• International Journal of Railway
• /
• v.7 no.1
• /
• pp.24-33
• /
• 2014

The Korean high-speed rail (HSR) began its commercial service in 2004. This service has been created significant changes in the system of intercity passenger travels of Korea. However, the actual ridership was approximately half of the estimated one in the planning stage. In this background, this paper presents the difference between the stated preference (SP) before the HSR service and the revealed preference (RP) after it using the intercity travel mode choice models. Several meaningful differences are found in terms of the factors affecting the travel mode choice, the estimation results of model, the monetary values of time, and elasticities. While the access/egress travel time of high-speed rail is less important than in-vehicle travel time in the SP sample, they have same weight in the RP sample. Also the RP models show that the probability of choosing HSR can be decreased by the increase of the number of vehicles in household contrary to the results from the SP models. The monetary values of travel time are relatively high and the direct and cross elasticities in response to changes in level-of-service of HSR are relatively low in the RP sample. This Korean case is expected to offer referable material for preparing high-speed rail services in other countries by showing the difference between the SP and RP before/after the actual service, identifying the importance of access/egress travel time and lower direct elasticities of HSR demand.

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

• Proceedings of the KOR-KST Conference
• /
• 1998.09a
• /
• pp.160-167
• /
• 1998

Recent world-wide interest in activity-based travel behavior modeling has generated an entirely new perspective on how the profession views the travel demand process. This paper seeks to further promote the case of activity-based travel behavior models by providing some empirical evidence of relationship between travel time and activity duration decision for worker with transportation panel data. The travel time from home to work and from work to home, without activity involvement, is estimated by the Ordinary Least Squares (OLS) method. And, the travel time to and from the selected activity and the activity duration are modeled simultaneously by the Three Stage Least Squares (3SLS) method due to the endogenous relationship between travel time and activity duration. Two kinds of models, OLS and 3SLS, include selectivity bias corrections in a discrete/continuous framework, because of the inter-relationship between the choice of activity type/travel mode (discrete) and the travel time/activity duration (continuous). Estimation is undertaken using a sample of over 1300 household two-day trip diaries collected from the same travelers in the Seattle area in 1989. The behavioral consequences of these models provide interesting and provocative findings that should be of value to transportation policy formulation and analysis.

• Journal of Korean Society of Transportation
• /
• v.30 no.2
• /
• pp.7-20
• /
• 2012

The objective of this paper is to construct pseudo-panel data set and estimate price and income elasticities of car travel demand, using 1995-2007 household income and expenditure survey data, in order to provide quantitative information for analyzing related policy effects in the transport sector. We categorized household survey data into 14 cohorts based on the birth year of the household head. As the result, a total of 133 pseudo-panel data sets was created for estimating price and income elasticities of car travel demand. Especially, price and income elasticities of car travel demand were separately estimated both short-term and long-term. We analyzed the panel model considering fixed effect within cohorts, using explanatory variables such as previous year's fuel consumption, real household income after tax, education level of the household head, the number of children under five, and the share of household type averaged by cohorts. As results, the short-term and long-term price elasticities of car travel demand were calculated as 0.2974-0.4280 and 0.4087-0.6275, respectively. Similarly, the short-term and long-term income elasticities were calculated as 0.3364-0.6281 and 0.7098, respectively.

• Proceedings of the KOR-KST Conference
• /
• 2007.11a
• /
• pp.638-646
• /
• 2007

• Korean Management Science Review
• /
• v.17 no.2
• /
• pp.87-95
• /
• 2000

This paper presents two analytical approaches to determine the vehicle fleet size for container shuttle service. The shuttle service can be defined as the repetitive travel between the designated places during working period. In the first approach, the transportation model is adopted in order to determine the number of vehicles required. Its advantages and disadvantages in practical application are also discussed. In the second approach, a logical network which is oriented on job is transformed from a physical network which is focused on demand site. Nodes on the logical network represent jobs which include loaded travel, loading and unloading and arcs represent empty travel for the next jobs which include loaded travel, loading and unloading and arcs represent empty travel for the next job. Then a mathematical formulation is constructed similar to the multiple traveling salesman problem (TSP). A solution procedure is carried out based on the well-known insertion heuristic with the real world data.

• Journal of Environmental Science International
• /
• v.10 no.3
• /
• pp.173-178
• /
• 2001

The aim of this paper is to evaluate users benefit values of theme park using Travel Cost Method with special reference to Woobang Tower Land in Taegu for the estimation of economic values. This research is mainly based on questionnaire survey of 100 users of the theme park. Socio-economic factors such as income, year of education, annual income, age and money(travel cost) are analysed from 5 residential areas of the respondents. Multiple regression analysis was used for the evaluation of annual number of park visitings based on the analysis. The regression model shows NV = $\alpha$+$\beta_1$TC+$\beta_2$INC+$\beta_3$EDU+$\beta_4$AGE (NV : Annual Number of Visitings, TC : Travel Cost, INC : Annual Income, EDU : Years of Education, AGE : Age). Regarding to visitors demand curve based on the equation showed that annual economic values of Woobang Tower Land was estimated as 50billion Korean Won.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.4D
• /
• pp.565-571
• /
• 2006

This study aimed to analyze access mode choice behavior for KTX Passengers. To fulfill the aims of this study, Dong-Daegu Station was selected as a station for a case study. This study takes place in two stages. These are (i) descriptive statistical analysis of transportation status before and after introduction of the KTX, (ii) empirical model estimation for analyzing access mode choice behavior. This study makes use of the data from travel survey from Daegu metropolitan area. The main part of the survey was carried out in the KTX Dong-Daegu station. The data was collected from a sample of 1,800 individuals. The survey data includes the information on travel from Dong-Daegu station to Seoul. From descriptive statistical analysis of transportation status before and after introduction of the KTX, it is found that revealed demand of the KTX is lower than that expected. Moreover, it is found that the low demand of the KTX stems from high cost for the KTX itself and inconvenience( including travel time and cost) of access mode. In order to analyze mode choice behavior for accessing Dong-Daegu station, multinomial logit model structure is used. For the model specification, a variety of behavioral assumptions about the factors which affect the access mode choice, were considered. From the empirical model estimation, it si found that access travel time and access travel cost are significant in choosing access mode. Given the empirical evidence, we see that improvement of access transportation system for Dong-Daegu station is very important for enhancing the use of KTX.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.35 no.5
• /
• pp.1123-1133
• /
• 2015

This study proposed an evaluation method of mobile emissions reduction strategies for air quality management. The proposed method was considered Travel Demand Model (TDM) and Analytic Hierarchy Process (AHP), while an existing method was focused on quantitative factors. AHP of the evaluation indices of mobile emissions reduction strategies show that quantitative evaluation indices such as air pollutants and greenhouse gas reduction are more important than the political evaluation indices (Consistency with an upper plan, Policy applicability, Technical applicability and feasibility) and each weight of air pollutants and greenhouse gas reduction are found to be 0.373 and 0.218. The early scrapping policy of decrepit diesel vehicle is the best policy in the proposal method using TDM and AHP but this result differs from evaluated result by TDM or AHP respectively. These results are limited to the basic assumption and range of reduction scenarios but are expected to contribute to establish more reasonable and effective mobile emission reduction strategies.

• KDI Journal of Economic Policy
• /
• v.38 no.1
• /
• pp.23-52
• /
• 2016

This paper examines the impact of introducing high-speed trains on consumer welfare, taking the ensuing changes in train schedules into account. Based on the estimated demand model for travel which incorporates consumer's heterogeneous preferences for travel schedules into the standard discrete-choice model, I separately evaluate the impact from adding high-speed trains and that from changes in train schedules. The results indicate that consumers who travel between two cities connected by high-speed trains benefit from the introduction of high-speed trains, while some travelers whose choice set does not include high-speed trains face a reduced frequency of non-high-speed trains, resulting in significant losses.