• 한국철도학회:학술대회논문집
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• 한국철도학회 2007년도 춘계학술대회 논문집
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• pp.1931-1936
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• 2007

Demand forecasting for railroad traffic is fairly important to establish future policy and plan. The future demand of railroad traffic can be predicted by analyzing the demand of air, marine and bus traffic which influence the demand of railroad traffic. In this study, forecasting the demand of railroad traffic is implemented through neural network using the demand of air, marine and bus traffic. Estimate accuracy of the demand of railroad traffic was shown about 84% through neural net model proposed.

• 한국도로학회논문집
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• 제18권3호
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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.

• 대한토목학회논문집
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• 제33권5호
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• pp.2057-2067
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• 2013

기존의 포장관리를 위한 장래 교통수요의 추정에는 객관적인 방법에 의한 장래 교통수요의 추정이라기보다는 과거 추세(trends)나 분석가의 주관적인 판단에 의해 이루어졌다고 할 수 있으며, 새로운 도로의 신설 및 우회도로의 계획 등 대상 지역의 장래 도로 및 지역개발 계획을 전혀 고려하지 못한 교통수요의 추정이 이루어졌다고 할 수 있다. 본 연구에서는 보다 객관적이며 정도 높은 국도의 유지관리를 위한 의사결정지원시스템(decision-making support system)의 구축을 위한 기초연구로써 장래 포장의 공용성에 큰 영향을 미치는 장기 교통수요 예측의 중요성을 살펴보고 기존 교통수요 추정 방식과의 비교를 위한 기준(baseline) 수요를 산정하기 위해 EMME(Equilibre multimodal, Multimodal Equilibrium)를 이용하여 4단계 교통수요 추정 방법에 따라 장래 교통수요를 예측하는 방안을 제시하였다. 사례연구를 위해 본 연구에서는 대전지방국토관리청 관할의 일부 지역을 대상으로 교통수요 추정방안별 비교를 수행하였으며, 기존의 수요추정 방법과 본 연구에서 제시한 장래 지역개발계획과 도로의 신설 및 확장계획 등을 고려한 교통수요 추정방법과는 교통량의 수요뿐만 아니라 관리자비용 및 이용자비용의 수준에도 큰 괴리가 있음을 확인하였다.

• 한국항공운항학회지
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• 제16권1호
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• pp.46-57
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• 2008

Since the 90's, Korean Air transport market has been more expanded because of economic growth, the construction of airport infrastructure, and the advent of low cost carrier. Especially, the air traffic demand in Busan metropolitan area has been increasing steadily. Therefore, in this paper, we developed a new forecasting model which could expect the future air traffic demand in Busan area. This model is developed by regression analysis using social-economic variables such as GRDP, income, and the number of people, and dummy variables, for instance, KTX opening, Japan economic depression, SARS and so on. Result from demand forecasting by this new model suggests that the new airport system is needed in order to sustain the increasing air traffic demand in Busan area.

• 산업공학
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• 제18권3호
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• pp.333-342
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• 2005

In this paper, we propose an efficient forecasting methodology of the mid and long-term frequency demand in Korea. The methodology consists of the following three steps: classification of basic service group, calculation of effective traffic, and frequency forecasting. Based on the previous studies, we classify the services into wide area mobile, short range radio, fixed wireless access and digital video broadcasting in the step of the classification of basic service group. For the calculation of effective traffic, we use the measures of erlang and bps. The step of the calculation of effective traffic classifies the user and basic application, and evaluates the effective traffic. Finally, in the step of frequency forecasting, different methodology will be proposed for each service group and its applications are presented.

• KDI Journal of Economic Policy
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• 제35권4호
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• pp.31-61
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• 2013

민간투자 도로사업의 경우, 사업의 미래 수익성과 직접적으로 관련 있는 예측 교통량의 불확실성과 이에 따른 위험이 민간 운영자에게 이전된다. 따라서 교통량 예측위험이 민간투자 도로사업의 추진에 어느 정도 영향을 미치며, 이러한 위험의 실제적인 경제적 가치를 파악하는 것은 민간투자사업의 적격성을 파악하고 이를 높일 수 있는 중요한 정보이다. 본 논문의 목적은 민간투자 도로사업의 교통수요 예측위험의 경제적 가치를 산정하는 것이다. 이를 위해 예측 교통량은 불확실성이 존재하는 확률변수이며, 시간이 경과하면서 기하 브라운 운동을 따른다고 가정한 후 민간투자사업의 가치변동성을 예측하는 방안을 제안하였다. 특히 본 논문에서는 개통 후 도로사업의 교통량 형성 특성을 고려한 램프업 기간 전후의 상이한 교통량 증가율과 그 변동성을 적용하여 단순히 임의적으로 가정한 기존 연구와 차별화하였다 사례 사업분석 결과, 예측된 해당 민간투자사업의 교통수요 예측 리스크 프리미엄은 출자 건설회사의 시가총액을 고려하지 않고 단순평균하는 경우 7.39%, 시가총액을 가중하여 평가하는 경우 8.30%로 분석되었으며, 교통수요 예측위험에 따른 해당 민간투자사업의 가치변동성은 17.11%로 예측되었다. 할인율이 클수록 프로젝트의 가치변동성은 작아졌는데, 비용의 고정으로 인한 레버리지 효과는 교통량 변동성보다 프로젝트의 가치변동성을 크게 하였다. 교통수요 예측위험에 따른 민간투자사업의 가치변동률과 리스크 프리미엄을 통해 산출하는 사례 민간투자사업 교통량 예측위험의 시장가치는 0.42~0.50 사이로 분석되었는데, 이는 교통량 변동성이 1% 증가하거나 감소하면 이에 따른 해당 프로젝트 위험 프리미엄은 0.42~0.50% 증가하거나 감소함을 의미한다.

• 정보학연구
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• 제5권4호
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• pp.173-183
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• 2002

본 논문에서는 무선통신 서비스를 위한 필수 자원인 주파수의 수요예측 방법론을 제시한다. 이는 효율적인 국내 전파자원 관리를 위해 필수적인 업무이다. 제안한 방법론은 크게 기본 서비스군 분류, 유효 트래픽 도출 및 주파수 수요예측의 세단계로 구성된다. 기본 서비스군 분류 단계에서는 기존의 주파수 수요예측 방법론의 결과를 이용하여 서비스를 Wide area mobile, Short range radio, Fixed wireless access 및 Digital video broadcasting으로 나누며, 유효 트래픽 도출 단계에서는 총 트래픽을 erlang 및 bps 단위로 환산하여 구하는 방법을 제안한다. 구체적으로 유효 트래픽 도출 단계에서는 사용자 분류, 기본 어플리케이션 분류 및 어플리케이션별 유효 트래픽 추정의 과정을 거친다. 끝으로, 주파수 수요예측 단계에서 각 서비스군별로 서로 다른 주파수 수요예측 방법론을 제시한다.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2005년도 추계학술대회 논문집
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• pp.889-896
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• 2005

While a year and a half has been passed since the launch of KTX service, traffic volume of Gyung-bu High Speed Railway is still much lower than the forecasted value. This situation has been badly affecting not only Korail's financial status but also KRNA's general railway construction projects as general public responds negatively to such projects as New Ho-nam Line Construction. This paper outlines traffic volume forecasting methodologies applied to construction of Gyung-bu High Speed Railway, identifies major causes of forecasting deviations. and finally extracts problems through comparison between the forecasted results and actual traffic volume.

• 대한교통학회지
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• 제7권2호
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• pp.29-43
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• 1989

The purpose of this study is to construct a forecasting model involved in a diverted traffic volume of the 2nd intra-urban expressway in construction presently, in the case of the future prediction of traffic demand for the intra-urban expressway in Pusan. In this study, the model involved in a diverted traffic volume is constructed trustworthy. And the future traffic demand of intra-urban expressway by this model was forecasted 114,005 volume/daily in 1996 and 147,090 volume/daily in 2001. However, it will made a study more and more concretely for practicality and limitation as well as construction of the forecasting model considered an intrinsic problem of an observational error and necessity of survey for much more socio-economic data, the traffic volume on all orad and OD pairs in Pusan.

• 한국정보시스템학회지:정보시스템연구
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• 제26권3호
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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.