• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.661-663
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• 2014

Lighting that installed in large buildings detects a movement of passer using human-detecting sensor or occupancy sensor. It can turn on lighting automatically using sensor when there is any movement and turn off when there is no movement to reduce unnecessary power consumption. However, there is a problem of malfunction due to improper location of the sensor. Also the case of passage, even after passing through the passage, lighting is turned on for a long time. It does not reduce the power consumption efficiently. In this paper, we propose a method to control lighting by estimating the position of the passer. According to the result simulated in one passage, it is confirmed that the time of turning on the lighting is reduced about 7 minute compared to existing methods.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1995.04a
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• pp.100-109
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• 1995

철도는 대량수송 및 정시제 운행이라는 중요한 역할을 하면서도 다른 한편으로는 철도연변에 거주하고 있는 사람들에게 상당한 소음공해를 미쳐 정온한 생활환경을 누릴 권리를 침해하고 있음에도 불구하고 철도소음을 관리하는 기준이나 대책등이 아직 미미한 실정이다. 향후 5년 내에는 고속철도의 등장도 확실하지만 기존 재래식 철도에 대한 소음 실태 자료마저 충분치 않아 철도연변의 소음진동 문제를 해결하기 위한 기본적 수단인 소음 기준 제시를 위해서는 폭넓은 기초 자료확보와 새로운 관련연구가 요청되었다. 이러한 필요성에 따라 전기기관차를 중심으로 영동선, 중앙선, 태백선, 경인선, 경원선 및 대도시 도심지를 관통하는 호남선 및 경부선 중에서 측정환경이 양호한 22개 지역을 선정하여 기존 철도의 구간별 30분, 1시간, 2시간, 3시간 등가소음도를 측정하였고 선로의 조건, 열차의 종류 및 속도, 거리권별 등에 따른 개별열차 통행시의 소음특성을 조사하여 철도소음의 기준 설정과 방지대책 강구시에 활용할 수 있도록 하며, 열차 통행속도로부터 최고소음도를 추정하여 주변지역의 등가소음도를 산정할 수 잇는 예측식을 도출하여 측정방법 개정에 활용하고, 그리고 선로변에 위치한 공동주택을 대상으로 층별 철도소음 노출도와 열차통과시의 공동주택 실내.외의 소음도를 비교조사하여 벽체 차음 효과를 조사하였고 철도소음에 대한 주민반응 조사를 하였다.

• Journal of Korean Society of Transportation
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• v.23 no.7 s.85
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• pp.165-179
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• 2005

The object of this study is a development of a stochastic user equilibrium transit assignment algorithm for multiple user classes considering stochastic characteristics and heterogeneous attributes of passengers. The existing transit assignment algorithms have limits to attain realistic results because they assume a characteristic of passengers to be equal. Although one group with transit information and the other group without it have different trip patterns, the past studies could not explain the differences. For overcoming the problems, we use following methods. First, we apply a stochastic transit assignment model to obtain the difference of the perceived travel cost between passengers and apply a multiple user class assignment model to obtain the heterogeneous qualify of groups to get realistic results. Second, we assume that person trips have influence on the travel cost function in the development of model. Third, we use a C-logit model for solving IIA(independence of irrelevant alternatives) problems. According to repetition assigned trips and equivalent path cost have difference by each group and each path. The result comes close to stochastic user equilibrium and converging speed is very fast. The algorithm of this study is expected to make good use of evaluation tools in the transit policies by applying heterogeneous attributes and OD data.

• Journal of Korean Society of Transportation
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• v.27 no.1
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• pp.73-81
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• 2009

While various factors in passenger and freight demand analysis affect on destination choice, a key factor, in general. is an attractiveness measure by size variable (e.g., population. employment etc) in destination zone. In order to measure the attractiveness, some empirical studies suggested that disaggregate gravity model are more suitable than aggregate gravity model. This study proposes that truck travelers trip diary data among Korean commodity flow data could be used to estimate the behaviors of incorporating trip departure time, activity duration and attractiveness in destination. As a result, the main findings of size and distance variables coincide with the conventional gravity model having a positive effect of population variable and a negative effect of distance variable. Due to disaggregate gravity modeling, the unique findings of this study reports that small trucks are more likely to choose short distance and early morning, morning peak and afternoon peak departure time choice. On the other hand, large trucks are more likely to choose long distance and night time departure time choice.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.565-571
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• 2006

This study aimed to analyze access mode choice behavior for KTX Passengers. To fulfill the aims of this study, Dong-Daegu Station was selected as a station for a case study. This study takes place in two stages. These are (i) descriptive statistical analysis of transportation status before and after introduction of the KTX, (ii) empirical model estimation for analyzing access mode choice behavior. This study makes use of the data from travel survey from Daegu metropolitan area. The main part of the survey was carried out in the KTX Dong-Daegu station. The data was collected from a sample of 1,800 individuals. The survey data includes the information on travel from Dong-Daegu station to Seoul. From descriptive statistical analysis of transportation status before and after introduction of the KTX, it is found that revealed demand of the KTX is lower than that expected. Moreover, it is found that the low demand of the KTX stems from high cost for the KTX itself and inconvenience( including travel time and cost) of access mode. In order to analyze mode choice behavior for accessing Dong-Daegu station, multinomial logit model structure is used. For the model specification, a variety of behavioral assumptions about the factors which affect the access mode choice, were considered. From the empirical model estimation, it si found that access travel time and access travel cost are significant in choosing access mode. Given the empirical evidence, we see that improvement of access transportation system for Dong-Daegu station is very important for enhancing the use of KTX.

• Journal of the Korean Regional Science Association
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• v.32 no.4
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• pp.39-49
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• 2016

The main objective of this paper is to analyze university students' modal shift for commuting trip due to the introduction of new urban rail transit in a satellite city of metropolitan area. The paper uses SP(2011)/RP(2013) data collected from Yeungnam University in Gyeongsan City, which is a satellite city of Deagu Metropolitan City. So far few researches, especially using before-and-after individual SP/RP travel survey, have been conducted on analyzing university students' modal shift due to the introduction of new urban rail transit. For this research, some descriptive statistical analyses were conducted. Furthermore, some empirical logit models were estimated for analyzing factors affecting the modal shift. Finally, some important findings and policy implications are discussed. The significant findings from this research are summarized as follows. From the descriptive statistical analyses of SP and RP data, it is found that the rate of modal shift to rail transit is relatively high especially for bus travellers. Furthermore, from the empirical SP model estimation, it is found that time saving is the most important factor affecting the modal shift to urban rail transit. On the other hand, from the empirical RP model estimation, it is found that residential location is the most important factor affecting the modal shift to urban rail transit.

• Journal of Korean Society of Transportation
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• v.17 no.3
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• pp.97-116
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• 1999

The growing demand for the real time traffic information is bringing about the category and number of traffic collection mechanism in the era of ITS. There are, however, two problems in making data into information using various traffic data. First, the information making process of making data into the representative information, for each traffic collection mechanism, for the specified analysis periods is required. Second, the integration process of fusing each representative information into "the information" for each link out of each source is also required. That is, both data reduction and/or data to information process and information fusion are required. This article is focusing on the development of information fusing algorithm based on voting technique, fuzzy regression, and, Bayesian pooling technique for estimating the dynamic link travel time of networks. The proposed algorithm has been validated using the field experiment data out of GPS probes and detectors over the roadways and the estimated link travel time from the algorithm is proved to be more useful than the mere arithmetic mean from each traffic source.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.1
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• pp.101-116
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• 2017

This Study estimates the actual night traffic using the smart card data used by most of the public transportation users, and compares it with the current night bus routes by KT Telecom based on the night time call volume. In order to compare the current night bus and night trips evaluated by smart card data, we presented indicators related to the degree of matching, and estimated the volume of service currently provided. The unique approach of the study is that we chose subway station instead of bus stop for the unit of the study. Bus stops has their complexity in a way that stops with same name could belong to different administrative area depending on its direction. For this reason, we decided to use subway station and defined its adjacent administrative district as the scope of influence. Since night bus is the primary means of transportation during the late night, it is anticipated that they will be able to provide better service by calculating the actual traffic and selecting the routes.

• Journal of Korean Society of Transportation
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• v.28 no.2
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• pp.111-121
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• 2010

DHV (Design-Hour Volume) for the estimation of number of lanes is determined by design-hour factor (K). The design-hour factor is defined as the proportion between the 30th highest hourly volume and AADT and determines the level of road planning. However, the K-factor estimated by an existing method has a problem because the hourly volumes on holiday and weekend appear in the relatively low rank in real world in spite of expected high volumes. To improve this problem, this study make use of the concept of traffic demand in estimating the design-hour factor. After the congested hourly volumes transfer to traffic hourly demand, the K-factors are estimated on urban expressways and are compared to the existing K-factors. It is perceived that the new K-factors have more realistic values due to utilizing the traffic demand. reflecting the congested flow.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.63-75
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• 2018

A Service Area plays an important role in preventing accidents in advance by creating a space for long distance drivers or drowsy drivers to rest. Therefore, proper positioning of the expressway service area is essential, and it is important to analyze accurate demand forecasting and user travel behavior. Thus, this study analysis travel behavior and developed odel of the probability of using the service area by using the DSRC data collected by the RSE on the highway. According to the analysis, the usage behavior of highway service areas was most frequently when travel time was 90 minutes or more on weekdays and 70 minutes or more on weekends. The utilization rate of the service area estimated from the probability model of use of the rest area in this study was 1 % to 2 % error. The results of this study are meaningful in analyzing the behavior of the use of rest areas using the structured data and can be used as a differentiated strategy for selecting the location of rest areas and enhancing the service level of users.