• Journal of Korean Society of Transportation
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• v.24 no.7 s.93
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• pp.91-100
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• 2006

Travel Demand Forecasting (TDF) is an essential and critical process in the evaluation of the highway improvement Project. The four-step TDF Process has generally been used to forecast travel demand and analyze the effects of diverted travel demand based on the given Origin-Destination trips in the future. Transportation system improvements, however, generate more travel, Induced Travel Demand (ITD) or latent travel demand, which has not been considered in the project evaluation. The Purpose of this study Is to develop a model which can forecast the ITD applied theory of economics and the Program(I.D.A) which can be widely applied to project evaluation analysis. The Kang-Byun-Book-Ro expansion scenario is used to apply and analyze a real-world situation. The result highlights that as much as 15% of diverted travel demand is generated as ITD. The results of this study are expected to improve reliability of the project evaluation of the highway improvement Project.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.2
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• pp.719-727
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• 2013

Four-step travel-demand modeling based on a trip-level has been widely used over many decades. However, there has been a wide variance between forecasted- and real-travel demands, which leads less reliable on the model implications. A primary reason is that person's real travel behavior is not properly captured throughout the model developments. An activity-based modeling (ABM) approach was proposed and developed toward increasing the accuracy and reality of person's travel behavior in the U.S. since 1990', and stands as a good alternative to replace the existing trip-based approach. The paper contributes to the understanding of how the ABM approaches are dissimilar to the trip-based modeling approach in terms of estimation units, estimation process, their pros and cons and etc. We examined three activity-based travel demand model systems (DaySim, CT-Ramp, and CEMDAP) that are most commonly applied by many MPOs (Metropolitan Planning Organization). We found that the ABM approach can effectively explain multi-dimensional travel decision-makings and be expected to increase the predictive accuracy. Overall, the ABM approach can be a good substitute for the existing travel-demand methods having unreliable forecasts.

• Journal of Korean Society of Transportation
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• v.26 no.6
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• pp.7-15
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• 2008

Due to the limitations in the statistical data, the existing studies adopted rough methodologies with strong assumptions in the estimation of international passenger travel demand forecast in the ASEAN region. This study aims to develop international passenger travel demand models using scientific methodologies. This study proposes a direct demand model using the immigration and emigration data between countries in the region. This is because of the difficulty of estimating trip generation and trip distribution separately due to the data limitation in the region. As there does not exist the mode choice model for the region, this study estimates a mode choice model using the Stated Preference technique. The mode choice model is separated into three categories of models according to the range of distance between the origin and destination of travel; this is to reflect the different behavior in mode choice according to the travel distance. The result of model estimations suggests that the estimated models produce resonable results statistically. It is expected that the proposed models are useful for the future travel demand estimation in the ASEAN region.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.5
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• pp.605-612
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• 2019

Traditionally, travel demand forecasts have been conducted based on the data collected by a survey of individual travel behavior, and their limitations such as the accuracy of travel demand forecasts have been also raised. In recent, advancements in information and communication technologies are enabling new datasets in travel demand forecasting research. Such datasets include data from global positioning system (GPS) devices, data from mobile phone signalling, and data from call detail record (CDR), and they are used for reducing the errors in travel demand forecasts. Based on these background, the objective of this study is to assess the feasibility of CDR as a base data for travel demand forecasts. To perform this objective, CDR data collected for Daegu Metropolitan area for four days in April including weekdays and weekend days, 2017, were used. Based on these data, we analyzed the correlation between CDR and travel demand by travel survey data. The result showed that there exists the correlation and the correlation tends to be higher in discretionary trips such as non-home based business, non-home based shopping, and non-home based other trips.

• Communications for Statistical Applications and Methods
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• v.19 no.1
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• pp.183-192
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• 2012

This study analyzes the travel behavior for short-term demand forecasting model of KTX. This research suggests the following. First, the outlier criteria is considered to appropriate twice the standard deviation of the traffic. Second, the result of a homogeneity test using ANOVA analysis has been divided into weekdays(Mon Thu and weekends(Fri Sun). Third, a cluster analysis for O/D pairs using trip frequency, traffic averages and th distance between stations was performed.

• Journal of Korean Society of Transportation
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• v.16 no.4
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• pp.53-64
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• 1998

본 연구의 목적은 '96년말 서울시에서 실시한 가구통행조사를 이용하여 서울시 수단선택모형을 구축하고 그 예측결과를 남산 혼잡통행료 전후저사자료와 비교하여 보다 구체적으로 그 정확성을 검증한 뒤 향후 서울시 교통수요관리 방안의 시행에 따른 수단선택변화 예측의 기본 모형으로 활용하는데 있다. 5가지의 대안모형의 분석결과 통행비용변수(승용차의 경유 주차요금포함)와 총통행시간변수(OVTT와 IVTT의 합), 승용차, 지하철, 택시상수로 구성된 모형이 최적모형으로 분석되었다. 이모형에 의한 시간가치는 9,395원, 승용차의 비용탄력성은-0.6767로서 기존 연구결과의 범위 내에 속한 것으로 나타났다. 최적모형을 이용하여 승용차통행비용이 증가한 경우를 모사분석결과 남산1,3호 터널 혼잡통행료 징수효과와 유사하게 승용차 분담율이 13% 가까이 감소한 것으로 나타나서 모형의 현실적합성도 비교적 높은 것으로 판명되었다. 향후 본 연구에서 선정된 최적수단선택모형을 통행배정모형과 결합하여 다양한 교통수요관리 방안에 따른 효과를 예측하는데 활용하면 서울과 같은 대도시의 단기적 교통관리의 수준을 한 단계 높이는데 기여할 것으로 판단된다.

• Journal of Korean Society of Transportation
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• v.28 no.2
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• pp.171-181
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• 2010

The integrated transit fare system of Seoul metropolitan area has given positively evaluated with reduction of user cost and activating the transfer behavior from its opening year, July 2007. However, there were only few research about railway demand forecasting methodology, especially mode share, has conducted under the integrated fare system. This study focuses on the utility estimation by each mode under the integrated fare system, and on the coefficient actualization relates on travel time and travel cost estimation with Household Travel Survey Data 2006. Also the railway demand analysis methodology under various fare systems is presented. The methodology from this study is expected to improve accuracy and usefulness in railway demand analysis.

• 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.29 no.5
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• pp.139-155
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• 2011

This study is to estimate the dynamic change of the regional railway passenger traffic and, based on the estimated, to forecast the future regional railway passenger traffic by using the Seasonal ARIMA model. The existing studies using ARIMA failed to consider seasonality nor the monthly or the quarterly data. It was attempted in this study to use the monthly regional railway passenger traffic data to propose a model that estimates dynamic change of demand. The authors employed the Seasonal ARIMA model previously developed and used (1) the numbers of monthly passenger data and (2) the monthly passenger-km data. The test results showed that the numbers of passengers in 2015 and 2020 would increase by 36% and 71%, respectively, compared to those in 2008. The numbers of passenger-kms in 2015 and 2020 would increase by 25% and 78%, respectively, compared to those in 2008.