• Journal of the Korean Society for Railway
• /
• v.12 no.3
• /
• pp.420-426
• /
• 2009

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
• /
• v.1 no.1
• /
• pp.28-42
• /
• 1983

In recent years, significant advances have been made enabling travel demand analysis and network design methods to be used as increasingly realistic evaluation tools. What has been lacking is the integration of travel demand analysis with network design models. This paper reviews some of advanced (integrated) modeling approaches and presents future research directions of integrated modeling system. To design urban transportation networks, it is argued that the travelers' free choice of mode, destination and route should be introduced into transportation network design procedure instead of assuming that trips from a zone to a workplace are fixed or deriving them in a normative procedure to achieve hypothetical system optima.

• Journal of Korean Society of Transportation
• /
• v.24 no.3 s.89
• /
• pp.157-165
• /
• 2006

The Purpose of this study is to analyze telecommunications impacts on travel in a comprehensive system, considering demand, supply, costs, and land use. This study first Presents a conceptual model, considering causal relationships among travel, telecommunications, land use, economic activity, and socio-demographics. Then, based on the conceptual model, the aggregate causal relationships between telecommunications (local telephone calls, toll calls, and mobile phone subscribers) and travel (vehicle-miles traveled and number of transit Passengers) are explored in a comprehensive framework, using structural equation modeling of national time series data spanning 1950-2000 in the U.S. The model results suggest that as telecommunications demand increases, travel demand increases, and vice versa. Additionally. transportation infrastructure and land use significantly affect travel demand.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.33 no.2
• /
• pp.719-727
• /
• 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 the Society of Disaster Information
• /
• v.20 no.2
• /
• pp.257-269
• /
• 2024

Purpose: The purpose of this study is to explain the pivotal role of the travel forecasting process in urban transportation planning. This study emphasizes the use of travel forecasting models to anticipate future traffic. Method: This study examines the methodology used in urban travel demand modeling within transportation planning, specifically focusing on the Urban Transportation Modeling System (UTMS). UTMS is designed to predict various aspects of urban transportation, including quantities, temporal patterns, origin-destination pairs, modal preferences, and optimal routes in metropolitan areas. By analyzing UTMS and its operational framework, this research aims to enhance an understanding of contemporary urban travel demand modeling practices and their implications for transportation planning and urban mobility management. Result: The result of this study provides a nuanced understanding of travel dynamics, emphasizing the influence of variables such as average income, household size, and vehicle ownership on travel patterns. Furthermore, the attraction model highlights specific areas of significance, elucidating the role of retail locations, non-retail areas, and other locales in shaping the observed dynamics of transportation. Conclusion: The study methodically addressed urban travel dynamics in a four-ward area, employing a comprehensive modeling approach involving trip generation, attraction, distribution, modal split, and assignment. The findings, such as the prevalence of motorbikes as the primary mode of transportation and the impact of adjusted traffic patterns on reduced travel times, offer valuable insights for urban planners and policymakers in optimizing transportation networks. These insights can inform strategic decisions to enhance efficiency and sustainability in urban mobility planning.

• Proceedings of the KSR Conference
• /
• 2011.05a
• /
• pp.1282-1289
• /
• 2011

The rail passenger demand for the railroad operations required a short-term demand rather than a long-term demand. The rail passenger demand can be classified according to the purpose. First, the rail passenger demand will be use to the restructure of line planning on the current operating line. Second, the rail passenger demand will be use to the line planning on the new line and purchasing the train vehicles. The objective of study is to analyze the travel behavior of rail passenger for modeling of short-term demand forecasting. The scope of research is the passenger of KTX. The travel behavior was analyzed the daily trips, origin/destination trips for KTX passenger using the ANOVA and the clustering analysis. The results of analysis provide the directions of the short-term demand forecasting model.

• Proceedings of the Korean Society of Disaster Information Conference
• /
• 2023.11a
• /
• pp.259-260
• /
• 2023

The rapid urbanization and modernization observed in countries like Myanmar have led to significant concerns regarding traffic congestion, especially in urban areas. This study focuses on the analysis and revitalization of urban transport in selected areas of Myanmar. The core of urban transportation planning lies in travel forecasting, which employs models to predict future traffic patterns and guide decisions related to road capacity, transit services, and land use policies. Travel demand modeling involves a series of mathematical models that simulate traveler behavior and decision-making within a transportation system, including highways, transit options, and policies. The paper offers an overview of the traditional four-step transportation modeling system, utilizing a simplified transport network in the context of Mandalay City, Myanmar.

• Proceedings of the KSR Conference
• /
• 2007.11a
• /
• pp.734-743
• /
• 2007

The KTX station is one of special generators that produce a lot of trips caused by special land use such as university, airport, and super shopping mall. Special generators need special attention in developing travel demand models since the standard trip generation and distribution model in the conventional four-step approach do not provide reliable estimates of their travel patterns. New modeling approach, activity-based model, considering travel behavior of person, seem to be more appropriate for those special generators. Thus, this study introduces a spatial-temporal activity-based approach and how activity-based approach can be applied to estimation of travel demand at KTX stations.

• Journal of Korean Society of Transportation
• /
• v.7 no.1
• /
• pp.35-42
• /
• 1989

The multinomial logit model has been applied for various choice problems. Among others, the joint destination mode choice, the mode choice and the route choice are the three major modeling topics for korean transportation planners. This paper examines with real world data (the Olympic road and its competing two major arterials) the usefulness of a Logit route choice model. Quites surpisingly, it is found that the multinomial route choice behavioral model calibrated for this study based on (0,1) individula data base can not provide a good estimate for O-D trips less than 6㎞. 400data points and 3case studies might not be sufficient for a sound conclusion. It is, however, believed from a series of similar studies conducted by the authors that the route choice behavior is more sensitive (more demand elastic with respect to travel time changes) than the mode choice and the shorter trip, the more sensitive. The travel time parameters for destination choice models are usually smalle than the travel time parameters for mode choice models and these parameters (for mode choice models) turn our smaller than the travel time parameters for route choice models from this study. Table 2 in this paper shows parameter changes for three different markets and Table 3 shows the modeling errors when the estimated individual probabilities are aggregated into a route level.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.21 no.4
• /
• pp.77-89
• /
• 2013

The purpose of this study is to anticipate the air travel demands over the period of 164 months, from January 1997 to August 2010 using ARIMA-Intervention modeling on the selected sample data. The sample data is composed of the number of the passengers who in the domestic route for Jeju route. In the analysis work of this study, the past events which are assumed to have affected the demands for the air travel routes to Jeju in different periods were used as the intervention variables. The impacts of such variables were reflected in the presupposed demand. The intervention variables used in this study are, respectively, the World Cup event in 2002 (from May to June), 2003 SARS outbreak (from April to May), Tsunami in January 2005, and the influenza outbreak from October to December 2009. The result of the above mentioned analysis revealed that the negative intervention events, like a global outbreak of an epidemic did have negative impact on the air travel demands in a risk aversion by the users of the aviation services. However, in case of the negative intervention events in limited area, where there are possible substituting destinations for the tourists, the impact was positive in terms of the air travel demands for substituting destinations due to the rational expectation of the users as they searched for other options. Also in this study, it was discovered that there is not a binding correlation between a nation wide mega-event, such as the World Cup games in 2002, and the increased air travel demands over a short-term period.