team selects 12 case study areas to investigate traffic environment on the sites for this analysis. Most of factors which influence on-street parking are found to have a qualitative data format except traffic volume and pedestrian movement data. Quantification theory II which is known to be suitable for qualitative analysis has been applied to identify the meaningful variables for dependent variable. In addition, discriminant analysis has performed to verify the correlation for each variable with hit ratio. Road width, traffic volume, street traders and their heavy packages, and illegally parked vehicle are found to be most significant factors for selection of on-street parking location. Therefore, it is necessary to consider traffic volume generated from massive residential complex and traffic volume for outside and above-mentioned factors for installation of on-street parking facility in the case of new road construction or road width widen.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.2
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• pp.19-27
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• 2010

Historical archived traffic data management system enables a long term time-series analysis and provides data necessary to acquire the constantly changing traffic conditions and to evaluate and analyze various traffic related strategies and policies. Such features are provided by maintaining highly reliable traffic data through scientific and systematic management. Now, the management systems for massive traffic data have a several problems such as, the storing and management methods of a large volume of archive data. In this paper, we describe how to storing and management for the massive traffic data and, we propose methodology for logical and physical architecture, collecting and storing, database design and implementation, process design of massive traffic data.