• Title/Summary/Keyword: Traffic Demand

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Forecasting the Demand of Railroad Traffic using Neural Network (신경망을 이용한 철도 수요 예측)

  • Shin, Young-Geun;Jung, Won-Gyo;Park, Sang-Sung;Jang, Dong-Sik
    • Proceedings of the KSR Conference
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    • 2007.05a
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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.

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Road Maintenance Planning with Traffic Demand Forecasting (장래교통수요예측을 고려한 도로 유지관리 방안)

  • Kim, Jeongmin;Choi, Seunghyun;Do, Myungsik;Han, Daeseok
    • 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.

The Development of Travel Demand Nowcasting Model Based on Travelers' Attention: Focusing on Web Search Traffic Information (여행자 관심 기반 스마트 여행 수요 예측 모형 개발: 웹검색 트래픽 정보를 중심으로)

  • Park, Do-Hyung
    • 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.

A Study on Scale Analysis of the Induced Traffic by Survey (이용자 설문을 통한 유발수요 규모 분석 - 광명역 고속철도 이용자를 중심으로 -)

  • Jo, Chang-Hee;Yu, Bo-Kuen
    • Proceedings of the KSR Conference
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    • 2010.06a
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    • pp.769-774
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    • 2010
  • KTX Introduced in korea have occurred enhanced services and reduced regional travel time. "Induced traffic" is defined in the traffic demand generated in new project. 'Induced traffic' compared to the Diversion Demand Survey and research on ways to quantify the situation, insufficient analysis of constant and long-term observations are needed to estimate the changes in demand. In this study, Induced traffic effects due to the opening of KTX for analysis survey to passengers by Railway and the scale factor induced traffic review.

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A Performance Comparison of the Partial Linearization Algorithm for the Multi-Mode Variable Demand Traffic Assignment Problem (다수단 가변수요 통행배정문제를 위한 부분선형화 알고리즘의 성능비교)

  • Park, Taehyung;Lee, Sangkeon
    • Journal of Korean Institute of Industrial Engineers
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    • v.39 no.4
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    • pp.253-259
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    • 2013
  • Investment scenarios in the transportation network design problem usually contain installation or expansion of multi-mode transportation links. When one applies the mode choice analysis and traffic assignment sequentially for each investment scenario, it is possible that the travel impedance used in the mode choice analysis is different from the user equilibrium cost of the traffic assignment step. Therefore, to estimate the travel impedance and mode choice accurately, one needs to develop a combined model for the mode choice and traffic assignment. In this paper, we derive the inverse demand and the excess demand functions for the multi-mode multinomial logit mode choice function and develop a combined model for the multi-mode variable demand traffic assignment problem. Using data from the regional O/D and network data provided by the KTDB, we compared the performance of the partial linearization algorithm with the Frank-Wolfe algorithm applied to the excess demand model and with the sequential heuristic procedures.

Change in Road Traffic Demand after the Operation of Exclusive Median Bus Lane in Seoul (서울시 중앙버스전용차로 시행에 따른 도로교통 수요 변화)

  • Yoon, Byoung-Jo
    • International Journal of Highway Engineering
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    • v.10 no.3
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    • pp.139-147
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    • 2008
  • 8 Exclusive Median Bus Lanes(EMBL) are operated in Seoul metropolitan city after the opening of Chon-ho section in 1996. But the changes in the road traffic demand on the direct and indirect influence area have not reported. In this paper, before and after survey and analysis of road traffic demand on 3 EMBLs opened in 2004 are conducted. In summary, the traffic demand of 3 EMBL road section decreased dramatically to 24.7% after the opening and then increased 1.4% after a year. The traffic demand of detour road decreased to 2.9% after the opening and then increased 0.3% after a year. Considering measurement error as ${\pm}5%$, Road traffic demands on the influence area of EMBL section are a stable state after one year. So it is presumed that the trip demand on EMBL section using vehicle does not make a detour around the influence area but divert into another transport modal.

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A Study on the Future Air Traffic Demand in Busan Metropolitan Area (부산권 항공수요예측 연구)

  • Kim, Byung-Jong;Lee, Min-Hee
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.16 no.1
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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.

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The Influence of Job Demand, Shift, Work Environment and Stressors on the Railway Traffic Controller's Health (철도관제사의 직무요구, 교대근무, 과업환경 및 스트레스 요인이 건강에 미치는 영향)

  • Kim, Jung-Gon;Shin, Tack-Hyun
    • Journal of the Korea Safety Management & Science
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    • v.18 no.4
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    • pp.73-80
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    • 2016
  • This study highlights the main effect of job demand, work shift, work environment and stressors on the railway traffic controller's health, and the moderating effect of work0life balance. The result of empirical analysis based on questionnaires received from 328 traffic controllers working at 10 railway operating companies indicates that job demand, work shift, work environment and stressors have significant effect on their health, among which stressors is a major factor. In the respect of moderating effect, WLB showed no significance except for job demand. This result implies that controller's health can not be enhanced through their individual family or leisure life. Therefore, effective countermeasures and policy to mitigate their health problems and heal their symptoms are urgent.

Traffic Demand Forecasting Method for LCCA of Pavement Section (도로포장의 생애주기비용 분석을 위한 장기 교통수요 추정)

  • Do, Myungsik;Kim, Yoonsik;Lee, Sang Hyuk;Han, Daeseok
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.33 no.5
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    • pp.2057-2067
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    • 2013
  • Traffic demand forecasting for pavement management in the present can be estimated using the past trends or subjective judgement of experts instead of objective methods. Also future road plans and local development plans of a target region, for example new road constructions and detour plans cannot be considered for the estimate of future traffic demands. This study, which is the fundamental research for developing objective and accurate decision-making support system of maintenance management for the national highway, proposed the methodology to predict future traffic demands according to 4-step traffic forecasting method using EMME in order to examine significance of future traffic demands affecting pavement deterioration trends and compare existing traffic demand forecasting methods. For the case study, this study conducted the comparison of traffic demand forecasting methods targeting Daejeon Regional Construction and Management Administration. Therefore, this study figured out that the differences of traffic demands and the level of agent costs as well as user costs between existing traffic demand forecasting methods and proposed traffic demand forecasting method with considering future road plans and local development plan.

Combined Traffic Signal Control and Traffic Assignment : Algorithms, Implementation and Numerical Results

  • Lee, Chung-Won
    • Proceedings of the KOR-KST Conference
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    • 2000.02a
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    • pp.89-115
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    • 2000
  • Traffic signal setting policies and traffic assignment procedures are mutually dependent. The combined signal control and traffic assignment problem deals with this interaction. With the total travel time minimization objective, gradient based local search methods are implemented. Deterministic user equilibrium is the selected user route choice rule, Webster's delay curve is the link performance function, and green time per cycle ratios are decision variables. Three implemented solution codes resulting in six variations include intersections operating under multiphase operation with overlapping traffic movements. For reference, the iterative approach is also coded and all codes are tested in four example networks at five demand levels. The results show the numerical gradient estimation procedure performs best although the simplified local searches show reducing the large network computational burden. Demand level as well as network size affects the relative performance of the local and iterative approaches. As demand level becomes higher, (1) in the small network, the local search tends to outperform the iterative search and (2) in the large network, vice versa.

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