• International Journal of Highway Engineering
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• v.18 no.3
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• pp.47-57
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• 2016

PURPOSES : This study aims to examine the differences between the existing traffic demand forecasting method and the traffic demand forecasting method considering future regional development plans and new road construction and expansion plans using a four-step traffic demand forecast for a more objective and sophisticated national highway maintenance. This study ultimately aims to present future pavement deterioration and budget forecasting planning based on the examination. METHODS : This study used the latest data offered by the Korea Transport Data Base (KTDB) as the basic data for demand forecast. The analysis scope was set using the Daejeon Metropolitan City's O/D and network data. This study used a traffic demand program called TransCad, and performed a traffic assignment by vehicle type through the application of a user equilibrium-based multi-class assignment technique. This study forecasted future traffic demand by verifying whether or not a realistic traffic pattern was expressed similarly by undertaking a calibration process. This study performed a life cycle cost analysis based on traffic using the forecasted future demand or existing past pattern, or by assuming the constant traffic demand. The maintenance criteria were decided according to equivalent single axle loads (ESAL). The maintenance period in the concerned section was calculated in this study. This study also computed the maintenance costs using a construction method by applying the maintenance criteria considering the ESAL. The road user costs were calculated by using the user cost calculation logic applied to the Korean Pavement Management System, which is the existing study outcome. RESULTS : This study ascertained that the increase and decrease of traffic occurred in the concerned section according to the future development plans. Furthermore, there were differences from demand forecasting that did not consider the development plans. Realistic and accurate demand forecasting supported an optimized decision making that efficiently assigns maintenance costs, and can be used as very important basic information for maintenance decision making. CONCLUSIONS : Therefore, decision making for a more efficient and sophisticated road management than the method assuming future traffic can be expected to be the same as the existing pattern or steady traffic demand. The reflection of a reliable forecasting of the future traffic demand to life cycle cost analysis (LCCA) can be a very vital factor because many studies are generally performed without considering the future traffic demand or with an analysis through setting a scenario upon LCCA within a pavement management system.

• Electronics and Telecommunications Trends
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• v.34 no.3
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• pp.106-113
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• 2019

Mobile traffic is one of the most important indexes of the growth of the mobile communications market, and it has a close relationship with subscribers' service usage patterns, frequency demand and supply, network management, and information communication policy. The purpose of this paper is to understand mobile data usage in Korea and to suggest the optimal steps for establishing the frequency supply and demand system by researching the traffic trends that reflect the characteristics of radio resources in the mobile communications field. To achieve this goal, attempts were made to increase the possibility of policy use by analyzing and forecasting mobile traffic trends, and to improve the accuracy of the research through the verification of the existing prediction results. The paper ends with a discussion of the necessity of a frequency management system based on data science.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.2309-2318
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• 2010

It is a plan the government increases a railroad section SOC investment, and to activate railroad construction while a railroad wins the spotlight with green transportation. But an error of the demand forecast that is a base of a railroad investment evaluation follows in occurring big, there is it with an operation with an obstacle of a railroad investment. Case of the Incheon International Airport Railroad which went into operation recently, While a present transportation demand showed about 10% than a demand forecasted in a past conference, it was magnified in a social problem. A lot of research was gone on in road project about traffic demand forecast and error, a study to find out the error cause is an insufficient situation although errors of a railroad occurs big. So, this study looked for errors and causes about trip generation model and modes sharing model of railroad demand forecast but it was defined causes so that it can occur similar problems in the future. Especially it investigated causes after comparing rate of development plan for the realization and O/D size in trip generation model and after comparing rate of modes sharing of past and current and conducting a survey for airport users. In conclusion, it suggested method to reduce errors of railroad demand forecasting in the future.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.101-115
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• 2008

This study reports UTIS(Urban Traffic Information System), which has been generalized in developed countries through brisk research and development and is being promoted for introduction by National Police Agency and Road Traffic Authority to reduce the astronomical amount of social expenses including traffic congestion expenses. Also this study investigates the proper charges for using by the preestimate of demand and contentment according to methods of payment after the service is introduced. The results of this study are as follows. First, demand forecast model is constructed by Binary Logit Model. Second, forecast models of using aspects of UTIS service according to methods of payment are established by Ordered Probit Model. Third, the proper charges for using of UTIS service according to methods of payment are presented to the supplier in the aspects of users. For this, preferences by using aspects and methods of payment are captured. And unit elasticity of coefficient of utilization is understood through responsiveness analysis according to methods of payment.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.638-644
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• 2008

Mungyeng line(Jupyung${\sim}$Mungyeng) was closed due to a rapid decrease in demand in 1995. However, as the rail transportation demand is expected to increase with the plan to develop a tourist resort and a traffic network in Mungyeng area, it is required to forecast future demand to meet the change of transportation environment in this region. This study predicts the rail transportation demand and analyzes financial benefit in operator's side in case of reopening this line, based on nation-wide traffic volume data from Korean Transportation Database(KTDB). The results of this research can be applied to not only establishing a train operation plan also improving customer service. Moreover, Korail will have an opportunity to develop new business by linking train service to tourist attractions around the Mungyeng area.

• The Journal of Information Systems
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• v.26 no.3
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• pp.171-185
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• 2017

Purpose Recently, there has been an increase in attempts to analyze social phenomena, consumption trends, and consumption behavior through a vast amount of customer data such as web search traffic information and social buzz information in various fields such as flu prediction and real estate price prediction. Internet portal service providers such as google and naver are disclosing web search traffic information of online users as services such as google trends and naver trends. Academic and industry are paying attention to research on information search behavior and utilization of online users based on the web search traffic information. Although there are many studies predicting social phenomena, consumption trends, political polls, etc. based on web search traffic information, it is hard to find the research to explain and predict tourism demand and establish tourism policy using it. In this study, we try to use web search traffic information to explain the tourism demand for major cities in Gangwon-do, the representative tourist area in Korea, and to develop a nowcasting model for the demand. Design/methodology/approach In the first step, the literature review on travel demand and web search traffic was conducted in parallel in two directions. In the second stage, we conducted a qualitative research to confirm the information retrieval behavior of the traveler. In the next step, we extracted the representative tourist cities of Gangwon-do and confirmed which keywords were used for the search. In the fourth step, we collected tourist demand data to be used as a dependent variable and collected web search traffic information of each keyword to be used as an independent variable. In the fifth step, we set up a time series benchmark model, and added the web search traffic information to this model to confirm whether the prediction model improved. In the last stage, we analyze the prediction models that are finally selected as optimal and confirm whether the influence of the keywords on the prediction of travel demand. Findings This study has developed a tourism demand forecasting model of Gangwon-do, a representative tourist destination in Korea, by expanding and applying web search traffic information to tourism demand forecasting. We compared the existing time series model with the benchmarking model and confirmed the superiority of the proposed model. In addition, this study also confirms that web search traffic information has a positive correlation with travel demand and precedes it by one or two months, thereby asserting its suitability as a prediction model. Furthermore, by deriving search keywords that have a significant effect on tourism demand forecast for each city, representative characteristics of each region can be selected.

• Electronics and Telecommunications Trends
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• v.35 no.6
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• pp.129-136
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• 2020

Korea launched the world's first commercial 5G services in April 2019. Mobile traffic is expected to increase further with the acceleration of mobile-centric data utilization. It is one of the most important indexes of the growth of the mobile communications market, and it has a close relationship with frequency demand and supply, network management, and information communication policy. To overcome the limitations of an analytical solution due to the high complexity of the real world, this paper estimates the diffusion of 5G users using systemic thinking and the behavior of individual agents. Based on these demand forecasts, contributions to the establishment of strategic policies are suggested. For better understanding, global 5G predictions of subscribers and mobile traffic are also compared.

• Proceedings of the KSR Conference
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• 2005.11a
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• pp.884-888
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• 2005

The interests of the government and civil business owner against the Light rail transit are increasing, it may be caused by the enterprise conception which does not consider a city circumstance that the construction plan is insensitively performed. This article present the forecast method of minimum transportation demand which secures a profitability. If It is in advance investigated the number of passenger using the existing traffic system of the area, it will be possible that the LRT project is planned on a realistic basis.

• Journal of Korean Society of Transportation
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• v.22 no.4 s.75
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• pp.117-134
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• 2004

Truck traffic accounts for a substantial fraction of the traffic stream in many regions and is often the source of localized traffic congestion, potential parking and safety problems. Truck trips tend to be ignored or treated superficially in travel demand models. It reduces the effectiveness and accuracy of travel demand forecasting and may result in misguided transportation policy and project decisions. This paper presents the development of speed-flow relationships with truck impacts based on CORSIM simulation results in order to enhance travel demand model by incorporating truck trips. The traditional BPR(Bureau of Public Road) function representing the speed-flow relationships for roadway facilities is modified to specifically include the impacts of truck traffics. A number of new speed-flow functions have been developed based on CORSIM simulation results for freeways and urban arterials.

• Journal of the Korean Society of Marine Environment & Safety
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• v.19 no.6
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• pp.612-620
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• 2013

In this study, time series analysis was tried, which is widely applied to demand forecast of diverse fields such as finance, economy, trade, and so on, different from previous regression analysis. Future marine traffic volume was forecasted on the basis of data of the number of ships entering Incheon port from January 1996 to June 2013, through courses of stationarity verification, model identification, coefficient estimation, and diagnostic checking. As a result of prediction January 2014 to December 2015, February has less traffic volume than other months, but January has more traffic volume than other months. Also, it was found out that Incheon port was more proper to ARIMA model than exponential smoothing method and there was a difference of monthly traffic volume according to seasons. The study has a meaning in that future traffic volume was forecasted per month with time series model. Also, it is judged that forecast of future marine traffic volume through time series model will be the more suitable model than prediction of marine traffic volume with previous regression analysis.