• Journal of Korea Multimedia Society
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• v.17 no.12
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• pp.1453-1460
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• 2014

WFQ (Weighted Fair Queuing) provides not only fairness among traffic flows in using bandwidth but also guarantees the Quality of Service (QoS) that individual flow requires, which is why it has been applied to the resource reservation protocol (RSVP)-capable router. The RSVP allocates an enough resource to satisfy both the rate and end-to-end delay requirements of the flow in the condition of no packet loss, and the WFQ scheduler guarantees those QoS requirements with the allocated resource. In practice, however, most QoS-guaranteed services allow a degree of packet loss, especially from 0.1% to 3% for Voice over IP. This paper discovers that the packet loss rate of each traffic flow is determined by only its time-stamp adjustment value, and then enhances the WFQ to provide a differentiated packet loss guarantee under general traffic conditions in terms of both traffic characteristics and QoS requirements. The performance evaluation showed that the proposed WFQ could increase the utilization of bandwidth by 8~11%.

• 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.

• Journal of Communications and Networks
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• v.3 no.4
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• pp.383-395
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• 2001

Recent measurement and simulation studies have revealed that wide area network traffic displays complex statistical characteristics-possibly multifractal scaling-on fine timescales, in addition to the well-known properly of self-similar scaling on coarser timescales. In this paper we investigate the performance and network engineering significance of these fine timescale features using measured TCP anti MPEG2 video traces, queueing simulations and analytical arguments. We demonstrate that the fine timescale features can affect performance substantially at low and intermediate utilizations, while the longer timescale self-similarity is important at intermediate and high utilizations. We relate the fine timescale structure in the measured TCP traces to flow controls, and show that UDP traffic-which is not flow controlled-lacks such fine timescale structure. Likewise we relate the fine timescale structure in video MPEG2 traces to sub-frame encoding. We show that it is possibly to construct a relatively parsimonious multi-fractal cascade model of fine timescale features that matches the queueing performance of both the TCP and video traces. We outline an analytical method ta estimate performance for traffic that is self-similar on coarse timescales and multi-fractal on fine timescales, and show that the engineering problem of setting safe operating points for planning or admission controls can be significantly influenced by fine timescale fluctuations in network traffic. The work reported here can be used to model the relevant characteristics of wide area traffic across a full range of engineering timescales, and can be the basis of more accurate network performance analysis and engineering.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4717-4737
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• 2017

Today, smart grids, smart homes, smart water networks, and intelligent transportation, are infrastructure systems that connect our world more than we ever thought possible and are associated with a single concept, the Internet of Things (IoT). The number of devices connected to the IoT and hence the number of traffic flow increases continuously, as well as the emergence of new applications. Although cutting-edge hardware technology can be employed to achieve a fast implementation to handle this huge data streams, there will always be a limit on size of traffic supported by a given architecture. However, recent cloud-based big data technologies fortunately offer an ideal environment to handle this issue. Moreover, the ever-increasing high volume of traffic created on demand presents great challenges for flow management. As a solution, flow aggregation decreases the number of flows needed to be processed by the network. The previous works in the literature prove that most of aggregation strategies designed for smart grids aim at optimizing system operation performance. They consider a common identifier to aggregate traffic on each device, having its independent static aggregation policy. In this paper, we propose a dynamic approach to aggregate flows based on traffic characteristics and device preferences. Our algorithm runs on a big data platform to provide an end-to-end network visibility of flows, which performs high-speed and high-volume computations to identify the clusters of similar flows and aggregate massive number of mice flows into a few meta-flows. Compared with existing solutions, our approach dynamically aggregates large number of such small flows into fewer flows, based on traffic characteristics and access node preferences. Using this approach, we alleviate the problem of processing a large amount of micro flows, and also significantly improve the accuracy of meeting the access node QoS demands. We conducted experiments, using a dataset of up to 100,000 flows, and studied the performance of our algorithm analytically. The experimental results are presented to show the promising effectiveness and scalability of our proposed approach.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.110-123
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• 2019

Traffic data is the most basic element necessary for transportation planning and traffic system operation. Recently, a method of estimating traffic flow characteristics using distance to a leading vehicle measured by an ADAS camera has been attempted. This study investigated the feasibility of the ADAS vehicle reflecting the distance error of image-based vehicle identification technology as a means to estimate the traffic flow through the normalized root mean square error (NRMSE) based on the number of lanes, traffic demand, penetration rate of probe vehicle, and time-space estimation area by employing the microscopic simulation model, VISSIM. As a result, the estimate of low density traffic flow (i.e., LOS A, LOS B) is unreliable due to the limitation of the maximum identification distance of ADAS camera. Although the reliability of the estimates can be improved if multiple lanes, high traffic demands, and high penetration rates are implemented, artificially raising the penetration rates is unrealistic. Their reliability can be improved by extending the time dimension of the estimation area as well, but the most influential one is the driving behavior of the ADAS vehicle. In conclusion, although it is not possible to accurately estimate the traffic flow with the ADAS camera, its applicability will be expanded by improving its performance and functions.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.5
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• pp.125-135
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• 2004

The validity of simulation has been well-established for decades in areas such as computer and communication system. Recently, the technique has become entrenched in specific areas such as transportation and traffic forecasting. Several methods have been proposed for investigating complex traffic flows. However, the dynamics of vehicles and their driver's characteristics, even though it is known that they are important factors for any traffic flow analysis, have never been considered sufficiently. In this paper, the traffic simulation using a multi-agent approach with considering vehicle dynamics is proposed. The multi-agent system is constructed with the traffic environment and the agents of vehicle and driver. The traffic environment consists of multi-lane roads, nodes, virtual lanes, and signals. To ensure the fast calculation, the agents are performed on the based of the rules to regulate their behaviors. The communication frameworks are proposed for the agents to share the information of vehicles' velocity and position. The model of a driver agent which controls a vehicle agent is described in the companion paper. The vehicle model contains the nonlinear subcomponents of engine, torque converter, automatic transmission, and wheels. The simulation has proceeded for an interrupted and uninterrupted flow model. The result has shown that the driver agent performs human-like behavior ranging from slow and careful to fast and aggressive driving behavior, and that the change of the traffic state is closely related with the distance and the signal delay between intersections. The system developed shows the effectiveness and the practical usefulness of the traffic simulation.

• International Journal of Highway Engineering
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• v.10 no.2
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• pp.221-227
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• 2008

This study identifies the relationship between traffic data quality obtained from loop detectors and their location. Traffic data basically shows traffic flow conditions and thus, these information can be used as inputs for various transportation management strategies. Out study presents how to determine optimal downstream detector location on merging area in order to enhance the effects of ramp metering strategies. Microscopic simulation model, PARAMICS, is used as the main analytical tool. Assuming that detector location relies heavily on traffic flow characteristics in each roadway segment, we perform statistical analysis to identify homogeneous traffic conditions on merging area.

• Journal of Korean Society of Transportation
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• v.12 no.2
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• pp.47-63
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• 1994

The purposes of this study are to identify Traffic Flow characteristics and to develop approach delay model of unsignalized intersection based on the travel speed in the conflicting area. The results of this study are as following ; 1. The cumulative frequency distributions of Left-turning speed show a few differences among approaches and they are distributed to lower range of speeds. On the other hand, those of through speed show obvious differences among bounds. The similar results also show in the analysis of Percentile speed. 2. The effectiveness of conflicting movements to travel speed in the conflicting area are analyzed using regression analysis. Left-turning speed model shows that Left-and Right-Conflicting speed. Through-speed model is also developed, when approaching through volume is less than 420vph. 3. Since the lost time due to the acceleration stop, and decelerlation is occured in the conflicting area, approach delay model is delivered using the travel speed models under the condition of small queuing delay.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3D
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• pp.335-345
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• 2009

Generally, density is used as a measure of effectiveness (MOE) of the level of service (LOS) for the basic segment of the roadway facility, but can not express the operational condition of the roadway facility properly because there can be an error in the computed density compared with the density measured in the field. Thus, the purpose of this study is to investigate the real-time traffic characteristic data (traffic flow, speed, occupancy, headway, spacing, etc.) from the detectors installed on the mainline section of urban freeway under the study, analyze the maximum flow rate from the relationship between the real-time traffic characteristics collected, and evaluate the LOS criteria within the basic segment of the urban freeway based on the relationship between the occupancy and the v/c ratio depending on the level of service.

• Journal of Korean Society of Transportation
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• v.17 no.4
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• pp.71-84
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• 1999

The purpose of this study is to construct a dynamic traffic analysis model using the existing traffic flow theory in order to develope a dynamic traffic assignment technique. In this study the dynamic traffic analysis model was constructed using Daganzo's CELL TRANSMISSION THEORY which was considered more suitable to dynamic traffic assignment than the other traffic flow theories. We developed newly the diverging split module, the cost update module and the link cost function and defined the maximum waiting time decision function that Daganzo haven't defined certainly at his Papers. The output that resulted from the simulation of the dynamic traffic analysis model with test network I and II was shown at some tables and figures, and the analysis of the bottleneck and the HOV lane theory showed realistic outputs. Especially, the result of traffic assignment using the model doesn't show equilibrium status every time slice but showed that the average travel cost of every path maintains similarly in every time slice. It is considered that this model can be used at the highway operation and the analysis of traffic characteristics at a diverging section and the analysis of the HOV lane effect.