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

• International Journal of Highway Engineering
• /
• v.19 no.5
• /
• pp.143-151
• /
• 2017

PURPOSES : The purpose of this study is to develop models of accidents occurring at circular intersections related to the time of day and night and driver gender, and to provide countermeasures for safer circular intersections. METHODS : Seventy intersections built before 2008 were surveyed for inclusion in the modeling. Traffic accident data from 2008 to 2014 were collected from the TAAS data set of the Road Traffic Authority. Sixteen variables explaining the accidents including geometry and traffic volume were selected from the literature and seven multiple linear regression models were developed using SPSS 20.0. RESULTS : First, the null hypotheses, that the number of traffic accidents are not related to driver gender or time of day, were rejected at a 5% level of significance. Second, seven statistically significant accident models with $R^2$ value of 0.643-0.890 were developed. Third, in daytime models by gender, when the right-turn-only lane was selected as the common variable, the number of lanes, presence of driveways and speed humps, diagrammatic exit destination sign, and total entering traffic volume were evaluated as specific variables. Finally, in nighttime models by gender, when the diagrammatic exit destination sign was selected as the common variable, total entering traffic volume, presence of right-turn-only lanes, number of circulatory road way lanes, and presence of splitter islands and driveways were identified as specific variables. CONCLUSIONS:This study developed seven accident models and analyzed the common and specific variables by time of day and gender. The results suggest approaches to providing countermeasures for safer circular intersections.

• Journal of Korean Society of Transportation
• /
• v.32 no.5
• /
• pp.497-502
• /
• 2014

As ground air traffic control at the airport is one of the most important tasks in air transport, attention to the development of a related simulator has expanded all around the world. For this reason, this research describes the characteristics and advantages of this advanced aerodrome traffic control simulator, developed in South Korea, as well as its linkage with A-SMGCS, which is planned to be developed in the future. One of the characteristics of this simulator is that it is possible to train an air traffic controller independently, especially under various conditions such as in different weathers and normal or abnormal circumstances. Therefore, this aerodrome traffic control simulator, through the comprehensive training under various conditions, will contribute to aviation safety and airport capacity enhancement training.

• Journal of Korean Society of Transportation
• /
• v.32 no.5
• /
• pp.522-530
• /
• 2014

Spatio-temporal congestion evolution pattern can be reproduced using the VDS(Vehicle Detection System) historic speed dataset in the TMC(Traffic Management Center)s. Such dataset provides a pool of spatio-temporally experienced traffic conditions. Traffic flow pattern is known as spatio-temporally recurred, and even non-recurrent congestion caused by incidents has patterns according to the incident conditions. These imply that the information should be useful for traffic prediction and traffic management. Traffic flow predictions are generally performed using black-box approaches such as neural network, genetic algorithm, and etc. Black-box approaches are not designed to provide an explanation of their modeling and reasoning process and not to estimate the benefits and the risks of the implementation of such a solution. TMCs are reluctant to employ the black-box approaches even though there are numerous valuable articles. This research proposes a more readily understandable and intuitively appealing data-driven approach and developes an algorithm for identifying congestion patterns for recurrent and non-recurrent congestion management and information provision.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.15 no.1
• /
• pp.8-15
• /
• 2007

Freeway corridors consist of urban freeways and parallel arterials that drivers can use alternatively. Ramp metering in freeways and signal control in arterials are contemporary traffic control methods that have been developed and applied in order to improve traffic conditions of freeway corridors. However, most of the existing studies have focused on either optimal ramp metering in freeways, or progression signal strategies between arterial intersections. There have been no traffic control systems in Korea that integrates the freeway ramp metering and arterial signal control. The effective control strategies for freeway operations may cause negative effects on arterial traffic. On the other hand, traffic congestion and bottleneck phenomenon of arterials due to the increasing peak-hour travel demand and ineffective signal operation may generate an accessibility problem to freeway ramps. Thus, the main function of the freeway which is the through-traffic process has not been successful. The purpose of this study is to develop an integrated control model that connects freeway ramp metering systems and signal control systems in arterial intersections. And Optimization of integrated control model which consists of ramp metering and signal control is another purpose. The design of experiment, neural network, and simulated annealing are used for optimization.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.10a
• /
• pp.110-113
• /
• 2022

Nowadays, breaking through the conventional traffic signal control method based on mathematical optimization, artificial intelligence began to be used in the area. In response to this trend, many studies are ongoing to figure out how to utilize AI technology properly for traffic signal optimization. They just simply focus on which method will work well besides lots of machine learning techniques and abandon the reward function engineering. In many cases, the reward function consists of the average delay of the vehicles in the intersection. However, this may lead to AI's misunderstanding about the traffic signal control: what AI regards as a good situation may not be realistic. Even the reward function itself may not meet the service level. Therefore, this study analyzes the problems of previous reward functions and will suggest how to reward function can be enhanced.

• Journal of Navigation and Port Research
• /
• v.32 no.1
• /
• pp.81-88
• /
• 2008

The forecast of a container traffic has been very important for port plan and development. Generally, statistic methods, such as regression analysis, ARIMA, have been much used for traffic forecasting. Recent research activities in forecasting with artificial neural networks(ANNs) suggest that ANNs can be a promising alternative to the traditional linear methods. In this paper, a hybrid methodology that combines both ARIMA and ANN models is proposed to take advantage of the unique strength of ARIMA and ANN models in linear and nonlinear modeling. The results with port traffic data indicate that effectiveness can differ according to the characteristics of ports.

• Journal of the Korean Society of Safety
• /
• v.27 no.2
• /
• pp.111-116
• /
• 2012

This study deals with the traffic accidents of circular intersections in Korea. The purposes are to comparatively analyze the characteristics by operational type, and to develop the models using the data of 82 intersections. In pursuing the above, this study gives particular emphasis to modeling such the accidents as the roundabout and rotary in urban area. The main results analyzed are as follows. First, the null hypotheses that the number of accidents are the same in both the urban and rural intersections, and roundabout and rotary in urban area, were analyzed to be rejected. Second, 3 accident models were developed, which were all statistically significant. The independent variables used in the above models are the ADT, number of approach lane, bus stop, parking facilities, and others. This study could be expected to give some implications to the traffic safety policy decision-making.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.7 no.2
• /
• pp.39-48
• /
• 2001

In recent years, the marine traffic congestion has increased due to the expansion of vessel traffic volume in Korean coastal waterway. Heavy traffic could bring serious marine casualties which cause the loss of human lives, properties and marine pollution in coastal area. The prevention of marine accidents has been a major topic in marin society and various policies and countermeasures have been developed, applied to the industries. VTS(Vessel Traffic Services) is considered as one of effective method to promote marine safety but it needs relatively huge amount of budgets to build and also number of personnels for the operation. Thus prior to establishing the VTS. It should be surveyed the marine traffics, general conditions of waterway including geographical, meteorological characteristics and assessed to find the most reasonable area and places for the system. Therefore this paper aims to develop the method for this evaluation through the hierarchical evaluation structure model in connection with ISM(interpretive structural modeling) and AHP(analytic hierarchy process) methods. The model in this paper is applied to 4 coastal area in Korean waterway as candidates and found that the priority for the needs of VTS should be in order such as Yosu, Wando, Mokpo, Geoje coastal area.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2007.12a
• /
• pp.259-260
• /
• 2007

The forecast of a container traffic has been very important for port plan and development Generally, statistic methods, such as regression analysis, ARIMA, have been much used for traffic forecasting. Recent research activities in forecasting with artificial neural networks(ANNs) suggest tint ANNs am be a promising alternative to the traditional linear methods. In this paper, a hybrid methodology that combines both ARIMA and ANN models is proposed to take advantage of the unique strength of ARIMA and ANN models in linear and nonlinear modeling. The results with port traffic data indicate tint effectiveness can differ according to the ch1racteristics of ports.