• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.219-226
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• 2004

본 연구는 지속적인 여객 및 화물량의 증가로 기존 수송수단이 포화에 이른 실정에 새로운 교통수단으로 추진한 고속철도 사업에 대해, 고속철도 개통 후 단기간에 드러난 이용현황 및 문제점을 도출해 기선방안을 제시하고자 한다. 이를 위해 관련 단체 및 기관의 자료를 수집 분석하였으며, 설문조사를 수행하여 결과를 도출하였다. 또한 광범 위한 고속철도 사업의 특성아래 여객 부문에 대한 대중교통 측면으로 연구의 범위를 한정하였다. 고속철도 개통 후, 여객 및 화물 수송의 형태에는 단기간이나마 큰 변화가 있는 것으로 나타났으나 그에 반해 고속철도의 이용에 있어서 주목할 만한 문제점 또한 조사되었다. 주요 사항으로는 역방향 유해성, 일반열차로의 불편전이, 터널통과시의 소음 등으로서 이는 개통 초기 고속철도에 대한 그릇된 대국민 인식을 가져오게 함과 동시에 향후 개인들간 교통수단 선택에 있어서까지 그릇된 영향을 끼칠 수 있다. 현재 각각의 문제점에 대한 개선방안으로 일반열차 확대 및 할인혜택, 점진적인 순방향 좌석으로서 교체 및 소음 저감방안을 위한 연구 용역 등이 실행되거나 준비되고 있으나 그에 대한 뚜렷한 개선 징후는 아직 미미한 상태로 분석되고 있다. 본 연구에서 실시한 설문조사 결과 아직까지는 고속철도에 대한 인식이 긍정적인 수준을 보이고 있으나 개별 문제점에 대한 좀더 깊은 고찰과 개선안 제시가 이루어진다면 향후 고속철도에 대한 대국민 인식을 한 단계 더 높여, 그 이용을 활성화 시킬 수 있는 좋은 기회가 될 것으로 판단된다.

• Journal of the Society of Disaster Information
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• v.18 no.3
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• pp.589-599
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• 2022

Purpose: The purpose of this study is to quantitatively identify the environmental contribution generated by urban rail users in the metropolitan area. Method: As for the analysis method, the mode choice and assignment of the traffic demand analysis were repeatedly performed on the assumption that each line was not opened for the metropolitan urban railway lines 1 to 9. After that, the environmental contribution according to changes in demand for the road was analyzed. Result: The total amount of carbon dioxide emissions and benefits were found to be the largest for subway line 1. However, when considering the number of stations and length, it was analyzed that the environmental contribution was the greatest in Metro Line 4. Conclusion: Measures to promote the use of public transportation are representative of environmental improvement policies, but there is a limit in that it is difficult for actual users/non-users to feel it. Therefore, it is judged that it is necessary to quantitatively present the effect in order to improve and spread awareness of the environment.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.4
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• pp.897-905
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• 2015

This research suggested the traffic signal calculation model of active transit signal priority using a shockwave model. Using this signal priority timing optimization model, the shockwave area is computed under the condition of Early Green and Green Extension among active transit signal priority techniques. This study suggested the speed estimation method of backward shockwave using average travel time and intersection passing time. A shockwave area change is calculated according to signal timing change of transit signal priority. Moreover, this signal timing calculation model could determine the optimal signal priority timings to minimize intersection delay of general vehicles. A micro simulation analysis using VISSIM and its user application model ComInterface was applied. This study checked that this model could calculate the signal timings to minimize intersection delay considering saturation condition of traffic flow. In case studies using an isolated intersection, this study checked that this model could improve general vehicle delay of more over ten percentage as compared with equality reduction strategy of non-priority phases. Recently, transit priority facilities are spreading such as tram, BRT and median bus lane in Korea. This research has an important significance in that the proposed priority model is a new methodology that improve operation efficiency of signal intersection.

• Journal of Korean Society of Transportation
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• v.35 no.6
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• pp.481-498
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• 2017

Travel time reduction benefit is the most important benefit item in the feasibility study of transportation infrastructure investment projects and calculated by using the value of travel time. The current feasibility study guideline (5th edition) calculate the value of non-business ravel time in a metropolitan area, using the ratio of the value of non-business travel time to business travel time calculated based on the nationwide inter-regional traffic survey data of 1999. The characteristics of metropolitan trips are different from those of nationwide regional trips. Metropolitan trips have frequent transfers between multiple public transits and long-time commuter trips. Therefore, this research aims to calculate the value of travel time reflecting traffic characteristics in a metropolitan area by improving the limitation of current calculation methods. To reflect these characteristics, this research extracts commuter trips from non-business trips and calculates the value of travel time for commuter trips. The results of the likelihood ratio test for the commuter trip model and the non-business trip model are found to be statistically significant. An integrated public transportation model was also estimated in this study to reflect the trip conditions of the Seoul metropolitan area integrated fare system. The results of comparing coefficients between bus and subway in the integrated public transit model indicated that there were no statistically significant differences between the two modes.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.4
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• pp.81-99
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• 2020

Origin-destination data have been collected and utilized for demand analysis and service design in various fields such as public transportation and traffic operation. As the utilization of big data becomes important, there are increasing needs to store raw origin-destination data for big data analysis. However, it is not practical to store and analyze the raw data for a long period of time since the size of the data increases by the power of the number of the collection points. To overcome this storage limitation and long-period pattern analysis, this study proposes a methodology for compression and origin-destination data analysis with the compressed data. The proposed methodology is applied to public transit data of Sejong and Seoul. We first measure the reconstruction error and the data size for each truncated matrix. Then, to determine a range of principal components for removing random data, we measure the level of the regularity based on covariance coefficients of the demand data reconstructed with each range of principal components. Based on the distribution of the covariance coefficients, we found the range of principal components that covers the regular demand. The ranges are determined as 1~60 and 1~80 for Sejong and Seoul respectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.2
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• pp.1-12
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• 2016

This paper is to analyze characteristics of transfer trips and to identify impacts of land use on them. Using the smart transport card data of Seoul on a weekday in April 2013, we explored general characteristics of the transfer trips such as spatial and temporal distributions, transfer types, and geographical patterns of transfer trips. Then, the multiple regression model for the transfer trips was developed, considering land use as well as socio-economic variables as explanatory ones. For the characteristics of the transfer trips, their ratio to the total trips accounts for 26.7%. Nearly 87% of the trips are one-time transferred, and 64.7% are bus-subway transfer trips. In addition, the transfer trips are more likely to appear nearby subway stations and business facilities. The regression model indicates that land use variables such as the floor areas of business facilities and department stores and mixed land use index significantly positively affect the transfer trips. Our results can be used as basic data for choosing feasible locations of multi-modal transfer centers in urban areas.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.1-19
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• 2023

Bikes have recently emerged as an alternative to carbon neutrality. To understand the demand for public bikes, we endeavored to estimate travel frequency of public bike by considering the intermediate stops. Using the GPS trajectory data of 'Ttareungyi', a public bike service in Seoul, we identified a stay point and estimated travel frequency reflecting population, land use, and physical characteristics. Application of map matching and a stay point detection algorithm revealed that stay point appeared in about 12.1% of the total trips. Compared to a trip without stay point, the trip with stay point has a longer average travel distance and travel time and a higher occurrence rate during off-peak hours. According to visualization analysis, the stay points are mainly found in parks, leisure facilities, and business facilities. To consider the stay point, the unit of analysis was set as a hexagonal grid rather than the existing rental station base. Travel frequency considering the stay point were analyzed using the Zero-Inflated Negative Binomial (ZINB) model. Results of our analysis revealed that the travel frequency were higher in bike infrastructure where the safety of bike users was secured, such as 'Bikepath' and 'Bike and pedestrian path'. Also, public bikes play a role as first & last mile means of access to public transportation. The measure of travel frequency was also observed to increase in life and employment centers. Considering the results of this analysis, securing safety facilities and space for users should be given priority when planning any additional expansion of bike infrastructure. Moreover, there is a necessity to establish a plan to supply bike infrastructure facilities linked to public transportation, especially the subway.

• The Journal of Bigdata
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• v.2 no.2
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• pp.1-7
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• 2017

Intelligent transportation system (ITS) has been introduced to maximize the efficiency of operation and utilization of the urban traffic facilities and promote the safety and convenience of the users. With the expansion of ITS, various traffic big data such as road traffic situation, traffic volume, public transportation operation status, management situation, and public traffic use status have been increased exponentially. In this paper, we derive structural characteristics of urban traffic according to the vehicle flow by using big data network analysis. DSRC (Dedicated Short Range Communications) data is used to construct the traffic network. The results can help to understand the complex urban traffic characteristics more easily and provide basic research data for urban transportation plan such as road congestion resolution plan, road expansion plan, and bus line/interval plan in a city.

• Journal of Internet Computing and Services
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• v.21 no.2
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• pp.9-18
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• 2020

In the field of image processing, a method of detecting and counting passengers as moving objects when getting on and off the bus has been studied. Among these technologies, one of the artificial intelligence techniques, the deep learning technique is used. As another method, a method of detecting an object using a stereo vision camera is also used. However, these techniques require expensive hardware equipment because of the computational complexity of used to detect objects. However, most video equipments have a significant decrease in computational processing power, and thus, in order to detect passengers on the bus, there is a need for an image processing technology suitable for various equipment using a relatively low computational technique. Therefore, in this paper, we propose a technique that can efficiently obtain the number of passengers on the bus by detecting the contour of the object through the background subtraction suitable for low-cost equipment. Experiments have shown that passengers were counted with approximately 70% accuracy on lower-end machines than those equipped with stereo vision camera.