• Proceedings of the KSR Conference
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• 2003.10b
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• pp.3-7
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• 2003

It is very difficult to find optimal train operation plan when analyzing the economic investment using traditional railroad travel demand estimation method. Train operation plan depends on travel demand and vice versa. To solve this problem, this study suggests a demand estimation method to address an optimal train operation scheme with the modal spilt using initial train operation plan and trip assignment.

• 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.

• 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 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.26 no.5
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• pp.163-174
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• 2008

The conventional four-step travel demand model is still widely used as the state-of-practice in most transportation planning agencies even though it does not provide reliable estimates of travel demand. In order to improve the accuracy of travel demand estimation, implementing an alternative approach would be critical as much as acquiring reliable socioeconomic and travel data. Recently, the role of travel demand model is diverse to satisfy the needs of microscopic analysis regarding various policies of travel demand management and traffic operations. In this context, the activity-based approach for travel demand estimation is introduced and a case study of developing a spatial-temporal activity presence-based approach that estimates travel demand through forecasting number of people present at certain place and time is accomplished. Results show that the spatial-temporal activity presence-based approach provides reliable estimates of both number of people present and trips actually people made. It is expected that the proposed approach will provide better estimates and be used in not only long-term transport plans but short-term transport impact studies with respect to various transport policies. Finally, in order to introduce the spatial-temporal activity presence-based approach, the data such as activity-based travel diary and land use based on geographic information system are essential.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.626-637
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• 2008

Although the amount of travel demand is a critical factor in a benefit-cost (B/C) analysis of railway investment, the travel demand changes especially for induced demand have not been considered. Therefore, the basic study of how to estimate travel demand changes after railway investment is worth investigating. This study reviews the methodologies for estimating diverted and induced demand generated after railway investment, and proposes appropriate approaches that will help railway planners to practically apply them in a case study. Further, the research stimulates the needs of consideration of the travel demand changes in the feasibility studies of railway planning.

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.63-72
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• 2002

We applied 3-D balancing technique to estimate nationwide travel demand using travel behavior of Toll Collecting System data, socio-economic data in the region, and the data of several organizations connected with travel demand estimation. The results from this study were validated by the indices of RMSE(Root Mean Square Error), TLFD(Trip Length Frequency Distribution). TCS based inter-city average travel to measure of reliability and adequacy of estimated travel demand. Finally, 3-D technique seems to reflect more travel behavior of TCS OD than 2-D technique, but we cannot assert that 3-D technique superior to 2-D technique.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.5D
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• pp.671-677
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• 2011

A diversity of railway network function enhancement projects such as the double tracking, electrification, and direct operation have been actively executed to improve the railway service. When the new rapid transit is provided, how many people will use it instead of other transports? How will the railway choice behavior be changed? Accordingly, in this paper, the applicability of diverted travel demand forecast methods, by Revealed Preference(RP) and Stated Preference(SP) data was reviewed for Daegu metropolitan rail rapid transit service. As the result of combining RP and SP data, including the sequential and simultaneous approach, the total travel time and travel cost parameters are of the right sign and are highly significant. The simultaneous approach is more efficient in terms of the estimation of coefficients. In particular, methods to improve validity of the Mixed RP/SP models, when RP data is used proportionally, the diverted travel demand can be easily identified by railway fare and travel time service level. Therefore, it is considered that this will practically apply even in other regions as well as Daegu metropolitan railway.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.721-729
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• 2009

Recently, there has been growing necessity to estimate the future travel demand of high speed train because the circumstance of high speed train service is rapidly changing with the launching of 2011 second stage of Gyeongbu high speed railway(Dongdaegu-Busan) and the completion of 2014 first stage of Honam high speed railway(Yongsan-Gwangju), etc. This study was designed to estimate future travel demand by analyzing the transport performance and train service characteristics of Gyeongbu and Honam line. This study presents the maximum load section and the changed future travel demand, which will be applied to establish a train operation plan.

• 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.