• Journal of KIBIM
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• v.13 no.4
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• pp.106-114
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• 2023

In this study, we developed a method to quantify urban social costs using mobile sensing data, providing a novel approach to urban planning. By collecting and analyzing extensive mobile data over time, we transformed travel patterns into measurable social costs. Our findings highlight the effectiveness of big data in urban planning, revealing key correlations between transportation modes and their associated social costs. This research not only advances the use of mobile data in urban planning but also suggests new directions for future studies to enhance data collection and analysis methods.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.443-452
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• 2011

This study analyzed passenger travel patterns especially for the transfer from metro to bus by using transit smart card data. We classified three types of land use such as residential, business, and shopping area where metro stations are located. The results show that more number of transfers was observed at residential area compared to that of shopping and business area. Also, more number of transfers from metro to arterial bus was observed than that of transfers to local bus. Further, the high number of transfers to arterial bus was observed at business and shopping area. This means that the transfer to bus at metro stations varies by land use. The egress walk distance from metro station was found to be approximately 400 meters and the average walk distance of young people was found to be shorter than that of the old.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.195-208
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• 2009

A network design problem (NDP) formulated as a mathematical program is generally used to find an optimum value to minimize or to maximize some objectives such as total travel time, social benefit, or others. NDP has, however, some limits of describing components of travel patterns like activities and trip generation due to its modeling simplicity, and also it has difficulty in including attributes of regional planning. In order to cope with such limits, this paper extends NDP to the urban planning field and proposes a mathematical program which can describe the interactions between urban social activities and transportation planning. Based on this model the authors try to optimize both urban activities and the transportation system. The model developed in this paper is tested to assess its application with a real-size regional transportation network.

• Journal of People, Plants, and Environment
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• v.23 no.2
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• pp.233-243
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• 2020

This study collects social big data used in various fields in the past 9 years and explains the patterns of major keywords of the arboretums and botanical gardens to use as the basic data to establish operational strategies for future arboretums and botanical gardens. A total of 6,245,278 cases of data were collected: 4,250,583 from blogs (68.1%), 1,843,677 from online cafes (29.5%), and 151,018 from knowledge search engine (2.4%). As a result of refining valid data, 1,223,162 cases were selected for analysis. We came up with keywords through big data, and used big data program Textom to derive keywords of arboretums and botanical gardens using text mining analysis. As a result, we identified keywords such as 'travel', 'picnic', 'children', 'festival', 'experience', 'Garden of Morning Calm', 'program', 'recreation forest', 'healing', and 'museum'. As a result of keyword analysis, we found that keywords such as 'healing', 'tree', 'experience', 'garden', and 'Garden of Morning Calm' received high public interest. We conducted word cloud analysis by extracting keywords with high frequency in total 6,245,278 titles on social media. The results showed that arboretums and botanical gardens were perceived as spaces for relaxation and leisure such as 'travel', 'picnic' and 'recreation', and that people had high interest in educational aspects with keywords such as 'experience' and 'field trip'. The demand for rest and leisure space, education, and things to see and enjoy in arboretums and botanical gardens increased than in the past. Therefore, there must be differentiation and specialization strategies such as plant collection strategies, exhibition planning and programs in establishing future operation strategies.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.1
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• pp.29-48
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• 2014

The recent keyword advertising does not reflect the individual customer searching pattern because it is focused on each keyword at the aggregate level. The purpose of this research is to observe processes of customer searching patterns. To be specific, individual deal-proneness is mainly concerned. This study incorporates location as a control variable. This paper examines the relationship between customers' searching patterns and probability of purchase. A customer searching session, which is the collection of sequence of keyword queries, is utilized as the unit of analysis. The degree of deal-proneness is measured using customer behavior which is revealed by customer searching keywords in the session. Deal-proneness measuring function calculates the discount of deal prone keyword leverage in accordance with customer searching order. Location searching specificity function is also calculated by the same logic. The analyzed data is narrowed down to the customer query session which has more than two keyword queries. The number of the data is 218,305 by session, which is derived from Internet advertising agency's (COMAS) advertisement managing data and the travel business advertisement revenue data from advertiser's. As a research result, there are three types of the deal-prone customer. At first, there is an unconditional active deal-proneness customer. It is the customer who has lower deal-proneness which means that he/she utilizes deal-prone keywords in the last phase. He/she starts searching a keyword like general ones and then finally purchased appropriate products by utilizing deal-prone keywords in the last time. Those two types of customers have the similar rates of purchase. However, the last type of the customer has middle deal-proneness; who utilizes deal-prone keywords in the middle of the process. This type of a customer closely gets into the information by employing deal-prone keywords but he/she could not find out appropriate alternative then would modify other keywords to look for other alternatives. That is the reason why the purchase probability in this case would be decreased Also, this research confirmed that there is a loyalty effect using location searching specificity. The customer who has higher trip loyalty for specificity location responds to selected promotion rather than general promotion. So, this customer has a lower probability to purchase.

• Journal of Korean Society of Transportation
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• v.32 no.4
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• pp.303-314
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• 2014

This study develops a $CO_2$ emissions estimation method, which considers different O/D travel patterns and through traffic volumes, in different regions for $CO_2$ emissions management in the field of transportation. In the research, O/D and network data provided by the Korea Transport Database (KTDB) Center are used as basic data. The results show that the total emission was similar to the Metropolitan's total emission which was estimated by KTDB (2009). With the analysis focusing on Gyeonggi-do, the results show that $CO_2$ emission from through traffic volumes was greater than $CO_2$ emissions of the Intra-Regional in southern regions; By contrast, $CO_2$ emissions of the Intra-Regional was greater than that from through traffic volumes in northern regions. Therefore, the $CO_2$ emissions management needs to be segregated into local government and nation with each travel pattern.

• Journal of the military operations research society of Korea
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• v.2 no.1
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• pp.127-143
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• 1976

The purpose of this thesis is to study the optimal arrangement of aircraft instrument panels through the human factors approach. Human factors engineering is the process of effectively fitting the human component to the machine component in any man-machine system. The human factors. are especially important to an aircraft pilot who must constantly shift his attention between the instrument panel within the cockpit and the surrounding area of the aircraft. The preliminary part of this study is to find the general patterns of the Korean pilot's eye movements during their various flying maneuvers, and which instruments require the most attention while in flight. It is assumed that all pilots have a general pattern of eye movement when observing the aircraft instrument panel and that an optimum arrangement would be to minimize the eye travel distance between instruments. In this thesis the arrangements of instruments is taken to be the independent variable and the eye travel distance between instruments the dependent variable. la order to compile the information necessary for this study, sixty Korean Air Force pilots were interviewed and requested to complete information forms. These information forms listed various flying maneuvers and listed each instrument used on the instrument panel. The compilation of the information on these completed forms listed the instruments most frequently used by the pilots. The second part of this study was to determine the optimum instrument arrangement. It was necessary to study the various number of possible arrangements of instruments depending upon the number of instruments involved. Therefore, these instruments are grouped by two major functions, The flight instruments were subdivided into three groups, and the engineering instruments were subdivided into six groups. With this subdivision we arrive at the possible number of arrangements of 4,320. Through the simulation method, total eye travel distance for each of these 4,320 arrangements is calculated and the arrangement which appears to be of optimum distance between the most frequently used aircraft instruments is determined. The results of this study indicate that the optimum distance between instruments would be 33,028cm and that the corresponding distance of the instrument panel now being used is 34,288cm. Therefore, an increased efficiency of $3.8\%$ would be realized if the existing aircraft instrument panel were re-arranged according to layout proposed in this thesis.

• Journal of the Economic Geographical Society of Korea
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• v.11 no.1
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• pp.59-77
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• 2008

The purpose of this study is to investigate the impact of traffic-related air pollution on the urban population in the Metropolitan Seoul area. In particular, this study analyzes urban population exposure to traffic-related particulate materials(PM). For the purpose, this study examines the relationships between traffic flows and PM concentration levels during the last fifteen years. Traffic volumes have been decreased significantly in recent year in Seoul, however, PM levels have been declined less compare to traffic volumes. It may be related with the rapid growth in the population and vehicle numbers in Gyenggi, the outskirt of Seoul, where several New Towns have been developed in the middle of 1990's. The spatial pattern of commuting has changed, and thus and travel distances and traffic volumes have increased along the main roads connecting CBDs in Seoul and New Towns consisting of large residential apartment complexes. These changes in traffic flows and travel behaviors cause increasing exposure to traffic-related air pollution for urban population over the Metropolitan Seoul area. GIS techniques are applied to analyze the spatial patterns of traffic flows, population distributions, PM distributions, and passenger flows comprehensively. This study also analyzes real time base traffic flow data and passenger flow data obtained from T-card transaction database applying data mining techniques. This study also attempts to develop a space-time model for assessing journey-time exposure to traffic related air pollutants based on travel passenger frequency distribution function. The results of this study can be used for the implications for sustainable transport systems, public health and transportation policy by reducing urban air pollution and road traffics in the Metropolitan Seoul area.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.7-16
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• 2004

The homogeneous road section is defined as one consisted of similar traffic characteristics focused on demand and supply. The criteria, in the aspect of demand, are the diverging rate and the ratio of green time to cycle time at signalized intersection, and distance between the signalized intersections. The criteria, in that or supply, are the traffic patterns such as traffic volume and its speed. In this study, the effective method to generate valuable data, pointing out the problems of removal method of obscure data, is proposed using data collected from Gonjiam IC to Jangji IC on the national highway No.3. Travel times are collected with licence matching method and traffic volume and speed are collected from detectors. Futhermore, the method of selecting homogeneous road section is proposed considering demand and supply aspect simultaneously. This method using outlier filtering algorithm can be applied to generate the travel time forecasting model and to revise the obscured of missing data transmitting from detectors. The point and link data collected at the same time on the rational highway can be used as a basis predicting the travel time and revising the obscured data in the future.

• Journal of Korea Spatial Information System Society
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• v.10 no.3
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• pp.55-65
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• 2008

For obtaining telematics traffic information(travel time or speed in an individual link), there are many kinds of devices to collect traffic data. Since the GPS satellite signals have been released to civil society, thank to the development of GPS technology, the GPS has become a very useful instrument for collecting traffic data. GPS can reduce the cost of installation and maintenance in contrast with existing traffic detectors which must be stationed on the ground. But. there are Problems when GPS data is applied to the existing filtering techniques used for analyzing the data collected by other detectors. This paper proposes a method to provide users with correct traffic information through filtering abnormal data caused by the unusual driving in collected data based on GPS. We have developed an algorithm that can be applied to real-time GPS data and create more reliable traffic information, by building patterns of past data and filtering abnormal data through selection of filtering areas using Quartile values. in order to verify the proposed algorithm, we experimented with actual traffic data that include probe cars equipped with a built-in GPS receiver which ran through Gangnam Street in Seoul. As a result of these experiments, it is shown that link travel speed data obtained from this algorithm is more accurate than those obtained by existing systems.