• Journal of Korean Society of Transportation
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• v.19 no.2
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• pp.107-107
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• 2001

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.876-879
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• 2002

The paper presents the analysis and results of traffic measurements in the 155 Mbit/s real working ATM backbone network. The traffic is described as an ordered sequence of real-time cells. In this paper we analyze two timescales in which some form of a stochastic process is taking place: cell scale and burst scale. We present another way to describe the cell flow in ATM networks by definition the function, designed to be the probability of the burst of length ∫in n sequential slots.

• Journal of Urban Science
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• v.7 no.1
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• pp.45-54
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• 2018

The purpose of this study is to find the factors that reduce prediction error in traffic volume using highway traffic volume data. The ARIMA model was used to predict the day, and it was confirmed that weekday and weekly characteristics were distinguished by prediction error. The forecasting results showed that weekday characteristics were prominent on Tuesdays, Wednesdays, and Thursdays, and forecast errors including MAPE and MAE on Sunday were about 15% points and about 10 points higher than weekday characteristics. Also, on Friday, the forecast error was high on weekdays, similar to Sunday's forecast error, unlike Tuesday, Wednesday, and Thursday, which had weekday characteristics. Therefore, when forecasting the time series belonging to Friday, it should be regarded as a weekly characteristic having characteristics similar to weekend rather than considering as weekday.

• Journal of the Korean Society of Safety
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• v.25 no.2
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• pp.89-94
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• 2010

This study deals with the traffic accident according to the improvement projects of frequent accident locations. The objective is to analyze the impact of improvements on the accident reduction. In pursuing the above, the study gives the particular attentions to developing the models based on the data of 70 intersections improved. The main results analyzed are as follows. First, 4 multiple linear regression accident models(total, side right-angle, rear end and side stripe accident) which were statistically significant were developed. Second, total accidents reduction by sight-distance and turning traffic flow improvements, side right-angle by sight-distance, over-speed and lane operation, rear end by turning traffic flow, signal and lane operation, and side stripe by traffic impedance improvements were analyzed. Finally, the above 4 models were evaluated to be statically significant through the correlation analysis and pair-sample t-test.

• Journal of Korean Society of Transportation
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• v.17 no.2
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• pp.149-162
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• 1999

One of the most important steps of the design, capacity and operation analysis stapes in the two-lane two way highways is the effect of heavy vehicle to traffic flow quality. This heavy vehicle's effect on traffic flow can be represented as PCE, which is the number of passenger cars that are displaced by a single heavy vehicle of a particular type under prevailing roadway, traffic, and control conditions. In this paper, we focus on the heavy vehicles effect on volume, speed, delay, and the maneuver of freedom which are major MOE's in traffic operation analysis and PCE criterion which should be measurable, determinable and able to reflect the traffic flow characteristics. Therefore, the objective of the paper is to determine the PCE criterion and to develop a new PCE determination method. In this study, delay is adopted as PCE criterion and, for calculation of delay, the highway is divided into the passing zone and the no-passing zone. PCE is determined by comparing the delay due to total traffic flow interaction with the delay due to a single heavy vehicle, Also, this paper proposes a new method to determine the average PCE on the highway that has the passing zones and no-passing zones.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.28 no.1
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• pp.22-33
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• 2020

Due to recent increased air traffic,, air traffic controllers in charge of en-route and approach control have faced huge increase in both workload and its intensity. The purpose of this paper is to analyze how much safety culture of air traffic controllers has effect on their complexity mitigation strategies during their duties. It could be expected complexity mitigation improve air traffic flow resulting in enhancing safety eventually. According to empirical analysis against air traffic controllers in civil aviation and air force in South Korea, it was proven safety culture had a statistically positive effect on complex mitigation strategies through safety behavior. In safety culture among air traffic controllers, intrinsic culture had a positive effect on extrinsic value of safety culture. Intrinsic value of safety culture led to air traffic controllers' safety behavior which created work complexity mitigation strategies. Among work complexity mitigation strategies, communication and cooperation was proven to be the most important factor effected by safety culture and behavior. It was implied that enhancing the intrinsic values of safety culture would cause to improve extrinsic safety culture and air traffic controller's work efficiency.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.6
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• pp.40-52
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• 2011

This paper develops a traffic condition decision algorithm to improve the reliability of traffic information on urban streets. This research is reestablished the criteria of qualitative traffic condition categorization and proposed a new qualitative traffic condition decision types and decision measures. The developed algorithm can be classified into 9 types for qualitative traffic condition in consideration of historical time series of speed changes and traffic patterns. The performance of the algorithm is verified through individual matching analysis using the radar detector data in Ansan city. The results of this paper is expected to help promotion of the traffic information processing system, real-time traffic flow monitoring and management, use of historical traffic information, etc.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.86-99
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• 2021

One of the methods to alleviate traffic congestion is to increase the efficiency of the roads by providing traffic condition information on road user and distributing the traffic. For this, reliability must be guaranteed, and quantitative real-time traffic speed prediction is essential. In this study, and based on analysis of traffic speed related to traffic conditions, historical data correlated with traffic flow were used as input. We developed an LSTM model that predicts speed in response to normal traffic conditions, along with a CNN-LSTM model that predicts speed in response to incidents. Through these models, we try to predict traffic speeds during the hour in five-minute intervals. As a result, predictions had an average error rate of 7.43km/h for normal traffic flows, and an error rate of 7.66km/h for traffic incident flows when there was an incident.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.8
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• pp.335-342
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• 2013

Nowadays, the traffic type and behavior are extremely diverse due to the growth of network speed and the appearance of various services on Internet. For efficient network operation and management, the importance of application-level traffic identification is more and more increasing in the area of traffic analysis. In recent years traffic identification methodology using statistical features of traffic flow has been broadly studied. However, there are several problems to be considered in the identification methodology base on statistical features of flow to improve the analysis accuracy. In this paper, we recognize these problems by analyzing the ground-truth traffic and propose the solution of these problems. The four problems considered in this paper are the distance measurement of features, the selection of the representative value of features, the abnormal behavior of TCP sessions, and the weight assignment to the feature. The proposed solutions were verified by showing the performance improvement through experiments in campus network.

• International Journal of Highway Engineering
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• v.17 no.5
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• pp.123-133
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• 2015

PURPOSES : This study aimed to develop a new highway capacity estimation method and provide comparative results among traditional capacity estimation methods and the recommended values in the latest version of KHCM. METHODS : The limitations of the existing methods, such as inconsistency and underestimation of the capacity value, are summarized through an extensive literature review. To overcome these limitations, a new method is introduced by adopting a definition of capacity and traffic flow characteristics at or near breakdown points. This method can produce the capacity value by searching a point corresponding to the maximum traffic flow through analysis of gradient changes (point of inflection) of the traffic flow and speed distribution. Comparative results of capacity values from each method are also presented to validate the new method by using data collected from detectors on freeways. RESULTS: From the analysis results, it is shown that a consistent capacity value can be estimated by applying the new method. In addition, the resulting capacity values are 3%-4% higher than those recommended in KHCM. CONCLUSIONS : The capacity values listed in the current KHCM tend to produce underestimated results. The new method presented in this paper may be included in the future edition of KHCM.