• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.3
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• pp.99-106
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• 2017

With the increased interest in the quality of life of modern people, the implementation of the five-day working week, the increase in traffic convenience, and the economic and social development, domestic and international travel is becoming commonplace. Furthermore, in the past, there were many cases of purchasing packaged goods of specialized travel agencies. However, as the development of the Internet improved the accessibility of information about the travel area, the tourist is changing the trend to plan the trip such as the choice of the destination. Web services have been introduced to recommend travel destinations and travel routes according to these needs of the customers. Therefore, after reviewing some of the most popular web services today, such as Stubby planner (http://www.stubbyplanner.com) and Earthtory (http://www.earthtory.com), they were supposed to be based on traditional Traveling Salesman Problems (TSPs), and the travel routes recommended by them included some practical limitations. That is, they were not considered important issues in the actual journey, such as the use of various transportation, travel expenses, the number of days, and lodging. Moreover, although to recommend travel destinations, there have been various studies such as using IoT (Internet of Things) technology and the analysis of cyberspatial Big Data on the web and SNS (Social Networking Service), there is little research to support travel routes considering the practical constraints. Therefore, this study proposes a new mathematical model for applying to travel route recommendation service, and it is verified by numerical experiments on travel to Jeju Island and trip to Europe including Germany, France and Czech Republic. It also expects to be able to provide more useful information to tourists in their travel plans through linkage with the services for recommending tourist attractions built in the Internet environment.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.75-84
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• 2008

In 2002, the 5-day workweek policy was effective in Korea. As we have expected, the 5-day workweek policy has changed people's travel behavior during weekdays and weekends. Several studies have been done to understand these changes and impacts on transportation systems. However, these studies have only focused on travel pattern changes without considering spatial factors. Said in another way, although individual travel pattern changes are usually investigated, indices adopted cannot describe travel pattern changes in a proper way due to lack of the spatial distribution measure. This study aims to analyze travel change since the 5-day work week policy in effect using a new index (i.e. Travel Vector Index) developed in this study, which can explain travel pattern changes in terms of magnitude and spatial point of views. The new index uses a GIS technology and TCS (Toll Collection System) databases in Korea. The results in this study show that the index is very useful and reliable to measure the travel patterns changes. They are applied to TCS data set and the results show that the 5-day workweek policy significantly affects on travel behaviors.

• The Journal of the Korea Contents Association
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• v.8 no.10
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• pp.76-87
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• 2008

Prediction of travel time on road network is one of crucial research issue in dynamic route guidance system. A new approach based on Rule-Based classification is proposed for predicting travel time. This approach departs from many existing prediction models in that it explicitly consider traffic patterns during day time as well as week day. We can predict travel time accurately by considering both traffic condition of time range in a day and traffic patterns of vehicles in a week. We compare the proposed method with the existing prediction models like Link-based, Micro-T* and Switching model. It is also revealed that proposed method can reduce MARE (mean absolute relative error) significantly, compared with the existing predictors.

• International Journal of Highway Engineering
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• v.14 no.5
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• pp.113-122
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• 2012

PURPOSES: The sensitivity of $CO_2$ emissions per vehicle by a various speeds is compared according to the type of roads. METHODS: The methodology of the study are as follows: First, the sensitivity of $CO_2$ emissions per vehicle are analyzed by averaged daily travel speeds. Second, the sensitivity of $CO_2$ emissions per vehicle are analyzed by averaged hourly travel speed. Third, the sensitivity of $CO_2$ emissions per vehicle are analyzed by sectional travel speeds. RESULTS: The sensitivity that on Saturday in a week, at peak times in a day and in close location from Seoul was higher than in other situations. CONCLUSIONS: From this study, we may conclude that $CO_2$ emissions per vehicle at low speeds are generally more sensitive.

• The Journal of the Korea Contents Association
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• v.12 no.5
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• pp.459-469
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• 2012

The purpose of this study is to analyze the domestic travel activities by job characteristic and derive implications to improve the domestic tourism by using 2010 Korea National Tourism Survey data(Ministry of Culture, Sports and Tourism). We classified survey samples(1,813 persons) by 6 job characteristic categories and compared the domestic travel activities(number of travel, day of travel, expenditure of travel). As the results of analysis, the domestic travel activities of paid worker, full-time worker, employers with a 500 or more workers, biweekly five-day worker are more than non-paid worker, part-time worker, employers with a 10 or less workers, worker who work six to seven days a week.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.113-121
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• 2009

The increasing interest in leisure activities of a five-day work per week has been recently prevailed. Additionally, as internet and mobile infrastructures have been becoming widespread, the user can get specific information using a search engine. However, it is difficult for the user to get accurate information they really want as shared information has been rapidly increased and the information has been searched. For example, users can retrieve required travel information, but they also must see a huge number of travel advertisements. In this paper, we design and implement a retrieval system using travel information collecting agent. The information gathering agent regularly visits travel-related category pages of the portal sites and major media travel-article pages to collect information related to travel, and the agent stores the gathered information to a database. Then, users can search the travel information conveniently without the need to view advertisements.

• Journal of the Korean Geographical Society
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• v.34 no.1
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• pp.47-61
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• 1999

The purpose of this study is to grasp position of Sachon airport-local airport-especially the characteristics of it's air passengers, the distribution of passengers hinterland on their purposes of the travel and on the day of the week, and the spatial structure of hinterland The results is as follows The distribution of the hinterland on the purposes of a passenger's travel shows the hunterland of friend and acquauntance visit is wider than that of business, And the middle level of its size is sightseeing The hinterland of commuting includes only Chinju, so the range of passengers' social activities is wider than that of passenger' economic activities In the distribution of the hunterland on the day of the week, the distnbution of the weekday is wider than that of the holidays, but the passenger travel to Chinju is concentrated on the holidays. As rnentioned adove, the hinterland centenng around Sachon airport is Chinju sity field. Tongyoung. Sachon and Koje city field, Kwangyang city and Namhae, Sanchong, Kosung, Hadong, Uiryoung county field. It is a little different result from the area of reverse commuting of the elementray, middle and high school Leachers living in Chinju That's because air passenger travel mainly occurs in industrial and sighrseeing cities

• The Journal of Fisheries Business Administration
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• v.38 no.2
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• pp.79-101
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• 2007

The purpose of this study is to estimate the economic value of the Songieong Beach in Off-season, using a Individual Travel Cost Model(ITCM). Songieong Beach is located in Busan but far away from city. These days, however, the increased rate of traffic inflow to the Songieong beach and the five-day working week are reflected in the trend analysis. Moreover, people have changed psychological value. For that reason, visitors are on the increase on the beach in off-season. The ITCM is applied to estimate non-market value or environmental Good like a Contingent Valuation Method and Hedonic Price Model etc. The ITCM was derived from the Count Data Model(i.e. Poisson and Negative Binomial model). So this paper compares Poisson and negative binomial count data models to measure the tourism demands. The data for the study were collected from the Songjeong Beach on visitors over the a week from November 1 through November 23, 2006. Interviewers were instructed to interview only individuals. So the sample was taken in 113. A dependent variable that is defined on the non-negative integers and subject to sampling truncation is the result of a truncated count data process. This paper analyzes the effects of determinants on visitors' demand for exhibition using a class of maximum-likelihood regression estimators for count data from truncated samples, The count data and truncated models are used primarily to explain non-negative integer and truncation properties of tourist trips as suggested by the economic valuation literature. The results suggest that the truncated negative binomial model is improved overdispersion problem and more preferred than the other models in the study. This paper is not the same as the others. One thing is that Estimating Value of the Beach in off-season. The other thing is this study emphasizes in particular 'travel cost' that is not only monetary cost but also including opportunity cost of 'travel time'. According to the truncated negative binomial model, estimates the Consumer Surplus(CS) values per trip of about 199,754 Korean won and the total economic value was estimated to be 1,288,680 Korean won.

• 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.35 no.4
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• pp.348-359
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• 2017

Recently, various public transportation activation policies are being implemented in order to mitigate traffic congestion in metropolitan areas. Especially in the metropolitan area, the bus information system has been introduced to provide information on the current location of the bus and the estimated arrival time. However, it is difficult to predict the travel time due to repetitive traffic congestion in buses passing through complex urban areas due to repetitive traffic congestion and bus bunching. The previous bus travel time study has difficulties in providing information on route travel time of bus users and information on long-term travel time due to short-term travel time prediction based on the data-driven method. In this study, the path based long-term bus travel time prediction methodology is studied. For this purpose, the training data is composed of 2015 bus travel information and the 2016 data are composed of verification data. We analyze bus travel information and factors affecting bus travel time were classified into departure time, day of week, and weather factors. These factors were used into clusters with similar patterns using self organizing map. Based on the derived clusters, the reference table for bus travel time by day and departure time for sunny and rainy days were constructed. The accuracy of bus travel time derived from this study was verified using the verification data. It is expected that the prediction algorithm of this paper could overcome the limitation of the existing intuitive and empirical approach, and it is possible to improve bus user satisfaction and to establish flexible public transportation policy by improving prediction accuracy.