• Journal of the Korean Society for Railway
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• v.12 no.5
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• pp.613-622
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• 2009

The modal spilt of highway has been increased and the one of railway has been decreased from 17.2%(1990) to 6.3%(2006). In this context, it is meaningful to examine the competitiveness of the railroad of Korea. The objective of this study is to analyze the competitiveness of railroad with the highway so that countermeasures improving the competitiveness of railroad could be suggested. For this, firs of all, indicators representing the competitiveness of the railroad transport are determined. The main influencing factors for mode choice include transport time, transport cost and level of service. Three types of commodity, container, cement and steel are the target for the analysis. It was found that the overall competitiveness of railroad transport is weaker compared with highway even for the main freight origin-destination pairs. It means that the freight transport system is focused on road rather than railroad. Therefore, we need to remeasure the competitiveness of railroad transport related to methods for freight railroad competitiveness improvement.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.1
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• pp.10-21
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• 2008

User travel behavior is based on the existence of complete traffic information in deterministic user optimal principle by Wardrop(1952). According to deterministic user optimal principle, users choose the optimal route from origin to destination and they change their routes arbitrarily in order to minimize travel cost. In this principle, users only consider travel time as a factor to take their routes. However, user behavior is not determined by only travel time in actuality. Namely, the models that reflect only travel time as a route choice factor could give irrational travel behavior results. Therefore, the model is necessary that considers various factors including travel time, transportation networks structure and traffic information. In this research, more realistic deterministic optimal traffic assignment model is proposed in the way of route recognizance behavior. This model assumes that when users decide their routes, they consider many factors such as travel time, road condition and traffic information. In addition, route recognizance attributes is reflected in this suggested model by forward searching method and backward searching method with numerical formulas and algorithms.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.100-111
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• 2019

The existing selected station analysis (SSA) method analyzes the link transfer mode data between origin and destination of individuals passing through stations from a microscopic standpoint. As such, existing SSA is insufficient as it uses integrated analysis using macroscopic data such as subway lines. This research builds a line chain OD based on path search of individual passenger's movement through the subway, and explores means to utilize the findings. First, a method is proposed that searches the traversed subway path from the linked passage modes that the passenger uses and applies the results to SSA line analysis. Compared to the existing SSA, this method provides for analysis of commonly conflicting features such as the line on which the station is passed, and the stations included on the line thanks to the presence of complete information of the individual passenger's traversed path. It also allows for integrated observation of the line chain OD that approaches a certain station. For enhanced understanding, Seoul Metro Line 9 is used as a case study to demonstrate the integrated formulation concept of line chain OD centered around a certain station as well as the macroscopic features of the traversed path that approaches stations included on the line.

• Land and Housing Review
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• v.14 no.4
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• pp.77-93
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• 2023

The COVID-19 pandemic has brought about significant social changes through government prevention and control measures, changes in people's risk perceptions, and lifestyle changes. In response, urban inhabitants changed their behaviors significantly, including their preferences for transportation modes and urban spaces in response to government quarantine policies and concerns over the potential risk of infection in urban spaces. These changes may have long-lasting effects on urban spaces beyond the COVID-19 pandemic or they may evolve and develop new forms. Therefore, this study aims to explore the potential for urban spaces to adapt to the present and future pandemics by examining changes in urban residents' preferences in travel modes and urban space use due to the COVID-19 pandemic. This study found that overall preferences for travel modes and urban spaces significantly differ between the pre-pandemic, pandemic, and post-pandemic periods. During the pandemic, preferences for travel modes and urban spaces has decreased, except for privately owned vehicles and green spaces, which are perceived to be safe from transmission, show more favorable than others. Post-pandemic preferences for travel modes and urban spaces are less favorable than pre-pandemic with urban spaces being five times less favorable than transportation. Although green spaces and medical facilities that were positively perceived during the pandemic are expected to return to the pre-pandemic preference level, other factors of urban spaces are facing a new-normal. The findings suggest that the COVID-19 pandemic has had a significant impact on urban residents' preferences for travel modes and urban space use. Understanding these changes is crucial for developing strategies to adapt to present and future pandemics and improve urban resilience.