• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.145-152
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• 2002

Real-time queueing information and/or predictive queue built-up information can be a good criterion in selecting travel options, such as routes, both for users, and for operators in operating transportation system. Provided properly, it will be a key information for reducing traffic congestion. Also, it helps drivers be able to select optimal roues and operators be able to manage the system effectively as a whole. To produce the predictive queue information, this paper proposes a predictive model for estimating and predicting queue lengths, mainly based on Kalman Filter. It has a structure of having state space model for predicting queue length which is set as observational variable. It has been applied for the Namsan first tunnel and the application results indicate that the model is quite reasonable in its efficacy and can be applicable for various ATIS system architecture. Some limitations and future research agenda have also been discussed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.4
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• pp.14-27
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• 2009

Collection of invaluable real-time traffic data becomes available under ubiquitous transportation sensor networks (UTSN). Various research efforts have been made to utilize such useful data for deriving more accurate and reliable traffic information. This study presented a novel concept of decentralized traffic information and method to process traffic data which are obtained from inter-vehicle communications under the UTSN. In addition, an experimental evaluation to investigate the feasibility of the proposed method using probe vehicle data. Predictive travel times were estimated and evaluated for the feasibility investigation. Technical issues were derived and discussed to fully implement the proposed system. The outcomes of this study would be used as a guideline in designing better next-generation traffic information systems.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.1
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• pp.61-72
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• 2005

In this paper, we develop anti-sway control in proposed techniques for an ATC system. The developed algorithm is to build the optimal path of container motion and to calculate an anti-collision path for collision avoidance in its movement to the finial coordinate. Moreover, in order to show the effectiveness in this research, we compared NNP PID controller to be tuning parameters of controller using NN with 2 DOF PID controller. The experimental results for an ATC simulator show that the proposed control scheme guarantees performances, trolley position, sway angle, and settling time in NNP PID controller than other controller. As a result, the application of NNP PID controller is analyzed to have robustness about disturbance which is wind of fixed pattern in the yard. Accordingly, the proposed algorithm in this study can be readily used for industrial applications

• Journal of Korean Society of Transportation
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• v.17 no.1
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• pp.141-157
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• 1999

This paper first reviews current practices of traveler information providing and provides some perspectives regarding the possible near term milestones in traveler information providing. Then, reviews of four types of prediction models: 1) dynamic traffic assignment (DTA) model; 2) statistical model; 3) simulation model; and 4) heuristic model are described in the sense that various prediction models are needed to support providing predictive traveler information in the near future. Next, the functional requirements and capabilities of the four types of prediction models are discussed and summarized along with some advantages and disadvantages of these models with reference to short-term travel time prediction. Furthermore, a comprehensive prediction procedure, which combines the four types of prediction models, is presented, together with the data requirements for each type of prediction model.

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

• Smart Media Journal
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• v.12 no.8
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• pp.18-25
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• 2023

The COVID-19 outbreak in 2020 caused continuous damage worldwode, especially the smart tourism industry was hit directly by the blockade of sky roads and restriction of going out. At a time when overseas travel and domestic travel have decreased significantly, the number of tourist hotels that are colsed and closed due to the continued deficit is increasing. Therefore, in this study, licensing data from the Ministry of Public Administraion and Security were collected and visualized to understand the operation status of the tourism and lodging industry. The machine learning classification algorithm was applied to implement the business status prediction model of the tourist hotel, the performance of the prediction model was optimized using the ensemble algorithm, and the performance of the model was evaluated through 5-Fold cross-validation. It was predicted that the survival rate of tourist hotels would decrease somewhat, but the actual survival rate was analyzed to be no different from before COVID-19. Through the prediction of the business status of the hotel industry in this paper, it can be used as a basis for grasping the operability and development trends of the entire tourism and lodging industry.

• Journal of Korean Society of Transportation
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• v.18 no.4
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• pp.75-85
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• 2000

The Purpose of this study is to analyze wether the composition of training sample have a relation with the Predictive ability and the learning results of ANNs(Artificial Neural Networks) fur predicting one cycle ahead of the queue length(veh.) in a signalized intersection. In this study, ANNs\` training sample is classified into the assumption of two cases. The first is to utilize time-series(Per cycle) data of queue length which would be detected by one detector (loop or video) The second is to use time-space correlated data(such as: a upstream feed-in flow, a link travel time, a approach maximum stationary queue length, a departure volume) which would be detected by a integrative vehicle detection systems (loop detector, video detector, RFIDs) which would be installed between the upstream node(intersection) and downstream node. The major findings from this paper is In Daechi Intersection(GangNamGu, Seoul), in the case of ANNs\` training sample constructed by time-space correlated data between the upstream node(intersection) and downstream node, the pattern recognition ability of an interrupted traffic flow is better.

• Geophysics and Geophysical Exploration
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• v.12 no.4
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• pp.289-298
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• 2009

Optimal data processing parameters were designed to attenuate multiples in seismic data acquired in the south-eastern area of the East Sea, in 2008. Bunch of multiples caused by shallow sea water depth were perceived periodically up to two way travel time of 1,750 ms at every 250 ms over seismic traces. We abbreviated sea bottom multiple as SBM, Peg-leg multiple as PLM, and free-surface multiple as FSM. To attenuate these multiples, seismic data processing flow was constructed including NMO, stack, minimum phase predictive deconvolution filter and wave equation multiple rejections (WEMR). Prevalent multiples were suppressed by predictive deconvolution and remaining multiples were attenuated by WEMR. We concluded that combining deconvolution with WEMR was effective to a seismic data of study area. Derived parameter can be applied to the seismic data processing on adjacent survey area.