• Proceedings of the KSR Conference
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• 2008.06a
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• pp.2109-2113
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• 2008

As the standard of living is higher, the passengers using public transportations desire better qualities of environment as well as more comfortable indoor environment. In case of train, the passengers' comfort in passenger cabin is one of the most important elements to be competitive with other transport systems. The indoor air quality of the cabin should be managed properly, because many passengers travel for a long time in the small space of $144\;m^3$. For proper management of the air quality, the heating, ventilation and air conditioning (HVAC) system is required for the ventilation of the compartment. To maintain comfortable environment in the compartment, the automatic ventilation system is needed to exchange the indoor air with fresh air or clean indoor air. In this study, we investigated the indoor air quality (PM-10, $CO_2$, and VOCs) in the compartment of train. In addition, type and pattern of PM-10 has been analyzed through the clustering analysis. Based on the analysis, we could found that the fine particulate matters in the compartment can be a serious hazard to human. To control the concentration of PM-10 and $CO_2$ air cleaners were developed. Through this study, it is expected that people who take a train will be in a more comfortable environment.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.4
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• pp.127-134
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• 2013

While there are many services that can check current traffic condition and application program such as bus arrival alarm are developed, since it only provide simple alarm and check level of information, it is still insufficient in many senses. Therefore, the program that try to develop in this study is the system that predict arrival time to destination and inform the bus passengers by applying real time traffic information. The system developed related to this study is still very inadequate. In the system developed in this thesis, when the user input the current bus number and destination using smart-phone, relevant server acquire the bus route information from bus information DB, and analyze real time traffic information based on the information from traffic information DB, and inform customer of expected arrival time to destination. In this thesis, traffic congestion can be eased off and regular operation of public transportation can be improved with reliable destination arrival alarm. Also, it is considered that pattern of bus users can be analyzed by using these information, and analyzing average transport speed and time of public transportation, travel time depending on various situation can give a boost to study related to transportation information and its development.

• Journal of Korean Society of Transportation
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• v.20 no.3
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• pp.149-158
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• 2002

For the purpose of preciously describing real time traffic pattern in urban road network, dynamic network loading(DNL) models able to simulate traffic behavior are required. A number of different methods are available, including macroscopic, microscopic dynamic network models, as well as analytical model. Equivalency minimization problem and Variation inequality problem are the analytical models, which include explicit mathematical travel cost function for describing traffic behaviors on the network. While microscopic simulation models move vehicles according to behavioral car-following and cell-transmission. However, DNL models embedding such travel time function have some limitations ; analytical model has lacking of describing traffic characteristics such as relations between flow and speed, between speed and density Microscopic simulation models are the most detailed and realistic, but they are difficult to calibrate and may not be the most practical tools for large-scale networks. To cope with such problems, this paper develops a new DNL model appropriate for dynamic traffic assignment(DTA), The model is combined with vertical queue model representing vehicles as vertical queues at the end of links. In order to compare and to assess the model, we use a contrived example network. From the numerical results, we found that the DNL model presented in the paper were able to describe traffic characteristics with reasonable amount of computing time. The model also showed good relationship between travel time and traffic flow and expressed the feature of backward turn at near capacity.

• Journal of Korean Society of Transportation
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• v.35 no.3
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• pp.197-209
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• 2017

With the advent of age that people spend more time and money on leisure activities, there is increasing interest in professional sport games. The location of large scale sport facilities has substantial impacts on existing transportation pattern because the facility attracts and generates massive traffic volume within a short period of time. This study aims to develop a mode choice model of leisure trips of which the destinations are a sport facility. A structured SP (stated preference) survey questionnaires were developed through an experimental design, and professional sport spectators were asked to state their preference in the choice of transport mode to the sport facility. The survey results show that public transportation is preferred to passenger cars for their trip to big sports event, implying that the convenience of back home trip after the event is an important factor of their mode choice. This study is a rare research on the trip pattern to sports complex in Korea, which provides policy implications on the provision of mass transit including subway system to large scale sport complexes. And it is also expected that this study contributes to future researches on leisure trip pattern.

• Journal of Korean Society of Transportation
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• v.33 no.3
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• pp.256-267
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• 2015

The intelligent transportation systems allow us to have valuable opportunities for collecting wide-area coverage traffic data. The significant efforts have been made in many countries to provide the reliable traffic conditions information such as travel time. This study analyzes the impacts of the fog weather conditions on the traffic stream. Also, a strategy for predicting the long-term traffic speeds is developed under foggy weather conditions. The results show that the average of speed reductions are 2.92kph and 5.36kph under the slight and heavy fog respectively. The best prediction performance is achieved when the previous 45 pattern cases data is used, and the 14.11% of mean absolute percentage error(MAPE) is obtained. The outcomes of this study support the development of more reliable traffic information for providing advanced traffic information service.

• Journal of the Korean Society for Railway
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• v.20 no.4
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• pp.529-538
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• 2017

There has been much interest in optimizing the halting patterns of high-speed trains, for example by introducing more non-stop trains to supply faster train service to the passengers, which could later bring about a discussion about introducing new high speed train service with differentiated price and service. In general, halting patterns can be considered by constructing an efficient line plan, in which all demand should be covered and the total travel time can be reduced as much as possible. In this study, we present a two-step process based on two optimization models. One is to minimize total kilometers of trains to run on each route ; this will be done using a line planning model under the assumption of all-stop patterns. Then, in the next step, the all-stop patterns are optimally decomposed into several halting patterns in order to minimize the total travel time. We applied the two-step process to the latest demand data in order to develop KTX halting patterns as well as to determine the frequency of each line and compare the current line plan with the optimized one.

• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.223-232
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• 2021

In general, stormwater flows to the road surface, especially in urban areas, and it is discharged through the drainage grate inlets on roads. The appropriate evaluation of the road drainage capacity is essential not only in the design of roads and inlets but also in the design of sewer systems. However, the method of road surface flow analysis that reflects the topographical and hydraulic conditions might not be fully developed. Therefore, the enhanced method of road surface flow analysis should be presented by investigating the existing analysis method such as the flow analysis module (uniform; varied) and the flow travel time (critical; fixed). In this study, the algorithm based on varied and uniform flow analysis was developed to analyze the flow pattern of road surface. The numerical analysis applied the uniform and varied flow analysis module and travel time as parameters were conducted to estimate the characteristics of rainfall-runoff in various road conditions using the developed algorithm. The width of the road (two-lane (6 m)) and the slope of the road (longitudinal slope of road 1 - 10%, transverse slope of road 2%, and transverse slope of gutter 2 - 10%) was considered. In addition, the flow of the road surface is collected from the gutter along the road slope and drained through the gutter in the downstream part, and the width of the gutter was selected to be 0.5 m. The simulation results were revealed that the runoff characteristics were affected by the road slope conditions, and it was found that the varied flow analysis module adequately reflected the gutter flow which is changed along the downstream caused by collecting of road surface flow at the gutter. The varied flow analysis module simulated 11.80% longer flow travel time on average (max. 23.66%) and 4.73% larger total road surface discharge on average (max. 9.50%) than the uniform flow analysis module. In order to accurately estimate the amount of runoff from the road, it was appropriate to perform flow analysis by applying the critical duration and the varied flow analysis module. The developed algorithm was expected to be able to be used in the design of road drainage because it was accurately simulated the runoff characteristics on the road surface.

• The Journal of Society for e-Business Studies
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• v.18 no.3
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• pp.211-222
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• 2013

Discovering zones which a1re sets of geographically adjacent regions are essential in sophisticated urban developments and people's movement improvements. While there are some studies that separately focus on movements between particular regions and zone discovery, they show limitations to understand people's movements from a wider viewpoint. Therefore, in this research, we propose a clustering based analysis method that aims at discovering movement patterns, which involves zones and their relations, based on a big data of smart card transaction systems. Moreover, the effectiveness of discovered movement patterns is quantitatively evaluated by using the proposed metrics. By using a real-world dataset obtained in Seoul metropolitan subway networks, we investigate and visualize hidden movement patterns in Seoul.

• Journal of Korean Society of Transportation
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• v.19 no.4
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• pp.97-108
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• 2001

A dynamic transportation management should be applied specially in AM peak because AM peak is more critical than PM peak in traffic volume and demand. AM peak trip can be characterized by commuting and schooling. which have the high level of usage on public transportation, and constraint on arrival time. So transportation management applied in AM peak could deal with a mode choice and an arrival time constrain. Researchers were involved in the dynamic transportation assignment models for management of congested traffic network. But, there were no models which considered a mode choice and an arrival time constrain should be included in management of AM peak. So there are limits to use exist models to control and analyze AM peak traffic. In this study, it is proposed the combined dynamic transportation model, considering a mode choice and the start time selection with arrival time constrains, based on Ran and Boyce's model. The proposed model is verified the compatibility by applying to the newly designed time space expanded network. The result shows that proposed model consistent with dynamic user optimal travel pattern. From this we certificate the applicability of the proposed model to control and analyze AM peak traffic.

• Journal of Korean Society of Transportation
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• v.24 no.3 s.89
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• pp.197-205
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• 2006

The study suggested a demand forecasting method which explicitly reflects transfer between various transport modes especially related light rail transit project with multi-modal transit system. The suggested method classifies several groups depending on characteristic of trips and applies different demand model for each group to explain travel pattern more realistically More specifically. the trips was classified by trips within the LRT route, trips between inside and outside of the LRT route. and through trips via the LRT route. The study also suggested a evaluation measurement of time saving due to the LRT construction, which are consistent along with the do-case and the do-nothing-case even though some mode shift could be happen after introducing the LRT.