• Proceedings of the KOR-KST Conference
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• 1998.10b
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• pp.466-466
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• 1998

도로 교통의 혼잡이 나날이 증가되고 있는 현실 상황에서 이를 해결하기 위한 새로운 도로의 무제한적 건설은 정보의 예산절약, 필요한 도로용지 확보의 어려움, 환경오염 문제 등으로 인해 현실적인 한계에 이르렀다. 따라서, 이러한 도로의 혼잡상황에 효과적으로 대처하기 위해서는 승용차를 이용하고자 하는 수요를 대량수송이 가능한 대중교통 이용수요로 전환시켜야 하며, 이를 위해서는 대중교통의 서비스수준 제고 및 운영 관리 체계 등의 개선이 필요하다. 이를 위한 전략적 및 운영적 측면에서의 대중교통계획은 미래 대중교통수요의 정확한 예측을 전제로 하여 수립되며, 이러한 수요의 예측은 필수적으로 현실을 보다 더 정확하게 묘사해 줄 수 있는 통행배정모형을 필요로 한다. 대중교통 통행배정은 규칙적인 배차시간과 정해진 노선을 운행하는 고정서비스 시스템으로 구성되어 있어서 한 링크 상에서도 여러 개의 운행노선을 고려해야 하기 때문에 승용차 통행배정과는 독립적으로 취급되어 왔으며, 이로 인해 그 동안 많은 연구가 선행되어 있지 않은 실정이다. 본 연구는 교통예측 프로그램 중의 하나인 EMME/2에서 사용하고 있는 대중교통수요 통행배정 모형인 최적전략모형(Optimal Strategy Model)의 단점을 보완하기 위한 것이다. 최적전략모형은 수요 배정시, 최적전략에 속하는 경로들에 대해 단순히 운행횟수에 비례하여 수요를 배정함으로 인해서, 예를 들면 운행횟수는 많지만 환승이 많은 경로에 수요를 많이 배정하는 것과 같은 비현실적인 결과가 발생하기도 한다. 본 연구는 이를 개선하기 위해서, 두 가지 대안을 제시했다. 먼저, 노선배정에 우선되는 최적경로 탐색시 환승노드에서의 환승에 대한 벌점을 그 노선의 운행회수에 줌으로써 환승이 많은 경로에 수요의 배정이 적게 되도록 하는 방법과 두 번째로 수요의 배정시 운행횟수가 아닌 목적지까지의 통행시간과 대시시간에 따른 확률적 배분을 통해 기존 모형의 단점을 보완하고자 했다.

• Journal of Korean Society of Transportation
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• v.21 no.6
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• pp.43-55
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• 2003

This paper presents a new method for estimating potential transit ridership residential population and number of employees that have accesses to transit services. A standard procedure that can be used to determine transit accessibility by pedestrians ad automobiles are developed to improve its transit demand forecasting capability. The analysis results are compared with those from the traditional buffer method as well as the network ratio method. It was found that the proposed method is more accurate than the traditional methods. The new method can be used to better estimate the "Walk Access" transit trips and "Auto Access" transit trips in the Mode Choice Model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.1-11
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• 2016

The purpose of this study is to analyze the effect of public transit accessibility on the Carsharing use demand. By utilizing the rental historical DB of Greencar which is operated in Suwon city and public transit GIS DB, the use demand models for Carsharing by rental offices are built and analyzed in accordance with public transit accessibility. The result indicates 73% of walking as a majority, 3% cycling, and 20% using buses and urban railways to access Carsharing rental offices. The goodness of fit of Carsharing use models reflecting accessibility to buses and railways is verified as 0.818 which proves that public transit accessibility is a significant variable. Therefore, it is verified that installing Carsharing rental offices where public transit transfer is convenient can possibly increase the use demand. Especially, while accessibility to buses is verified as a significant variable out of other public transit means, the accessibility to urban railways is verified as not significant. This suggests that a variety of complementary policies such as transfer discount policy and one-way transfer return policy are necessary in between urban railways and Carsharing in order to promote mutual use demand in accordance with the other public transit means. This study result is yet the basic research on Carsharing, however it is expected to contribute to improvement of transfer demand in between different public transit means.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4D
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• pp.467-472
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• 2009

Even if Seoul City administration improved its public transportation service, transportation model share in seoul has not been increased. Subway user is also decreasing. Therefore, policy transition into TOD(Transit Oriented Development) should be applied in oder to enhance subway modal share. This paper develops a influencing model by using variables of transportation demand and supply. In addition, it provides major influencing factors for users in subway station area and level of transportation supply based on the analysis results. The results show that: first, cluster analysis presents that traffic pattern is proved to be different according to land use characteristics(residence, non-residence); second, main transportation variables such as transferring distance, the number of bus stop, the number of short distant bus lines, and the number of bicycle are more supplied in residential area compared to non-residential areas; third, the number of lines, bus dispatching interval, operating time, and distance between subway stations are more supplied in non-residential areas than residential areas. All in all, the results will be useful for providing priority of considerations in case of decision-making on public transportation policy in subway station area.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.6
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• pp.2493-2501
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• 2013

Various schemes of transportation demand management(TDM) to discourage the use of cars and enhance public transit performance have been implemented in large cities. Nevertheless, policy effects in reducing car have not been satisfactory. Car-dependent travelers who tend to keep driving cars regardless of the change of the trip circumstances as such increase of travel time and cost according to car use or improvement of public transit service may be due to not according to utility reflecting mode-specific impedance and their own socio-economic characteristics. In this study, travelers were classified into four groups by their choice frequency of private car and public transit in unspecified multiple trip(car-dependent, car-choice, public transit-choice, public transit-dependent class). And the characteristics of each group were comparative analyzed. The results show that the group of a higher car-dependent is a higher priority on convenience and comfortability of the car when making decisions and the group of a lower of car-dependent is likely to change to public transit.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.2
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• pp.80-93
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• 2018

Public transit services are generally analyzed based on the correlation of demand and supply. The computation of supply uses accessibility while demand uses travel demands estimation based on residential population. However, the traditional demand estimation has a limitation in analysing in micro-scale compared to the smartcard data traffic. This study analyzed potential improvement of public transit services using smartcard traffic data. The supply of transportation was defined using time distance accessibility. Also, time loss was calculated in those origin destination(OD) pairs where time distance accessibilities are relatively low. The proposed method was applied at Seoul. The results showed that the areas where OD pairs need improvement include Seodaemun-gu, Guro-gu and Nowon-gu.

• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.25-35
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• 2008

The ridership and transit systems are influenced by the expansion of metro-rail in Seoul metropolitan area. However, it has been difficult to measure its precise quantitative influences. Also effective policy implementations have been limited due to the lack of practical evidences. Thus an empirical analysis for an operating metro-rail is essentially required. In this regard, this study examines the impact of the Jungang line on transportation system, whose metro-rail block has been recently started new service. The main interest of this study is to find out the changes of ridership and to forecast the ridership changes by the metro-rail service. The results indicate that the effect on auto users is less than that of bus users. The auto demand is decreased by 33.3% and the bus demand by 66.6%. Additionally, its influence on Gyeonggi-do bus was greater compared with that on the Seoul bus. From questionnaire survey, this results could be confirmed. To sum up, the metro-rail gives less influences on auto users, while it gives greater influences on bus users.

• Journal of Korean Society of Transportation
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• v.26 no.2
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• pp.109-119
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• 2008

The number of card users has grown steadily after the adaption of smart card. Considering the diverse information from smart card data, the increase of card usage rate leads to various useful implications meaning in travel pattern analysis and transportation policy. One of the most important implications is the possibility that the data enables us to generate transit O/D tables easily. In the case of generating transit O/D tables from smart card data, it is necessary to filter data error and/or data missing. Also, the correction of data missing is an important procedure. In this study, it is examined to compute the level of data error and data missing, and to correct data missing for transit O/D generation.

• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.656-659
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• 2017

현대 사회에서는 다양한 이동수단 중 지하철, 버스 등의 대중교통에 대한 수요가 높은 편이다. 본 연구의 배경이 되는 서울특별시의 경우에는 출퇴근 시, 과반 수 이상이 대중교통을 이용한다. 대중교통 이용량에는 날씨, 평일-주말, 연착, 도로현황 등 여러 가지에 원인을 둔다. 본 연구에서는 여러 요인 중에서도 날씨 데이터(기온, 강수량, 미세먼지)에 초점을 두어, 날씨에 따른 대중교통 이용량의 변화양상을 학습하여 예측하는 연구를 진행한다. 서울특별시 25개 자치구마다의 날씨 데이터와 대중교통 이용 데이터를 이용하여 Regression을 통한 데이터 학습을 진행하였으며, 학습된 모델을 통한 날씨에 따른 서울특별시 대중교통 이용량 예측에 따른 평균 오차율은 15.49%로 낮은 오차율을 가진다. 본 연구 결과는 날씨에 따른 버스와 지하철의 배차 간격 조절 등의 대중교통 배치 판단 결정에 기초자료로 사용될 것으로 기대된다.