• 한국항공운항학회:학술대회논문집
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• 2016.05a
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• pp.269-275
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• 2016

This paper considers the arrival, airport and departure capacity as a whole, through which, the network effect between airports is fully emphasized, the flight action is coordinated, and the flight demand pattern is reasonably assigned. The optimization problem of flight queues in multi-airport is studied in detail; the mathematical model of multi-airport opening non-real time flow management in terminal area is established, and related problems such as the parameters, the simplification and the solving of the model are discussed in detail to some extent. Appropriate decision making variables are taken to make the multi-airport network system linear 0-1 integer programming model, thus, the solving of the model is available and the central flow management is realized. The heuristic implicit enumeration presented in this paper can effectively solve this kind of problems. Through the simulation of some airports network system, we not only validate the algorithm presented in this paper, but also give a deep analysis of the results, which would produce reference for later practicable use. The simulation proves that this algorithm offers a good way to settle the problem of multi-airport flight queue optimization in air traffic management automation system in terminal area.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.12
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• pp.789-794
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• 2008

Recently, much attention has been paid in the field of defrosting because clear windshield in vehicle without effecting the thermal comfort is realized essentially. Then in winter, defrosting performance is one of the important factors in vehicle design to make certain driver's view. In this study, the velocity profile, temperature distribution and frost melting pattern on the windshield screen have been predicted in three dimensional geometry of an automobile interior. Numerical analyses predict a detailed description of fluid flow and temperature patterns on the inside windshield screen, utilizing the flow through defroster nozzle. Numerical prediction established a good defrosting performance with the standard distance ratio and the defroster nozzle angle ranging from $30^{\circ}$ to $40^{\circ}$, which satisfy the condition of National Highway Traffic Safety Administration (NHTSA) completely.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.2
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• pp.1-11
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• 2014

In this paper, travel speed patterns were deducted based on historical DSRC travel speed data using Decision Tree technique to improve availability of the massive amount of historical data. These patterns were designed to reflect spatio-temporal vicissitudes in reality by generating pattern units classified by months, time of day, and highway sections. The study area was from Seoul TG to Ansung IC sections on Gyung-bu highway where high peak time of day frequently occurs in South Korea. Decision Tree technique was applied to categorize travel speed according to day of week. As a result, five different pattern groups were generated: (Mon)(Tue Wed Thu)(Fri)(Sat)(Sun). Statistical verification was conducted to prove the validity of patterns on nine different highway sections, and the accuracy of fitting was found to be 93%. To reduce travel pattern errors against individual travel speed data, inclusion of four additional variables were also tested. Among those variables, 'traffic condition on previous month' variable improved the pattern grouping accuracy by reducing 50% of speed variance in the decision tree model developed.

• The Journal of the Korea Contents Association
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• v.5 no.6
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• pp.10-19
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• 2005

It may not be strange to anticipate that the forth-coming epoch of electronic government would bring us lots of convenience on account of ubiquitous environment with mobile devices. Such environment enables us to access the up-to-date information anytime and also a worker to carry out administration services to perform one's line of duty at anytime with electronic, handy devices such as PDA. What we now recognize from the field of electronic traffic administration services is that the office work flow as well as the public services has been remarkably improved by using of not only text but video and image information under the distributed, mobile environment. One of key requirements of this kinds of services is the feature of exchanging various information among multiple information publishers and subscribers. We call this feature Messaging Services generally The study in this paper focuses on the architecture design of the Messaging Engine software, complying with the pattern-oriented software architecture design methodology. And our contribution also goes to the discovery of three architecture patterns found in the design process and the efficient multi-threading architecture compared to one of the Messaging Engine solutions.

• Journal of Advanced Navigation Technology
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• v.27 no.6
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• pp.888-896
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• 2023

When an aircraft is landing, it is expected that the aircraft will follow a specified approach procedure and then land at the airport. However, depending on the airport situation, neighbouring aircraft or the instructions of the air traffic controller, there can be a deviation from the specified approach. Detecting aircraft approach patterns is necessary for traffic flow and flight safety, and this paper suggests clustering techniques to identify aircraft patterns in the approach segment. The Gaussian Mixture Model (GMM), one of the machine learning techniques, is used to cluster the trajectories of aircraft, and ADS-B data from aircraft landing at the Gimhae airport in 2019 are used. The aircraft trajectories are clustered on the plane, and a total of 86 approach trajectory patterns are extracted using the centroid value of each cluster. Considering the correlation between the approach procedure pattern and overshoots, the distribution of overshoots is calculated.

• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.115-126
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• 2009

The lane-change behavior usually consists of discretionary lane-change and mandatory lane-change types. For the first type, drivers change lanes selectively to maintain their own driving condition and the second type is the case that the drivers must change the current lane, which can occur in recurrent congestion sections like merging and weaving sections. The mandatory lane-change behavior have a great effect on the operation condition of freeway. In this paper, we first generate data such as traffic volumes, speeds, densities, and the number of lane-change within the merging and weaving sections using the data of individual vehicle collected from time-lapse aerial photography. And then, the data is divided into the stable and congested flow by analyzing the speed variation pattern of individual vehicles. In addition, the number of lane-changing from ramp to mainline within every 30-meter interval is investigated before and after traffic congestion at study sites and the distribution of lane-changing at each 30-meter point is analyzed to identify the variation of lane-changing ratio depending on the stable and congested flows. To recognize the effect of mainline flow influenced by ramp flow, this study also analyzes the characteristics of the lane-changing distributions within the lanes of mainline. The purpose of this paper is to present the basic theory to be used in developing a lane-changing model at the merging and weaving sections on freeways.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.7
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• pp.297-306
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• 2017

Citizens want more accurate forecast information using Bus Information System. However, most bus information systems that use an average based short-term prediction algorithm include many errors because they do not consider the effects of the traffic flow, signal period, and halting time. In this paper, we try to improve the precision of forecast information by analyzing the influencing factors of the error, thereby making the convenience of the citizens. We analyzed the influence factors of the error using BIS data. It is shown in the analyzed data that the effects of the time characteristics and geographical conditions are mixed, and that effects on halting time and passes speed is different. Therefore, the halt time is constructed using Generalized Additive Model with explanatory variable such as hour, GPS coordinate and number of routes, and we used Hidden Markov Model to construct a pattern considering the influence of traffic flow on the unit section. As a result of the pattern construction, accurate real-time forecasting and long-term prediction of route travel time were possible. Finally, it is shown that this model is suitable for travel time prediction through statistical test between observed data and predicted data. As a result of this paper, we can provide more precise forecast information to the citizens, and we think that long-term forecasting can play an important role in decision making such as route scheduling.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.4
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• pp.189-196
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• 2017

BIS(Bus Information System) provides the different information related to buses including predictions of arriving times at stations. BIS have been deployed almost all cities in our country and played active roles to improve the convenience of public transportation systems. Moving average filters, Kalman filter and regression models have been representative in forecasting the arriving times of buses in current BIS. The accuracy in prediction of arriving times depends largely on the forecasting algorithms and traffic conditions considered when forecasting in BIS. In present BIS, the simple prediction algorithms are used only considering the passage times and distances between stations. The forecasting of arrivals, however, have been influenced by the traffic conditions such as traffic signals, traffic accidents and pedestrians ets., and missing data. To improve the accuracy of bus arriving estimates, there are big troubles in building models including the above problems. Hidden Markov Models have been effective algorithms considering various restrictions above. So, we have built the HMM forecasting models for bus arriving times in the current BIS. When building models, the data collected from Sunchean City at 2015 have been utilized. There are about 2298 stations and 217 routes in Suncheon city. The models are developed differently week days and weekend. And then the models are conformed with the data from different districts and times. We find that our HMM models can provide more accurate forecasting than other existing methods like moving average filters, Kalmam filters, or regression models. In this paper, we propose Hidden Markov Model to obtain more precise and accurate model better than Moving Average Filter, Kalman Filter and regression model. With the help of Hidden Markov Model, two different sections were used to find the pattern and verified using Bootstrap process.

• Journal of Navigation and Port Research
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• v.41 no.6
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• pp.445-450
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• 2017

It is necessary to set a route to reflect the traffic flow for the safety of the traffic vessels. This ongoing analysis is needed to ensure that the vessels comply with a route. The purpose of this study is to discover the problems of the recommended route vicinity for Wando Harbor and suggest an improvement plan. We used a support vector machine based on the ship's trajectory to establish an efficient route center line. Since the vessels should navigate to the starboard side, with reference to the center line of the recommended route, the trajectories of the vessels were divided into two clusters. The support vector machine is being used in many fields such as pattern recognition, and it is effective for this binary classification. As a result of this study, about 79.5 % of the merchant eastbound ships in a 2.4 NM distance to Jangjuk Sudo did not observe the recommended route, so the risk of collision always existed. The contraflow traffic rate of the route of the eastbound ships decreased from 79.5 % to 30.9 % when the recommended route was reset about 300 meters to the north, from its present position. The support vector machine applied in this study is expected to be applicable, to effectively set the route center line because the ship trajectories can be classified into two clusters.

• Spatial Information Research
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• v.19 no.4
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• pp.11-20
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• 2011

In accordance with low carbon and green growth paradigm, a subway is one of major public transit systems for resolving traffic congestion and decreasing traffic accidents. In addition, as subway networks expand, passengers' travel pattern in the subway network change and consequently affect the urban structure. Generally, new subway route has been planned and developed, mainly considering a travel demand forecast. However, it is desired to conduct an empirical analysis on the forecast model regarding change of travel accessibility and passenger demand pattern according to new subway line. Therefore, in this paper, an alternative method, developed based upon a spatial syntax model, is proposed for evaluating new subway route in terms of passenger's mobility and network accessibility. In a case study, we constructed subway network data, mainly targeting the no 9 subway line opened in 2009. With an axial-map analysis, we calculated spatial characteristics to describe topological movement interface. We then analyzed actual modal shift and change on demand of passengers through the number of subway passenger between subway stations and the number of passenger according to comparative bus line from Smart Card to validate suggested methods. Results show that the proposed method provides quantitative means of visualizing passenger flow in subway route planning and of analyzing the time-space characteristics of network. Also, it is expected that the proposed method can be utilized for predicting a passengers' pattern and its impact on public transportation.