• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.19 no.9
• /
• pp.1719-1729
• /
• 1994

In this paper, an adaptive CAC(Connection Admission Control) method is proposed. The adaptive CAC uses traffic estimates derived from both traffic parameter specified by user and cell flow measurements. Traffic estimation using user-specified parameters is performed at every moment of connection request or connection release by recursive formula which makes real-time calculation possible. Traffic estimation using cell flow measurement is carried out when the number of connected calls does not change during a measurement reflection period-renewal period. The most import ant thing for the traffic estimation using cell flow measurement is the determination of the length of a renewal period to trace a real traffic flow with an allowable time lag and the measurement reflection ratio(MRR) both to reduce the portion of overestimation and to avoid underestimation of real traffic flow. To solve these problems, the adaptive CAC updates renewal period and MRR adaptively according to the number of connections and the elapsed time after last connection or release respectively. Performance analysis for the proposed method is evaluated in several aspects for the cases of both homogeneous and heterogeneous bursty traffic. Numerical examples show the adaptive CAC method has the better performance compared with conventional CAC method based on burst model from the both utilization and QOS point of view.

• Journal of Satellite, Information and Communications
• /
• v.5 no.2
• /
• pp.87-91
• /
• 2010

The IEEE 802.15.4 and IEEE 802.15.7 standard are the typical of low rate wireless and Visible Light Wireless personal area networks. Its Medium Access Control protocol can support the QoS traffic flows for real-time application through guaranteed time slots (GTS) in beacon mode. However, how to achieve a best allocation scheme is not solved clearly. The current analytical models of IEEE 802.15.4 MAC reported in the literature have been mainly developed under the assumption of saturated traffic or non-bursty unsaturated traffic conditions. These assumptions don't capture the characteristics of bursty multimedia traffic. In this paper, we propose a new analytical model for GTS allocation with burst Markov modulated ON-OFF arrival traffic.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.16 no.3
• /
• pp.59-72
• /
• 2017

As the part of study which handles the measure to use the individual vehicle information of taxi GPS data on signal controls in order to overcome the limitation of Loop detector-based collecting methods of real-time signal control system, this paper conducted series of evaluations and improvements on link travel time, queue vehicle time estimates and traffic condition decision algorithm from the research introduced in 2016. considering the control group and the other, the link travel time has enhanced the travel time and the length of queue vehicle has enhanced the estimated model taking account of the traffic situation. It is analyzed that the accuracy of the average link travel time and the length of queue vehicle are respectably both approximately 95 % and 85%. The traffic condition decision algorithm reflected the improved travel speed and vehicle length. Smoothing was performed to determine the trend of the traffic situation and reduce the fluctuation of the data, and the algorithms have refined so as to reflect the pass period on overflow judgment criterion.

• Journal of information and communication convergence engineering
• /
• v.5 no.1
• /
• pp.54-58
• /
• 2007

A real-time frame-layer rate control algorithm with a token bucket traffic shaper is proposed for distortion variation minimization. The proposed rate control method uses a non-iterative optimization method for low computational complexity, and performs bit allocation at the frame level to minimize the average distortion over an entire sequence as well as variations in distortion between frames. The proposed algorithm does not produce time delay from encoding, and is suitable for real-time low-complexity video encoder. Experimental results indicate that the proposed control method provides better visual and PSNR performances than the existing rate control method.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.33 no.3
• /
• pp.1115-1122
• /
• 2013

Recently the demands for traffic information tend to increase, and travel time might one of the most important traffic information. To effectively estimate exact travel time, highly reliable traffic data collection is required. BIS(Bus Information System) data would be useful for the estimation of the route travel time because BIS is collecting data for the bus travel time on the main road of the city on real-time basis. Traditionally use of BIS data has been limited to the realm of bus operating but it has not been used for a variety of traffic categories. Therefore, this study estimates a route travel time on road networks in urban areas on the basis of real-time data of BIS and then eventually constructs regression models. These models use an explanatory variable that corresponds to bus travel time excluding service time at the bus stop. The results show that the coefficient of determination for the constructed regression model is more than 0.950. As a result of T-test performance with assistance from collected data and estimated model values, it is likely that the model is statistically significant with a confidence level of 95%. It is generally found that the estimation for the exact travel time on real-time basis is plausible if the BIS data is used.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.1D
• /
• pp.1-9
• /
• 2009

Bus information system(BIS), as a part of the intelligent transportation system(ITS), is one of the most advanced public transportation systems which provide the real-time bus traffic information for the users waiting the buses at the bus stop. However, correct bus information data, such as the present bus location, the user waiting time, the bus arrival time, etc. are not provided for the bus users because the proper bus arrival time predictive models are not used yet in most of the cities operating the bus information system, including the metropolitan City of Ulsan. Thus, the purpose in this study is to investigate real-time bus traffic characteristic data for identifying the bus operation characteristics on the arterial under the study in the metropolitan City of Ulsan, analyze real-time bus traffic characteristic data on the ID locations of the arterial under the study, construct the optimal unit segment models for the unit segments which are the bus stop, node and travel section using the exponential smoothing, weighted smoothing and Kalman Filter methods, respectively, and finally suggest the optimal integrated model for predicting the real-time bus arrival time at the bus stop of the arterial under the study.

• Journal of Korean Society of Transportation
• /
• v.17 no.2
• /
• pp.179-191
• /
• 1999

To device effective freeway traffic flow control strategies and freeway traffic information dissemination strategies, it is very important to estimate real physical queue length on the freeway. Shock wave theory and queueing theory have limitation to be used to estimate the queue length. The primary objective of this study is to develop a reliable method for estimating the physical queue length and level of congestion. Queueing propagation processes were analysed by using such traffic data as main line traffic volume, ramp volume, density. speed, and physical queue length collected by video photographing on Olympic Freeway. As a result of analysis, it has been confirmed that the real queue length can be estimated by using the traffic counts arriving the congested region and passing a bottleneck location. Further more, a reliable method for estimating the level of congestion could be developed on the basis of real-time traffic counts.

• IE interfaces
• /
• v.15 no.4
• /
• pp.374-381
• /
• 2002

In this paper, we design and implement a real-time route guidance system(RGS) in large-scale networks. Coupled with the well-known mathematical routing algorithms, we devise an RGS for knowledge aquisition and self-learning ability within the framework of the expert system. Through off-line construction of database, on-line treatment of unexpected traffic accidents, etc., the developed RGS can provide drivers with good quality real-time routing information. The practical effectiveness of the proposed system is demonstrated in terms of response time and route appropriateness.

• Journal of the Korea Society of Computer and Information
• /
• v.20 no.12
• /
• pp.37-44
• /
• 2015

In this paper, we propose the assistance method to enable safe driving through analysis of dangerous driving behavior using real-time alarm by vehicle speed, azimuth data and smartphone. For this method, smartphone is receiving driving data from digital tachograph using communication. Safe driving habit is a very important issue to commercial vehicle because that driver's long time driving than other vehicle type driver. Existing methods are very inefficient to improve immediately dangerous driving habits during driving because proceed driving behavior analysis after the vehicle operation. We propose the new safe driving assistance method that can prevent traffic accidents by real-time and improve the driver's wrong driving habits through real-time dangerous driving behavior analysis and notification the result to the driver. We have confirmed that the method in this paper will help to improve driving habits and can be applied through the proposed method implementation and simulation experiment.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.33 no.5B
• /
• pp.344-355
• /
• 2008

In this paper, we are dealing with the problems of performance evaluation of Differentiated Services(DiffServ) networks. For successful performance evaluation, the ability to accurately represent "real" traffic on the network by suitable traffic models is an essential ingredient. Many research results on the nature of real traffic measurements demonstrated LRD(long-range dependence) property for the Internet traffic including Web, TELNET, and P2P traffic. The LRD can be effectively represented by self-similarity. In this paper, we design and implement self-similar traffic generator using the aggregated On/Off source model, based on the analysis of the On-Off source model, FFT-FGN(Fast Fourier Transform-Fractional Gaussian Noise) model, and RMD(Random Midpoint Displacement) model. We confirmed the self-similarity of our generated traffic by checking the packet inter-arrival time of TCPdump data. Further we applied the implemented traffic generator to the performance evaluation of DiffServ networks and observed the effect of performance to the a value of the On/Off model, and performance of EF/BE class traffic by CBQ.