• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.68-80
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• 2016

This study proposes the traffic prediction and optimal traffic control system based on cell transmission model and genetic algorithm in cloud environment. The proposed prediction and control system consists of four parts. 1) Data preprocessing module detects and imputes the corrupted data and missing data points. 2) Data-driven traffic prediction module predicts the future traffic state using Multi-level K-Nearest Neighbor (MK-NN) Algorithm with stored historical data in SQL database. 3) Online traffic simulation module simulates the future traffic state in various situations including accident, road work, and extreme weather condition with predicted traffic data by MK-NN. 4) Optimal road control module produces the control strategy for large road network with cell transmission model and genetic algorithm. The results show that proposed system can effectively reduce the Vehicle Hours Traveled upto 60%.

• Journal of Korean Society of Transportation
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• v.12 no.1
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• pp.97-116
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• 1994

Today advanced traffic management systems are required because of a high increase in traffic demand. Accordingly, the objective of this study is to take advantage of image processing systems and present image processing methods available for collection of the data on traffic characteristics, and then to investigate the possibility of traffic flow analysis by means of comparison and analysis of measured traffic flow. Data were collected at two places of Daegu city and Kyongbu expressway by using VTR. Rear view (down stream) and frontal view (up stream) methods were employed to compare and analyze traffic characteristics including traffic volume, speed, time-headway, time-occupancy, and vehicle-length, by analysis of measured traffic flow and image processing respectively. Judging from the results obtained by this study, image processing techniques are sufficient for the analysis of traffic volume, but a frame grabber equipped with high speed processor is necessary as well, with low level system judged to be sufficient for traffic volume analysis.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.1
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• pp.16-22
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• 2017

In this paper, we first introduce a mobile data traffic offload method called Local IP Access (LIPA) with femtocell networks. Then, we evaluate the traffic transmission time and probability of mobile data traffic that is transmitted to the core network (CN) when mobile devices transmit the mobile data traffic to indoor devices in three different scenarios, i.e., conventional systems, femtocell based systems, and femtocell and LIPA based systems. Through performance results, it is shown that the next generation mobile network with the femtocell and LIPA not only decrease the density of the mobile data traffic in CNs but also reduce the total transmission time of the mobile data traffic in indoor environments. That is, for the traffic transmission time, the conventional systems and femtocell based systems have 3 and 4 times higher than the femtocell and LIPA based systems, respectively, when the Internet delay is 10ms while 14 and 26 times higher than that, respectively, when the Internet delay is 100ms.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.1-13
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• 2021

In this study, a time series analysis technique was applied to calibrate and predict traffic data for various purposes, such as planning, design, maintenance, and research. Existing algorithms have limitations in application to data such as traffic data because they show strong periodicity and seasonality or irregular data. To overcome and supplement these limitations, we applied the SARIMA model, an analytical technique that combines the autocorrelation model, the Seasonal Auto Regressive(SAR), and the seasonal Moving Average(SMA). According to the analysis, traffic volume prediction using the SARIMA(4,1,3)(4,0,3) 12 model, which is the optimal parameter combination, showed excellent performance of 85% on average. In addition to traffic data, this study is considered to be of great value in that it can contribute significantly to traffic correction and forecast improvement in the event of missing traffic data, and is also applicable to a variety of time series data recently collected.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.6
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• pp.992-1001
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• 2022

The maritime traffic analysis has been conducted in various ways to solve problems arising from the complex marine environment. However, recent trends in the maritime industry, such as the development of the maritime autonomous surface ships (MASS), suggest that maritime traf ic analysis needs change. Accordingly, based on the studies conducted over the past decade for improvements, automatic identification system (AIS) data is mainly used for maritime traffic analysis. Moreover, the use of geographic information that directly af ects ship operation is relatively insufficient. Therefore, this study presented a method of using a combination of shape format data and AIS data to enhance maritime traffic analysis in preparation for the commercialization of autonomous ships. Consequently, extractable marine traffic characteristics were presented when shape format data were used for marine traffic analysis. This is expected to be used for marine traffic analysis for the introduction of autonomous ships in the future.

• The Journal of the Korea Contents Association
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• v.20 no.4
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• pp.25-37
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• 2020

As social costs of traffic congestion increase, various studies are underway to predict road speed. In order to improve the accuracy of road speed prediction, unexpected traffic situations need to be considered. In this paper, we propose a road speed prediction scheme considering traffic incidents affecting road speed. We use not only the speed data of the target road but also the speed data of the connected roads to reflect the impact of the connected roads. We also analyze the amount of speed change to predict the traffic congestion caused by traffic incidents. We use the speed data of connected roads and target road with input data to predict road speed in the first place. To reduce the prediction error caused by breaking the regular road flow due to traffic incidents, we predict the final road speed by applying event weights. It is shown through various performance evaluations that the proposed method outperforms the existing methods.

• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.183-189
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• 2011

This paper suggests a user based OST(Open Street Traffic) system that solves TPEG's one-way communication problem, UTIS's limited usage and DSRC's small traffic bandwidth. In current commercial TPEG service, only some service providers collect traffic information. Thus, it can't cover traffic status in local lanes And UTIS, which local governments and police supports, requires additional equipments. Currently, only taxi and official vehicles use this system. Therefore, new traffic service by mobile device and user's participation can provide very detail traffic information coupling with previous traffic systems. But in this new system, real-time high volume data can be a problem. So, in this paper, new data storage manager design(TDSM :Traffic Data Storage Manager) is suggested and its performance is measured against commercial DBMS.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.7
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• pp.759-766
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• 2020

In recent years, the maritime traffic environment has been changing in various ways, and the traffic volume has been increasing constantly. Accordingly, the requirements for maritime traffic analysis have become diversified. To this end, traffic characteristics must first be analyzed using vessel trajectory data. However, as the conventional method is mostly manual, it requires a considerable amount of time and effort, and errors may occur during data processing. In addition, ensuring the reliability of the analysis results is difficult, because this method considers the subjective opinion of analysts. Therefore, in this paper, we propose an automated method of traffic network generation for maritime traffic analysis. In the experiment, spatiotemporal features are analyzed using data collected at Mokpo Harbor over six months. The proposed method can automatically generate a traffic network reflecting the traffic characteristics of the experimental area. In addition, it can be applied to a large amount of trajectory data. Finally, as the spatiotemporal characteristics can be analyzed using the traffic network, the proposed method is expected to be used in various maritime traffic analyses.

• Journal of Korean Society of Transportation
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• v.33 no.4
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• pp.417-429
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• 2015

Evaluation of traffic data quality is a backbone of better traffic information and management systems because it directly affects the reliability of traffic information. This study developed an integrated index for evaluating the quality of archived intelligent transportation systems (ITS) data. Two novel indices including spatio-temporal consistency and severity of missing data were devised and integrated with existing indices such as availability and completeness. An evaluation framework was proposed based on the developed integrated index. Both analytical hierarchical analysis (AHP) technique and entropy method were adopted to derive mixed weighting values to be used for the integrated index. It is expected that the proposed methodology would be effectively used in enhancing the quality of traffic data as a part of traffic information system.

• Journal of Communications and Networks
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• v.12 no.4
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• pp.308-316
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• 2010

The problem of compressed sensing (CS) based multiple access is studied under the assumption of random data traffic. In many multiple access systems, i.e., wireless sensor networks (WSNs), data arrival is random due to the bursty data traffic for every transmitter. Following the recently developed CS methodology, the technique of compressing the transmitter identities into data transmissions is proposed, such that it is unnecessary for a transmitter to inform the base station its identity and its request to transmit. The proposed compressed multiple access scheme identifies transmitters and recovers data symbols jointly. Numerical simulations demonstrate that, compared with traditional multiple access approaches like carrier sense multiple access (CSMA), the proposed CS based scheme achieves better expectation and variance of packet delays when the traffic load is not too small.