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

• Journal of Korean Society of Transportation
• /
• v.31 no.3
• /
• pp.86-95
• /
• 2013

In this study, a model of compensation and amendment of forecasted travel demand was developed to calculate the range of values depends on the changes in the risk factors, selecting factors that might affect traffic demand changes among risk factors. Selected factors are as follows: influenced area population, the number of registrated vehicle per person, ratio of service industry workers, and city intervals. Then this model is applied to six routes of expressway and the calculated value were compensated with error rate being reflected on each quartile value with respect to influenced area population (200,000 people standards). Result from appling developed model to Cheongwon-Sangju expressway suggests that the model could compensate the error rate by more than 50%, which in turn validate the effectiveness of the model developed. Some limitations and future research agenda have also been identified.

• Proceedings of the KSR Conference
• /
• 2010.06a
• /
• pp.2166-2178
• /
• 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
• /
• v.26 no.2
• /
• pp.147-156
• /
• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.6
• /
• pp.32-48
• /
• 2023

Autonomous driving technology is shaping the future of personalized travel, encouraging personalized travel, and traffic impact could be influenced by individualized travel behavior during the transition of driving entity from human to machine. In order to evaluate traffic impact, it is necessary to estimate the total number of trips based on an understanding of individual travel characteristics. The Activity-based model(ABM), which allows for the reflection of individual travel characteristics, deals with all travel sequences of an individual. Understanding the relationship between travel and travel must be important for assessing traffic impact using ABM. However, the ABM has a limitation in the data hunger model. It is difficult to adjust in the actual demand forecasting. Therefore, we utilized a Tour-based model that can explain the relationship between travels based on household travel survey data instead. After that, vehicle registration and population data were used for correction. The result showed that, compared to the KTDB one, the traffic generation exhibited a 13% increase in total trips and approximately 9% reduction in working trips, valid within an acceptable margin of error. As a result, it can be used as a generation correction method based on Tour, which can reflect individual travel characteristics, prior to building an activity-based model to predict demand due to the introduction of autonomous vehicles in terms of road operation, which is the ultimate goal of this study.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.3
• /
• pp.51-61
• /
• 2023

Travel demand estimation of E-Scooter is the start point of solving the regional demand-supply imbalance problem and plays pivotal role in a linked transportation system such as Mobility-as-a-Service (a.k.a. MaaS). Most focuses on developing trip generation model of shared E-Scooter but it is no study on selection of an appropriate zone scale when it comes to estimating travel demand of E-Scooter. This paper aimed for selecting an optimal TAZ scale for developing trip distribution model for shared E-Scooter. The TAZ scale candidates were selected in 250m, 500m, 750m, 1,000m square grid. The shared E-Scooter usage historical data were utilized for calculating trip distance and time, and then applying to developing gravity model. Mean Squared Error (MSE) is applied for the verification step to select the best suitable gravity model by TAZ scale. As a result, 250m of TAZ scale is the best for describing practical trip distribution of shared E-Scooter among the candidates.

• Journal of Distribution Science
• /
• v.10 no.9
• /
• pp.5-11
• /
• 2012

Purpose - The objective of the paper is to explain both the price sensitivity of international tourists to South Korea and the price sensitivity of Korean tourists to international travel. The study examines long-run equilibrium relationships and Granger causal relationships between foreign exchange rates and inbound and outbound tourism demand in South Korea. Research design/ data / methodology - The study employs monthly time series data from January 1990 to September 2010. The paper examines the long-run equilibrium relationship using the Johansen cointegration test approach after unit root tests. The short-run Granger causality was tested using the vector error correction model with the Wald test. Results - Hypothesis 1 testing whether there is a long-run equilibrium relationship between exchange rates, inbound and outbound tourism demand is supported. Hypothesis 2 testing whether exchange rates lead to a change in touristarrivals and expenditure is not supported. Hypothesis 3 testing whether exchange rates lead to a change in tourist departures and expenditure is supported. Conclusions - The findings of this study show that the impacts of tourism price competitiveness are changing quite significantly with regard to destination competitiveness. In other words, the elasticity of tourism price over tourism demand has been moderated.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.14 no.4
• /
• pp.62-72
• /
• 2015

Nowadays the issue of aging society has received considerable critical attention, especially in transportation planning and demand forecasting. This study identified the factors related to travel time budget for elderly by purpose using seemingly unrelated regression model (SUR model). The SUR model is suitable when error terms of each equation are assumed to be correlated across the equations in terms of travel time budget which is constant in 2 hours per day commonly. The results showed that elderly's travel time budget was affected by individual, household, urban facility and transportation service. The leisure travel comprised a large proportion of total travel time and had a positive relationship with elderly, sports, religious facilities. Moreover, the elderly who had low income or unemployed person had low frequency of social activity such as leisure, shopping and business. This study can provide a comprehensive implications of forecasting the future travel demand and analyzing the travel behavior.

• Journal of Korean Society of Transportation
• /
• v.29 no.6
• /
• pp.97-106
• /
• 2011

Mode choice model is an essential element for estimating- the demand of new means of transportation in the planning stage as well as in the establishment phase. In general, current demand analysis model developed for the mode choice analysis applies common parameters of utility function in each region which causes inaccuracy in forecasting mode choice behavior. Several critical problems from using common parameters are: a common parameter set can not reflect different distribution of coefficient for travel time and travel cost by different population. Consequently, the resulting model fails to accurately explain policy variables such as travel time and travel cost. In particular, the nonlinear logit model applied to aggregation data is vulnerable to the aggregation error. The purpose of this paper is to consider the regional characteristics by adopting the parameters fitted to each area, so as to reduce prediction errors and enhance accuracy of the resulting mode choice model. In order to estimate parameter of each area, this study used Household Travel Survey Data of Metropolitan Transportation Authority. For the verification of the model, the value of time by marginal rate of substitution is evaluated and statistical test for resulting coefficients is also carried out. In order to crosscheck the applicability and reliability of the model, changes in mode choice are analyzed when Seoul subway line 9 is newly opened and the results are compared with those from the existing model developed without considering the regional characteristics.

• Journal of Korean Society of Transportation
• /
• v.29 no.1
• /
• pp.17-27
• /
• 2011

This paper investigates some critical errors influencing travel demand estimation in Korea Transportation Data Base (KTDB), and through this investigation reasonable traffic analysis zone (TAZ) size and internal trips ratio are analyzed. With varying zone size, the accuracy of travel demand estimation is studied and appropriate level of zone size in KTDB is also presented. For this purpose zonal structure consisting of location of zone centroid, number of centroid connecters has been constructed by social economic index, and then some descriptive statistical analyses such as F-test, coefficient of correlation are performed. From the results, this paper shows that the optimum levels of zone system were various according to the order and capacity of roads, and also shows that the smaller TAZ, the less error in this research. In conclusion, in order to improve accuracy of traffic demand estimation it is necessary to make zone size smaller.