• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.833-839
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• 2019

Bus Information System (BIS) collects information related to the operation of buses and provides information to users through predictive algorithms. Method of predicting through recent information in same section reflects the traffic situation of the section, but cannot reflect the characteristics of the target line. The method of predicting the historical data at the same time zone is limited in forecasting peak time with high volatility of traffic flow. Therefore, we developed a pattern recognition bus arrival time prediction algorithm which could be overcome previous limitation. This method recognize the traffic pattern of target flow and select the most similar past traffic pattern. The results of this study were compared with the BIS arrival forecast information history of Seoul. RMSE of travel time between estimated and observed was approximately 35 seconds (40 seconds in BIS) at the off-peak time and 40 seconds (60 seconds in BIS) at the peak time. This means that there is data that can represent the current traffic situation in other time zones except for the same past time zone.

• The KIPS Transactions:PartD
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• v.17D no.2
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• pp.87-102
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• 2010

A vast amount of traffic data is produced every day from detection devices but this data includes a considerable amount of errors and missing values. Moreover, this information is periodically deleted before it could be used as important analysis information. Therefore, this paper discusses the implementation of an integrated traffic history database system that continuously stores the traffic data as a multidimensional model and increases the validity and completeness of the data via a flow of processing steps, and provides a what-if analysis function. The implemented system provides various techniques to correct errors and missing data patterns, and a what-if analysis function that enables the analysis of results under various conditions by allowing the flexible definition of various process related environment variables and combinations of the processing flows. Such what-if analysis functions dramatically increase the usability of traffic data but are not provided by other traffic data systems. Experimantal results for cleaning the traffic history data showed that it provides superior performance in terms of validity and completeness.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1174-1177
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• 1987

The design of flow control protocols for integrared networks with complete voice traffic on the data link level is investigated. The class of admissible flow control policies analyzed maximized the average data link throughput subject to an average system time delay constraints a finite intervals (O,s). In particular, it is shown that the optimum control law is bang-bang (window flow mechanism). The window size L can be analytically derived from maximum tolerated time delay T, the input arrival C of the queueing system, the duration of the time interval S, the initial number of packets in the queue.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.10
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• pp.995-999
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• 2010

Every year, traffic accidents and traffic congestion have been rapidly increasing, Although the roadway design and signal system have been improved to relieve traffic accidents, traffic casualties and property damage do not decrease. This paper develops a real-time traffic accident detection and analysis system (RTADAS): In the proposed system, we aim to precisely detect traffic accidents at different design and flow of intersections, However, because the data collected from intersections have uncertainty and complicated causal dependency between them, we construct probability-based networks for correct accident detection.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.6
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• pp.1851-1861
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• 2014

This study aims to calculate reliable sectional travel speeds with the consideration of the characteristics of the probe data collected in the interrupted traffic flow. First, in order to analysis the characteristics of the probe data, we looked into the distribution of the sectional travel times of each probe vehicle and compared the difference in the sectional travel speeds of each probe vehicle collected by DSRC. As a result, it is shown that outliers should be removed for the distribution of the sectional travel times. However, The comparison results show that the sectional travel speeds from the DSRC probe vehicles are not significantly different. Finally, based on the distribution characteristics of the sectional travel speeds of each probe vehicle and the representative values counted during a collection period, we drew the optimal outlier removal procedure and evaluated the estimation errors. The evaluation results showed that the DSRC sectional travel speeds were found to be similar to the observed values from actually running vehicles. On the contrary, in the case of the sectional travel speeds of intra-city bus, it was analyzed that they were less accurate than the DSRC sectional travel speeds. In the future, it will be necessary to improve BIS process and make use of the travel information on intra-city buses collected in real time to find various ways of applying it as traffic information.

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

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.12
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• pp.1771-1779
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• 2016

In these days, the world is getting connected to the internet like a sophisticated net, such an environment gives a suitable environment for cyber attackers, so-called cyber-terrorists. As a result, a number of cyber attacks has significantly increased and researches to find cyber attack traffics in the field of network monitoring has also been proceeding. But cyber attack traffics have been appearing in new forms in every attack making it harder to monitor. This paper suggests a method of tracking down cyber attack traffic sources by defining relational information flow of traffic data from highest cascaded and grouped relational flow. The result of applying this cyber attack source tracking method to real cyber attack traffic, was found to be reliable with quality results.

• 한국ITS학회:학술대회논문집
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• 2008.11a
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• pp.11-24
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• 2008

• Journal of Korean Society of Transportation
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• v.11 no.1
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• pp.23-36
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• 1993

The two-lane, two-way highway simulation program(TWOPAS) is evaluated for Korean Highway Capacity Manual Study. TWOPAS program input variables, especially related vehicle performance, traffic flow relationship, car-following model and passing logic are examined and modified through the analysis results of our two-lane, two-way highway traffic characteristics. Simulation outputs with and without modification are compared with the field data. The results show that improved TWOPAS program(TWOPAS KI) is well suitable for simulating our two-lane, two-way highway condition.

• Journal of the korean Society of Automotive Engineers
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• v.9 no.1
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• pp.57-68
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• 1987

The driving pattern was studied in Seoul along nineteen representative routes using a test car equipped with all the instruments required for recording traffic flow and measuring fuel consumption. Speed histories, gear shift points, instantaneous fuel consumption rates, etc. were recorded and the data were anlyzed to determine the traffic characteristics for Seoul. The Seoul-14 Mode has been developed to simulated actual driving conditions in Seoul with respect to fuel consumption. The average speed of the Seoul-14 Mode is 30.1 Km/h and the Mode length is 11.94 Km.