• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.11B
• /
• pp.1038-1049
• /
• 2003

Exactly measuring traffic load is the basis for efficient traffic engineering. However, precise traffic measurement involves inspecting every packet traversing a lint resulting in significant overhead on routers with high-speed links. Sampling techniques are proposed as an alternative way to reduce the measurement overhead. But, since sampling inevitably accompany with error, there should be a way to control, or at least limit, the error for traffic engineering applications to work correctly. In this paper, we address the problem of bounding sampling error within a pre-specified tolerance level. We derive a relationship between the number of samples, the accuracy of estimation and the squared coefficient of variation of packet size distribution. Based on this relationship, we propose an adaptive random sampling technique that determines the minimum sampling probability adaptively according to traffic dynamics. Using real network traffic traces, we show that the proposed adaptive random sampling technique indeed produces the desired accuracy, while also yielding significant reduction in the amount of traffic samples.

• Journal of Korean Society of Transportation
• /
• v.17 no.1
• /
• pp.7-17
• /
• 1999

The expressway network includes a total of about 1,899 km in our country The only 1,016 km of that is being managed by the closed Toll Collection System(TCS) which is composed of 74 tollgates. We obtain inter-tollgate O-D matrices from that system everyday. But, they are not traffic-zonal O-D matrices. So they have not been used for the expressway traffic analysis and the traffic demand estimation despite of their accuracy. If we could estimate the traffic-zonal O-D matrices from TCS O-D ones, we could perform expressway traffic analysis more efficiently. Moreover we could obtain more precise expressway O-D matrices and traffic-zonal O/D ones by this approach than by the conventional ones. In this paper. we proposed the model estimating traffic-zonal O/D matrices from TCS O-D ones. The assigned volumes with the estimated traffic-zonal O-D matrices produced the only 17.9% error all over the TCS expressway section when compared to the real traffic volumes. So, the proposed model enables for us to estimate more accurate O/D matrics than any other existing methods.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• v.1
• /
• pp.151-156
• /
• 2006

Accurate vessel traffic observation is indispensable to carry out vessel traffic management, design of vessel traffic route, planning of port construction, etc. In order to observe the vessel traffic accurately without many efforts such as the use of a ship or car equipped with special radar observation system and the preparation of observation staff, the authors have been developing completely automated remote radar/AIS network system covering the main traffic area in Tokyo Bay. The composite radar image observed at Yokosuka and Kawasaki radar stations with AIS information can be seen on web site of Internet. In addition to the development of radar/AIS observation system, the software to analyze observed vessel traffic flow has been developed. This software has various functions such as automatic tracking of ship's positions, automatic estimation of ship's size, automatic integration of radar image and AIS data, animation of ships' movements, extraction of dangerous ship encounters, etc. The configuration and functions of the developed remote radar/AIS network system are shown first in this paper. Then various functions of the software to analyze vessel traffic are introduced, and some analyzed results on the vessel traffic in Tokyo Bay are described demonstrating the effectiveness of the developed system.

• Journal of Korean Society of Transportation
• /
• v.32 no.6
• /
• pp.567-578
• /
• 2014

The study suggested a method to improve analysis accuracy such that the interactive effects of transportation changes between outside and inside of sub-areas were sequentially considered in the analysis by linking a macroscopic network analysis and a microscopic traffic simulation. A dynamic O/D estimation method was developed for practical implement of sub-area microscopic simulation analysis by using the results of macroscopic network analysis, the results of selected link analysis at the cordon line of the sub-area, departure time data of household travel survey, timely observed traffic volume data at the cordon. This estimated dynamic O/D for the sub-area made it possible to analyze traffic phenomena in details. Various detailed phenomena such as traffic queues, delay at intersection, and conflicts between vehicles, which is impossible to be grasped through a macroscopic analysis, can be analyzed with the dynamic microscopic traffic analysis. Through implementing an empirical study and validation, the study provided a reference result about accuracy of a microscopic traffic simulation of a sub-area to help its application for real transportation policy analysis.

• Journal of Electrical Engineering and Technology
• /
• v.2 no.4
• /
• pp.543-548
• /
• 2007

We present a dynamic Bayesian network (DBN) model of a generalized class of nonstationary birth-death processes. The model includes birth and death rate parameters that are randomly selected from a known discrete set of values. We present an on-line algorithm to obtain optimal estimates of the parameters. We provide a simulation of real-time characterization of load traffic estimation using our DBN approach.

• Journal of the Korea Society for Simulation
• /
• v.6 no.2
• /
• pp.117-124
• /
• 1997

A simulation model for the estimation of cutoff connection rate in the asynchronous transfer mode (ATM) switching system under multimedia traffic environments is presented. The simulator is developed by the integration of the AweSim tool with user-written C++ routines that model the internal structures of operational details of the switching system. For the case study, the simulator is applied to the ATM switching system developed by Electronics and Telecommunications Research Institute (ETRI) to compare design alternatives according to the cutoff connection rates.

• Journal of Korean Society of Transportation
• /
• v.23 no.6 s.84
• /
• pp.19-30
• /
• 2005

The objective of this research is to keep track of path travel time using methods of collecting traffic data. Users of traffic information are looking for extensive information on path travel time, which is referred to as the time taken for traveling from the origin to the destination. However, all the information available is the average path travel times, which is a simple sum of the average link travel times. The average path travel time services are not up to the expectation of traffic information consumers. To improve provide more accurate path travel time services, this research makes a number of different estimates of various path travel times on one path, assuming it will be under the same condition, and provides a range of estimates with their probabilities to the consumers, who are looking for detailed information. To estimate the distribution of the path travel times as a combination of link travel times. this research analyzes the relation between the link travel time and path travel time. Based on the result of the estimation. this research develops the algorithm that combines the distribution of link travel time and estimates the path travel time based on the link travel times. This algorithm was tested and proven to be highly reliable for estimating the path traffic time.

• Journal of Korean Society of Transportation
• /
• v.24 no.1 s.87
• /
• pp.73-84
• /
• 2006

This study was carried out to set up the logic to determine lengths of the homogeneous sections effectively in order to provide dynamic travel time on real time base for the application of the model. First, considering real time traffic pattern fluctuation, lengths of the homogeneous sections for each time period and the final homogeneous sections were determined. In order to determine lengths of the homogeneous sections according to traffic condition, the cluster analysis was used based on real time data. In order to verify the homogeneous section the case with detectors in all links and the case with detectors in homogeneous section for each time period are used. As the results of verification, each cases showed similar estimation results. The results of this study are expected to be used for National Highway traffic management and the system to Provide a traffic information in the future. According to this study, when the homogeneous section decision model are used to the ITS project for National Highway, operation cost is expected to be cut by effectively establishing point detectors.

• The Journal of the Korea Contents Association
• /
• v.17 no.3
• /
• pp.589-595
• /
• 2017

We present an estimation model for optimal channel capacity required to data traffic transmission. The optimal channel capacity should be calculated in order to satisfy the permitted transmission delay of each wireless data services. Considering the discrete-time operation of digital communication systems and batch arrival of packet-switched traffic for various wireless services, $Geo^x$/G/1 non-preemptive priority queueing model is analyzed. Based on the heuristic interpretation of the mean waiting time, the mean waiting times of various data packets which have the service priority. Using the mean waiting times of service classes, we propose the procedure of determining the optimal channel capacity to satisfy the quality of service requirement of the mean delay of wireless services. We look forward to applying our results to improvement in wireless data services and economic operation of the network facilities.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.1
• /
• pp.169-189
• /
• 2015

Detection of anomalous events from video streams is a challenging problem in many video surveillance applications. One such application that has received significant attention from the computer vision community is traffic video surveillance. In this paper, a Lossy Count based Sequential Temporal Pattern mining approach (LC-STP) is proposed for detecting spatio-temporal abnormal events (such as a traffic violation at junction) from sequences of video streams. The proposed approach relies mainly on spatial abstractions of each object, mining frequent temporal patterns in a sequence of video frames to form a regular temporal pattern. In order to detect each object in every frame, the input video is first pre-processed by applying Gaussian Mixture Models. After the detection of foreground objects, the tracking is carried out using block motion estimation by the three-step search method. The primitive events of the object are represented by assigning spatial and temporal symbols corresponding to their location and time information. These primitive events are analyzed to form a temporal pattern in a sequence of video frames, representing temporal relation between various object's primitive events. This is repeated for each window of sequences, and the support for temporal sequence is obtained based on LC-STP to discover regular patterns of normal events. Events deviating from these patterns are identified as anomalies. Unlike the traditional frequent item set mining methods, the proposed method generates maximal frequent patterns without candidate generation. Furthermore, experimental results show that the proposed method performs well and can detect video anomalies in real traffic video data.