• Journal of Korea Port Economic Association
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• v.20 no.2
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• pp.53-71
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• 2004

The container throughput of China, after the joining in the WTO, has begun to increase notably. As a result, China is busy building new ports continuously. In accordance with China's situation Korea promote the development plans of ports and marketing strategy to attract the increasing cargo traffics with China, including transhipment cargoes. To build the competition strategy and the panning port for trading cargoes with China, an analysis on origin/destination is necessary. The cargo volume from/to the particular port(Korea/China) and origin/destination of traffic are important factors in the requirement for the port development. Therefore, in the era that trading with China is rapidly increasing, this study is performed to analyze the port's usage of transporting the cargos and the origin/destination of trading cargoes with china. Also this paper suggests to the competitive strategies of Pyungtaek Port to attract cargoes particularly from/to China.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.57-66
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• 2004

When we estimate an origin-destination matrix from traffic counts. origin-destination matrix estimation from traffic counts according to the selected optimal traffic counting links is method for improving the results of origin-destinaation matrix estimation and for increasing economic efficiency. This paper proposed model of selecting traffic counting links using integer program technique, and selected a traffic counting links using this model, and estimated and origin-destingtion matrix from traffic counts according to the selected optimal traffic counting links. Also, we compared a result of estimating origin-destination matrix from the selected optimal traffic counting links using this model to a result of estimating origin-destination matrix from the randomly selected traffic counting links. The error analysis result was more improved a result of origin-destination matrix estimation using this model than a result of randomly selected links.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.1708-1727
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• 2009

Even though we usually analyze logistic market based on confined railway logistics, but this study would like to judge what is potential demand transferable to railway goods through accurate analysis of railway sharing rates by the analysis of origin and destination of each item in total freight transportation market. Accordingly, by analyzing each items transferable to railway, excluding items stuck to original market, this study wants to choose some major items which are expected to lasting demand and activate railway logistics plan by focusing on major items for marketing strategy.

• Journal of Information Technology Applications and Management
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• v.20 no.1
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• pp.87-106
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• 2013

This study is to explore the airline network patterns of Incheon and Narita International Airports using passenger flight departure and arrival data of the two airports. The so-called Origin-Destination data is collected from the airports' websites and some of the important data items are flight number, city of origin, destination city, departure/arrival time, number of flights, and delay time. A snowflake schema dimensional model is proposed and implemented. Tableau Public, a well-known visual analytic tool, is used to connect the dimensional model and played an important role in navigating the data space to find interesting and visual patterns among corresponding airports and airlines. For the efficiency of analyzing this spacious data mart, data visualization method was used. Four types of visualization method proposed by Yau was used; visualizing patterns over time, visualizing proportions, visualizing relationships, and visualizing spatial relationships. The strength of connectivity of each flight segments is calculated to evaluate the degree of globalization of Seoul and Tokyo. We anticipate that various patterns and new findings produced by the data mart would provide airline managers, airport authorities, and policy makers in the field of travel and transportation with insightful information.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.4
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• pp.81-99
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• 2020

Origin-destination data have been collected and utilized for demand analysis and service design in various fields such as public transportation and traffic operation. As the utilization of big data becomes important, there are increasing needs to store raw origin-destination data for big data analysis. However, it is not practical to store and analyze the raw data for a long period of time since the size of the data increases by the power of the number of the collection points. To overcome this storage limitation and long-period pattern analysis, this study proposes a methodology for compression and origin-destination data analysis with the compressed data. The proposed methodology is applied to public transit data of Sejong and Seoul. We first measure the reconstruction error and the data size for each truncated matrix. Then, to determine a range of principal components for removing random data, we measure the level of the regularity based on covariance coefficients of the demand data reconstructed with each range of principal components. Based on the distribution of the covariance coefficients, we found the range of principal components that covers the regular demand. The ranges are determined as 1~60 and 1~80 for Sejong and Seoul respectively.

• Journal of Korea Planning Association
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• v.54 no.2
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• pp.76-83
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• 2019

This study aims to empirically identify the effect of spatial accessibility, based on travel, on housing prices in the Korean capital region. More specifically, it has two research purposes: First, investigating the effect of comprehensive spatial accessibility, based on road network and actual trips from origin to destination, on average apartment price (Korean Won per square meter) at the level of Eup, Myeon and Dong; Second, identifying better accessibility index between Hansen's and Kalogirou and Foley's ones. The former represents a road-based travel time decay function with destination trips, while the latter is a function with origin trips as well as destination ones. The study employs spatial economic models considering spatial auto-correlative relationship as an appropriate methodology with such control independent indicators as population density, road density, educational environment and distances from CBDs. Analysis results demonstrate that spatial accessibility, based on road network and actual trips from origin to destination, has a statistically significant impacts on housing price in the region. Our empirical evidence proves that the Hansen index is more appropriate than the other in estimating housing price impacts.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.14-24
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• 2018

Pedestrian movement of passengers using smart card within stations can be divided into three types of activities - straight ride and alight, line transfer, and station transfer. Straight ride and alight is transfer activity for which the card terminal and embarking line are identical. In this case, straight ride occurs at the origin station and straight alight occurs at the destination station. Line transfer refers to activity in which the subway line embarked on by the passenger is different from that which is disembarked. Succinctly, line transfer is transfer at a middle station, rather than at origin or destination stations. Station transfer occurs when the card terminal line and embarking line are different. It appears when station transfer happens at the origin station as starting transfer, and at the destination station as destination transfer. In the case of Metropolitan smart card data, origin and destination station card terminal line number data is recorded, but subway line data does not exist. Consequently, transportation card data, as it exists, cannot adequately be used to analyze pedestrian movement as a whole in subway stations. This research uses the smart card data, with its constraints, to propose an analysis model for passenger pedestrian movement within subway stations. To achieve this, a path selection model is constructed, which links origin and destination stations, and then applied for analysis. Finally, a case study of the metropolitan subway is undertaken and pedestrian volume analyzed.

• Safety and Health at Work
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• v.2 no.3
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• pp.236-242
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• 2011

Objectives: To determine the feasibility of predicting static and dynamic peak back-compressive forces based on (1) static back compressive force values at the lift origin and destination and (2) lifting speed. Methods: Ten male subjects performed symmetric mid-sagittal floor-to-shoulder, floor-to-waist, and waist-to-shoulder lifts at three different speeds (slow, medium, and fast), and with two different loads (light and heavy). Two-dimensional kinematics and kinetics were captured. Linear regression analyses were used to develop prediction equations, the amount of predictability, and significance for static and dynamic peak back-compressive forces based on a static origin and destination average (SODA) backcompressive force. Results: Static and dynamic peak back-compressive forces were highly predicted by the SODA, with R2 values ranging from 0.830 to 0.947. Slopes were significantly different between slow and fast lifting speeds (p < 0.05) for the dynamic peak prediction equations. The slope of the regression line for static prediction was significantly greater than one with a significant positive intercept value. Conclusion: SODA under-predict both static and dynamic peak back-compressive force values. Peak values are highly predictable and could be readily determined using back-compressive force assessments at the origin and destination of a lifting task. This could be valuable for enhancing job design and analysis in the workplace and for large-scale studies where a full analysis of each lifting task is not feasible.

• Korea Journal of Hospital Management
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• v.23 no.2
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• pp.28-41
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• 2018

Purpose: This study purposed to analyze the spatial accessibility of mental health institutions in Ganwon-Do using Geographic Information System and to suggest policy implications. Methodology: Network analysis was applied to assess the spatial accessibility of mental health institutions in Gangwon-Do. To perform the network analysis, network data set was built using administrative district map, road network, address of mental health institutions in Gangwon-Do. After building network data set, Two network analysis methods, 1) Service area analysis, 2) Origin Destination cost matrix were applied. Service area analysis calculated accessive areas that were within specified time. And using Origin Destination cost matrix, travel time and road travel distance were calculated between centroids of Eup, Myeon, Dong and the nearest mental health institutions. Result: After the service area analysis, it is estimated that 19.63% of the total areas in Gangwon-Do takes more than 60 minutes to get to clinic institutions. For hospital institutions, 23.08% of the total areas takes more than 60 minutes to get there. And 59.96% of Gangwon-do takes more than 30 minutes to get to general hospitals. The result of Origin-Destination cost matrix showed that most Eup Myeon Dong in Gangwon-Do was connected to the institutions in Wonju-si, Chuncheon-si, Gangneung-si. And it showed that there were large regional variation in time and distance to reach the institutions. Implication: Results showed that there were regional variations of spatial accessibility to the mental health institutions in Gangwon-Do. To solve this problem, Several policy interventions could be applied such as mental health resources allocation plan, telemedicine, providing more closely coordinated services between mental health institutions and community mental health centers to enhance the accessibility.

• Korean Journal of Hazardous Materials
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• v.6 no.2
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• pp.68-76
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• 2018

This study aims to provide a methodological framework to estimate the travel demand of hazardous materials transporting vehicles by link and analyze daily traffic patterns on an expressway to develop safety roadway management strategies. Traffic volume of hazardous material vehicles is counted through the on-site investigation at twenty-five tollgates on the expressway, and their demands by a link are predicted through origin-destination flows estimation. The result shows that the number of the domestic hazardous materials vehicles is approximately 51,207 vehicles per day and it indicates that hazardous materials transport vehicles account for 1.5% of total daily traffic on the internal expressway and 6.2% of total cargo traffic volumes. This study roughly estimated how many hazardous materials vehicles pass through the expressway segment. Thus it is expected to be utilized for establishing a systematic highway management strategy in the future by calculating the traffic volume of the hazardous material vehicles traveling on the interstate expressway.