• Journal of the Economic Geographical Society of Korea
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• v.9 no.3
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• pp.379-395
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• 2006

The purpose of this study is to analyze the spatial characteristics of travel patterns and travel behaviors of transit users in the Metropolitan Seoul area. We apply the data mining techniques to explore the travel patterns of transit users from the T-money card database which has been produced over 10,000,000 transaction records per day. The database contains the information of locations and times of origin, transfer, and destination points for each transaction as well as the informations of transit modes taken via the transaction. We develop an data mining algorithm to explore traversal patterns from the enormous information. The algorithm determines the travel sequences of each passenger, and produce the volumes of support on each points (stops) of transportation networks in the Metropolitan Seoul area. In order to visualize the spatial patterns of travel demands for transit systems we apply GIS techniques, and attempt to investigate the spatial characteristics of travel patterns and travel demand. Subway stops located in the Gangnam area appear the highest peak for the travel origin and destination, while the CBD in the Gangbuk stands at the second position. Two or three sub-peaks appear at the densely populated residential areas developed as the high-rise apartment complex. Subway stations located along the Subway Line 2, especially from Guro to Samsung receive heavy travel demand (total support), while bus stops located at the CBD in the Gangbuk stands the highest travel demand by bus.

• Journal of the Economic Geographical Society of Korea
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• v.10 no.1
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• pp.44-63
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• 2007

The purpose of this study is to propose mining processes in the large trip-transaction database of the Metropolitan Seoul area and to analyze the spatial characteristics of travel behavior. For the purpose. this study introduces a mining algorithm developed for exploring trip patterns from the large trip-transaction database produced every day by transit users in the Metropolitan Seoul area. The algorithm computes trip chains of transit users by using the bus routes and a graph of the subway stops in the Seoul subway network. We explore the transfer frequency of the transit users in their trip chains in a day transaction database of three different years. We find the number of transit users who transfer to other bus or subway is increasing yearly. From the trip chains of the large trip-transaction database, trip patterns are mined to analyze how transit users travel in the public transportation system. The mining algorithm is a kind of level-wise approaches to find frequent trip patterns. The resulting frequent patterns are illustrated to show top-ranked subway stations and bus stops in their supports. From the outputs, we explore the travel patterns of three different time zones in a day. We obtain sufficient differences in the spatial structures in the travel patterns of origin and destination depending on time zones. In order to examine the changes in the travel patterns along time, we apply the algorithm to one day data per year since 2004. The results are visualized by utilizing GIS, and then the spatial characteristics of travel patterns are analyzed. The spatial distribution of trip origins and destinations shows the sharp distinction among time zones.

• Asia-Pacific Journal of Business
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• v.9 no.4
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• pp.1-11
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• 2018

Retiring from work is a major personal and professional transition and has a major influence on one's life. Tourism researchers have been aware of the importance of seniors' tourism and leisure activities to enhance their well-being. The study examines the effect of tourism experience on leisure life domain, which in turn influences overall quality of life. Moreover, the moderating effect of travel patterns is also tested. A final sample of 328 was used for data analysis including Structural equation modeling (SEM) and multi-group analysis to test the hypotheses. The findings revealed that tourism experience positively influences satisfaction with leisure life domain and overall quality of life. Findings also indicated that there are moderating effects of the travel patterns on the relationship between satisfaction with leisure life domains and overall quality of life. The study also provided managerial implications for tourism marketers and destination managers.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.2
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• pp.1-11
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• 2014

In this paper, travel speed patterns were deducted based on historical DSRC travel speed data using Decision Tree technique to improve availability of the massive amount of historical data. These patterns were designed to reflect spatio-temporal vicissitudes in reality by generating pattern units classified by months, time of day, and highway sections. The study area was from Seoul TG to Ansung IC sections on Gyung-bu highway where high peak time of day frequently occurs in South Korea. Decision Tree technique was applied to categorize travel speed according to day of week. As a result, five different pattern groups were generated: (Mon)(Tue Wed Thu)(Fri)(Sat)(Sun). Statistical verification was conducted to prove the validity of patterns on nine different highway sections, and the accuracy of fitting was found to be 93%. To reduce travel pattern errors against individual travel speed data, inclusion of four additional variables were also tested. Among those variables, 'traffic condition on previous month' variable improved the pattern grouping accuracy by reducing 50% of speed variance in the decision tree model developed.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.119-128
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• 2008

Weather like rain, strong wind or snowfall may make the road condition deteriorated and sometimes induce traffic accidents, which lead to severe traffic congestion, thereby travelers may change their destinations elsewhere. Although origin-destination trip information is required to analyze transportation planning in urban area, there are little researches on the relationship between weather condition and travel patterns. This paper investigates the characteristics of travel patterns on expressway in rainy days of 2006. We compare the normal travel patterns with those of rainy days by the travel distance for each vehicle type. Results show that traffic volume and travel distance have been reduced in rainy days as we expect, and also show different travel patterns for weekday and weekend.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.4
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• pp.68-79
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• 2010

Weather like rain, strong wind or snowfall may make the road condition deteriorated and sometimes induce traffic accidents, which lead to severe traffic congestion, thereby travelers may change their destinations elsewhere. Although origin-destination trip information is required to analyze transportation planning in urban area, there are little researches on the relationship between weather condition and travel patterns. This paper investigates the characteristics of travel patterns on expressway in snowing days of 1998-2008. We compare the normal travel patterns with those of snowing days by the travel distance for each vehicle type. Results show that traffic volume and travel distance have been reduced in snowing days as we expect, and also show different travel patterns for weekday and weekend.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.559-564
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• 2006

The purpose of this study is to minimize negative effect of VMS travel time information service by sensitivity analysis, which forecasts the change in link traffic volume. As a result, strategies for providing travel information that can change driving patterns for minimizing travel time were found. The framework for analysis is recently expanded with the application of game theory. According to the experiment, the algorithm generated for travel time information service reduces total travel time and yields travel patterns that is very close to the system optimization. Also, this study found that the route the travel time service information is provided about could play the important role.

• International Journal of Highway Engineering
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• v.16 no.5
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• pp.99-108
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• 2014

PURPOSES : The travel times of expressway buses have been estimated using the travel time data between entrance tollgates and exit tollgates, which are produced by the Toll Collections System (TCS). However, the travel time data from TCS has a few critical problems. For example, the travel time data include the travel times of trucks as well as those of buses. Therefore, the travel time estimation of expressway buses using TCS data may be implicitly and explicitly incorrect. The goal of this study is to improve the accuracy of the expressway bus travel time estimation using DSRC-based travel time by identifying the appropriate analysis period of input data. METHODS : All expressway buses are equipped with the Hi-Pass transponders so that the travel times of only expressway buses can be extracted now using DSRC. Thus, this study analyzed the operational characteristics as well as travel time patterns of the expressway buses operating between Seoul and Dajeon. And then, this study determined the most appropriate analysis period of input data for the expressway bus travel time estimation model in order to improve the accuracy of the model. RESULTS : As a result of feasibility analysis according to the analysis period, overall MAPE values were found to be similar. However, the MAPE values of the cases using similar volume patterns outperformed other cases. CONCLUSIONS : The best input period was that of the case which uses the travel time pattern of the days whose total expressway traffic volumes are similar to that of one day before the day during which the travel times of expressway buses must be estimated.

• Journal of the Korean Geographical Society
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• v.44 no.2
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• pp.176-186
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• 2009

Transportation policy to facilitate the public mode use is of the foremost importance to the local governments of Metropolitan Seoul, regarding the economic and environmental consequences of the increasing use of car. Understanding the travel behaviour is essential to the establishment of proper policy to guide more people to the use of public modes instead of private. The paper reports a result of sequential analysis of individual travel behaviour in Metropolitan Seoul, using a multi-dimensional motif search technique applied to Smart Card data that integrates individuals' different public mode uses. Groups of travel patterns with similar sequential information identified distinctive travel behaviour between Seoul north and south and between metro and bus uses. Travel patterns are more bounded within north Seoul and south Seoul respectively than crossing Han River between north and south. Within north and south, travel patterns visiting northern CBD and southern CBD, respectively, as well as their local neighbour in north and south, often use metro and metro-local bus combination, while travel patterns visiting only the north and south locals without CBDs more use only the local bus line and even only the areal bus line.

• Journal of Korean Society of Transportation
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• v.28 no.1
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• pp.51-61
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• 2010

The main objective of this paper is to analyze change of travel patterns according to public transportation reform. The paper uses data collected from Gyeongsan City. So far few researches, especially using before-and-after individual travel survey, have been conducted on analyzing effects of public transportation reform. For this research, some descriptive statistical analyses and statistical hypotheses tests were conducted. Furthermore, some empirical logit models were estimated for analyzing the individual effects of the public transportation reform. Finally, some important foundings, policy implications, and limitations of this research are discussed.