• Journal of Korean Society of Transportation
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• v.20 no.3
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• pp.93-103
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• 2002

우리 국민의 교통수요행태를 분석하기 위하여 준이상수요체계(almost ideal demand system) 함수형태의 집계교통수요모형을 설정하였다. 대중교통수단으로서 시내버스, 시외버스, 택시, 기차, 전철이 그리고 개인교통수단으로서 연료비가 포함되었으며, 기타재화 및 서비스에 대한 소비지출이 함께 추정되었다. 추정에 이용된 자료는 통계청의 "도시가계연보"에 수록된 '전국 도시가구 소비지출'과 "물가통계"에 수록된 '전국 도시소비자 물가'이다. 추정결과 모형의 설명력을 나타내는 수정결정계수(adjusted-$R^2$)는 대부분 0.9 내외에서 높게 나타났다. 추정계수는 총 51개중에서 25개가 5% 수준에서 유의한 것으로 나타났다. 추정된 계수값을 이용하여 가격탄력성과 소득탄력성을 구하였다. 자기가격탄력성과 소득탄력성 추정치는 조금 높기는 하나 부호와 상대적 크기가 모두 예상과 일치하고 다른 연구결과들과 유사한 범위에 있다. 연료비에 대한 소득탄력성은 1.72로 가장 높게 나타났고, 대중교통수단은 0.03~0.49 사이에서 나타나므로 교통수단이 정상재임을 의미한다. 보상수요의 교차가격탄력성은 총 15개의 교차관계에서 12개의 관계가 상식과 일치한다. 다음 연구에서는 더 많은 시계열자료를 발굴하여, 장기간의 교통수요 변화에 대한 분석을 시도할 필요가 있다. 또한 초월대수함수나 동태함수 등 다양한 형태의 수요함수를 시도할 필요가 있다. 여러가지 형태의 교통수요함수추정을 통해서 우리 현실에 적합한 교통수요모형을 발견할 수 있을 것이다. 대도시와 중소도시 등 지역별 지출자료를 발굴하여 지역특성을 반영하는 교통수요함수의 추정도 필요하다.

• Journal of the Korean Society of Safety
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• v.4 no.1
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• pp.103-120
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• 1989

최근 도시교통계획분야에 있어서 교통수요의 예측모델 또는 교통정책의 평가 모델로서 비집계(非集計) 모델에 관한 연구가 진행되고 있다. 이 비집계모델은 개개의 의사결정단위에 있어서 선택행동을 영역마다 집계하는 것이 아니고 의사결정레벨의 데이터률 그대로 모델로 구성할 경우 이 데이터를 이용함으로써 의사결정단위의 선택행동을 모델화 할 수 있다는 특징을 갖고 있다. 한편 비집계모델의 사용목적은 여러가지로 생각되나 이것을 교통수요의 목적이나 교통정잭의 평가를 위한 모델로 이용할 때는 파라미터의 추정값이나 선택비율의 추정값에 대한 안정성이 매우 중요한 문제가 되고 있다.

• Journal of Korean Society of Transportation
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• v.26 no.2
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• pp.147-156
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• 2008

It has been widely known that there are so many factors making travel demand errors in transportation forecasting steps. One of the reasons may stem from the level of aggregation of zone and network in analysis process. This paper investigates the effect of level of aggregation considering with number of zones in travel demand forecasting by expanding or reducing the zone and network gradually. Numerical results show that the aggregation could not make a significant impact on the travel demand, while disaggregation does. These results imply that a careful manipulation is required to add or to reduce zones and links in transportation planning process.

• Proceedings of the KOR-KST Conference
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• 2007.11a
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• pp.163-169
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• 2007

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.2166-2178
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• 2010

The Korea Transportation Database (KTDB) is used to obtain data on the origin and destination (OD) of inter-city travel, which are currently used in railroad planning when estimating traffic demand. The KTDB employs the trip assignment method, whereby the total traffic volume researched for inter-city travel in Korea is divided into road, rail and air traffic, etc. However, as regards rail travel, the railroad stations are not identical to the existing zones or the connector has not been established because there are several stations in one zone as such, certain problems with the applicable methods have been identified. Therefore, estimates of the volume of railroad traffic using the KTDB display low reliability compared to other modes of transportation. In this study, these problems are reviewed and analyzed, and use of the aggregate model method to estimate the direct demand for rail travel is proposed in order to improve the reliability of estimation. In addition, a method of minimizing error in traffic demand estimation for the railroad field is proposed via an analysis of the relationship between the aggregate model and various social-economic indicators including population, distances, numbers of industrial employees, numbers of automobiles, and the extension of roads between cities.

• Journal of Korean Society of Transportation
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• v.11 no.3
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• pp.31-48
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• 1993

본 연구에서는 다른 기종점 통행표(Trip Matrices)들을 같은 교통망(Network)에 배정하였을 때 교통분배 결과의 차이점들을 분석하고 교통분배의 민감도를 비교하였다. 전통적인 4단계 교통수요 추정에 의해서 산출된 교통배분을 비교의 기본자료로 이용했다. 또한 본 연구에서는 교통배분의 결과를 평가하기 위해 주로 사용하는 측정효과들과 교통배분의 기법들(Traffic Assignment Techniques)의 민감도도 연구조사하였다. 본 연구를 통하여 총교통량(Total Trips)과 통행길이빈도(Trip Length Frequency)제약에 의해 임의로 선출된 기종점 통행표를 이용한 교통배분의 결과는 전통적인 4단계 교통수요 측정에 의해 산출된 교통배분 및 조사교통량(Counted Traffic Volumes)에 매우 유사한 결과가 나왔다. 결론적으로 죤별 통행발생량에서의 오차는 교통배분의 본성적인 집계특성(Aggregative Nature)에 의하여 그 심각성이 감소되는 경향이 있다. 이것은 즉 앞단계(Trip Generation and Distribution Phases)에서 전통적으로 요구되어지는 정밀도가 없어도 적절한 교통배분기법을 사용함으로써 좋은 결과를 산출할 수 있다는 것을 암시한다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.40-53
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• 2021

Recently, shared dockless e-scooter usage has rapidly increased, rather than the station-based shared mobility service, because of convenience. This transition leads to new social problems in urban areas such as increased traffic accidents and hindrance of pedestrian environments. In this study, we analyze the usage characteristics of shared e-scooters in Seoul, and identify factors influencing demand for shared e-scooters by developing a negative binomial regression model. As a result, the usage characteristics show that the average trip distance, the average trip duration, and the average trip speed were 1.5km, 9.4min, and 10.3km/h, respectively. Demographic factor, transport facility factors, land use factors, and weather factors have statistically significant impacts on demand for shared e-scooters. The results of this study will be used as basic data for suggesting effective operation strategies for areas with higher shared e-scooter demand and for establishing transport policies for facilitating shared e-scooter usage.

• Journal of Korean Society of Transportation
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• v.23 no.2
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• pp.25-36
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• 2005

In this study, we suggested a new approach method forecasting distribution demand of urban rail transit usign fuzzy control, with intend to reflect irregularity and various functional relationship between trip length and distribution demand. To establish fuzzy control model and test this model, the actual trip volume(production, attraction and distribution volume) and trip length (space distance between a departure and arrival station) of Daegu subway line 1 were used. Firstly, usign these data we established a fuzzy control model, nd the estimation accuracy of the model was examined and compared with that of generalized gravity model. The results showed that the fuzzy control model was superior to gravity model in accuracy of estimation. Therefore, wwe found that fuzzy control was able to be applied as a effective method to predict the distribution demand of urban rail transit. Finally, to increase the estimation precision of the model, we expect studies that define membership functions and set up fuzzy rules organized with neural networks.

• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.15-22
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• 2009

There exist some limits when we forecast urban railway demand by traditional 4 step model. The first reason is that the model based on socioeconomic data by an administrative unit, 'Dong', yields a 'Dong' unit trip matrix. But a 'Dong' often has two or more stations. The second reason is that urban railway demand by station would be affected rather by station access area on foot than by a 'Dong' unit. So the model based on 'Dong' characteristic data have some inaccuracies in itself. Owing to the limits of the model based on 'Dong' unit data, there exits some difficulty in forecasting urban railway demand by station. So this paper studied two alternatives. The first is to forecast the demand by using the data of station access area on foot rather than 'Dong' unit data. This needs too much time and effort to collect data and analyse them, while the accuracy of the model didn't improve a lot. The second is to adjust the location of 'Dong' centroid and the length of centroid connector link. By this way we can reflect the characteristics of station access area on foot under traditional 4 step model. Comparing the expected demand to the observed data for each station, the result looks like very similar.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.219-232
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• 2023

Mobility services need to change according to the regional characteristics of the target service area. Accordingly, analysis of mobility patterns and characteristics based on Origin-Destination (OD) data that reflect travel behaviors in the target service area is required. However, since conventional methods construct the OD data obtained from the administrative district-based zone system, it is hard to ensure spatial homogeneity. Hence, there are limitations in analyzing the inherent travel patterns of each mobility service, particularly for new mobility service like Demand Responsive Transit (DRT). Unlike the conventional approach, this study applies a data-driven clustering technique to conduct spatial analyses on OD travel patterns of regional mobility services based on reconstructed OD data derived from re-aggregation for original OD distributions. Based on the reconstructed OD data that contains information on the inherent feature vectors of the original OD data, the proposed method enables analysis of the spatial characteristics of regional mobility services, including public transit bus, taxi and DRT.