• Title/Summary/Keyword: Traffic Forecasting

Search Result 228, Processing Time 0.027 seconds

An analysis of the operational efficiency of the major airports worldwide using DEA and Malmquist productivity indices (세계 주요 공항 운영 효율성 분석: DEA와 Malmquist 생산성 지수 분석을 중심으로)

  • Kim, Hong-Seop;Park, Jeong-Rim
    • Journal of Distribution Science
    • /
    • v.11 no.8
    • /
    • pp.5-14
    • /
    • 2013
  • Purpose - We live in a world of constant change and competition. Many airports have specific competitiveness goals and strategies for achieving and maintaining them. The global economic recession, financial crises, and rising oil prices have resulted in an increasingly important role for facility investment and renewal and the implementation of appropriate policies in ensuring the competitive advantage for airports. It is thus important to analyze the factors that enhance efficiency and productivity for an airport. This study aims to determine the efficiency levels of 20 major airports in East Asia, Europe, and North America. Further, this study also suggests suitable policies and strategies for their development. Research design, data, and methodology - This paper employs the DEA-CCR, DEA-BCC, and DEA-Malmquist production index analysis models to determine airport efficiency. The study uses data on the efficiency and productivity of the world's leading airports between 2006 and 2010. The input variables include the airport size, the number of runways, the size of passenger terminals, and the size of cargo terminals. The output variables include the annual number of passengers and the annual cargo volume. The study uses basic data from the 2010 World Airport Traffic Report (ACI). The world's top 20 airports (as rated by the ACI report) are investigated. The study uses the expanded DEA Model and the Super Efficiency Model to identify the most effective airports among the top 20. The Malmquist productivity index analysis is used to measure airport effectiveness. Results - This study analyzes longitudinal and cross-sectional data on the world's top 20 airports covering 2006 to 2010. A CCR analysis shows that the most efficient airports in 2010 were Gatwick Airport (LGW), Zurich Airport (ZRH), Vienna Airport (VIE), Leonardo da Vinci Fiumicino Airport (FCO), Los Angeles International Airport (LAX), Seattle-Tacoma Airport (SEA), San Francisco Airport (SFO), HongKong Airport (HKG), Beijing Capital International Airport (PEK), and Shanghai Pudong Airport (PVG). We find that changes in airport productivity are affected more by technical factors than by airport efficiency. Conclusions - Based on the study results, we offer four airport development proposals. First, a benchmark airport needs to be identified. Second, inefficiency must be reduced and high-cost factors need to be managed. Third, airport operations should be enhanced through technical innovation. Finally, scientific demand forecasting and facility preparation must become the focus of attention. This paper has some limitations. Because the Malmquist productivity index is based on the hypothesis of the, the identified production change could be over- or under-estimated. Further, as DEA estimates the relative efficiency. It also cannot generalize to include all airport conditions because the variables are limited. To measure airport productivity more accurately, other input variables and environmental variables such as financial and policy factors should be included.

Estimating Travel Demand by Using a Spatial-Temporal Activity Presence-Based Approach (시.공간 활동인구 추정에 의한 통행수요 예측)

  • Eom, Jin-Ki
    • Journal of Korean Society of Transportation
    • /
    • v.26 no.5
    • /
    • pp.163-174
    • /
    • 2008
  • The conventional four-step travel demand model is still widely used as the state-of-practice in most transportation planning agencies even though it does not provide reliable estimates of travel demand. In order to improve the accuracy of travel demand estimation, implementing an alternative approach would be critical as much as acquiring reliable socioeconomic and travel data. Recently, the role of travel demand model is diverse to satisfy the needs of microscopic analysis regarding various policies of travel demand management and traffic operations. In this context, the activity-based approach for travel demand estimation is introduced and a case study of developing a spatial-temporal activity presence-based approach that estimates travel demand through forecasting number of people present at certain place and time is accomplished. Results show that the spatial-temporal activity presence-based approach provides reliable estimates of both number of people present and trips actually people made. It is expected that the proposed approach will provide better estimates and be used in not only long-term transport plans but short-term transport impact studies with respect to various transport policies. Finally, in order to introduce the spatial-temporal activity presence-based approach, the data such as activity-based travel diary and land use based on geographic information system are essential.

A Study on Activity Type Based on Multi-dimensional Characteristics (개인의 복합적인 특성에 따른 활동유형 분석)

  • Na, Sung Yong;Lee, Seungjae;Kim, Joo Young
    • Journal of Korean Society of Transportation
    • /
    • v.32 no.5
    • /
    • pp.544-553
    • /
    • 2014
  • Activity-based models analyze individuals' various daily activities that are identified as a decision-making unit for transportation planning. In other words, it is the model that determines the types of activities according to the social, economic and situational characteristics of the groups with the same activity patterns and predicts individuals' activity time, distance, spatial movement and transportation mode. The activity-based model is a method of estimating more efficient and realistic demand in transportation forecasting because traffic is regarded as a complex decision-making process that an individual and other people participate in. In this paper, we grasp the factors affecting choice behavior of activity pattern and analyze choice behavior of activity pattern based on multi-dimensional characteristic of each person. First, we classify activity types of reviewing the trip chain and activity purpose. Next, we identified preferable activity types using complicated characteristics of main agent of activity. We concluded that choice behavior of activity pattern is dependent on complex characteristics of each agent, and further multi-dimensional characteristics of each person are affected over the whole decision process of activity schedule.

Compensation and Amendment of Highway Travel Demand Forecasting (고속도로 교통수요 보정모형에 관한 고찰)

  • Lee, Eui-Jun;Kim, Young-Sun;Yi, Yong-Ju;OH, Young-Tae;Choi, Keechoo;Yu, Jeong Whon
    • Journal of Korean Society of Transportation
    • /
    • v.31 no.3
    • /
    • pp.86-95
    • /
    • 2013
  • In this study, a model of compensation and amendment of forecasted travel demand was developed to calculate the range of values depends on the changes in the risk factors, selecting factors that might affect traffic demand changes among risk factors. Selected factors are as follows: influenced area population, the number of registrated vehicle per person, ratio of service industry workers, and city intervals. Then this model is applied to six routes of expressway and the calculated value were compensated with error rate being reflected on each quartile value with respect to influenced area population (200,000 people standards). Result from appling developed model to Cheongwon-Sangju expressway suggests that the model could compensate the error rate by more than 50%, which in turn validate the effectiveness of the model developed. Some limitations and future research agenda have also been identified.

A Prediction and Analysis for Functional Change of Ecosystem in South Korea (생태계 용역가치를 이용한 대한민국 생태계의 기능적 변화 예측 및 분석)

  • Kim, Jin-Soo;Park, So-Young
    • Journal of the Korean Association of Geographic Information Studies
    • /
    • v.16 no.2
    • /
    • pp.114-128
    • /
    • 2013
  • Rapid industrialization and economic growth have led to serious problems including reduced open space, environmental degradation, traffic congestion, and urban sprawl. These problems have been exacerbated by the absence of effective conservation and governance, and have resulted in various social conflicts. In response to these challenges, many scholar and government hope to achieve sustainable development through the establishment and management of environment-friendly planning. For this purpose, we would like to analyze functional change for ecosystem by future land-use/cover changes in South Korea. Toward this goal, we predicted land-use/cover changes from 2010 to 2060 using the future population of Statistics Korea and urban growth probability map created by logistic regression analysis and analyzed ecosystem service value using costanza's coefficient. In the case of scenario 1, ecosystem service value represented 6,783~7,092 million USD. In the case of scenario 2, ecosystem represented 6,775~7,089 million USD, 2.9~7.6 million USD decreased compared by scenario 1. This was the result of area reduction for farmland and wetland which have high environmental value relatively according to urban growth by development point of view. The results of this analysis indicate that environmentally sustainable systems and urban development must be applied to achieve sustainable development and environmental protection. Quantitative analysis of environmental values in accordance with environmental policy can help inform the decisions of policy makers and urban developers. Furthermore, forecasting urban growth based on future demand will provide more precise predictive analysis.

Analysis of Factors Affecting on the Freight Rate of Container Carriers (컨테이너 운임에 미치는 영향요인 분석)

  • Ahn, Young-Gyun;Ko, Byoung-Wook
    • Korea Trade Review
    • /
    • v.43 no.5
    • /
    • pp.159-177
    • /
    • 2018
  • The container shipping sector is an important international logistics operation that connects open economies. Freight rates rapidly change as the market fluctuates, and staff related to the shipping market are interested in factors that determine freight rates in the container market. This study uses the Vector Error Correction Model(VECM) to estimate the impact of factors affecting container freight rates. This study uses data published by Clarksons. The analysis results show a 4.2% increase in freight rates when world container traffic increases at 1.0%, a 4.0% decrease in freight rates when volume of container carriers increases by 1.0%, a 0.07% increase in freight rates when bunker price increases by 1.0%, and a 0.04% increase in freight rates accompanying 1.0% increase in libor interests rates. In addition, if the current freight rate is 1.0% higher than the long-term equilibrium rate, the freight rate will be reduced by 3.2% in the subsequent term. In addition, if the current freight rate is 1.0% lower than the long-term equilibrium rate, the freight rate will decrease by 0.12% in the following term. However, the adjusting power in a period of recession is not statistically significant which means that the pressure of freight rate increase in this case is neglectable. This research is expected to contribute to the utilization of scientific methods in forecasting container freight rates.

Development of Estimation Models for Parking Units -Focused on Gwangju Metropolitan City Condominium Apartments- (주차원단위 산정 모형 개발에 관한 연구 -광주광역시 공동 주택 아파트를 대상으로-)

  • Kwon, Sung-Dae;Ko, Dong-Bong;Park, Je-Jin;Ha, Tae-Jun
    • KSCE Journal of Civil and Environmental Engineering Research
    • /
    • v.34 no.2
    • /
    • pp.549-559
    • /
    • 2014
  • The rapid expansion of cities led to the shortage of housing in urban areas. The government compensated for this shortage through large scale residential developments that increased the housing supply. The supply of condominium apartments remains above 83% of the entire housing supply, and the proportion of apartments are at a steady increase, at about 50%. Due to the increase, illegally parked cars resulting from the shortage of parking spaces within the apartment complex have become increasingly problematic as they block the transit of emergency vehicles, and heighten the tension among neighboring residents in obtaining a parking space. Especially, the future residents are considered to plan the parking based on the estimated demand for parking. However, the parking unit method utilized to estimate the parking demand accounts for the exclusive use of space, which is believed to be far from the parking demands in reality. The reason for this discrepancy is that, as the number of households decrease, and area of exclusive space is expanded, the planned parking increases. On the other hand, when the number of households increase, and the area of exclusive space is reduced, the planned parking decreases, thus methods to recalculate the parking units based on estimated parking demand is an urgent concern. To estimate the parking units based on condominium apartments, this study first examined the existing research literature, and appointed the field of investigation to collect the necessary data. In addition, field study data and surveys collected and analyzed, in order to identify the problems underlying parking units, and problems regarding the current traffic impact assessment parking unit calculation method were deduced. Through identifying the influential factors on parking demand estimates, and performing a factorial analysis based on the collected data, the variables were selected in relation to the parking demand estimates, to develop the parking unit estimate model. Finally, through comparing and verifying the existing traffic impact assessment parking unit estimate against the newly developed model using collected data, a far more realistic parking unite estimate was suggested, reflecting the characteristics of the residents. The parking unit estimate model developed in this study is anticipated to serve as the guidelines for future parking lot legislature, as wel as the basis to provide a more realistic estimate of parking demands based on the resident characteristics of an apartment complex.

Analysis of the Long-Range Transport Contribution to PM10 in Korea Based on the Variations of Anthropogenic Emissions in East Asia using WRF-Chem (WRF-Chem 모델을 활용한 동아시아의 인위적 배출량 변동에 따른 한국 미세 먼지 장거리 수송 기여도 분석)

  • Lee, Hyae-Jin;Cho, Jae-Hee
    • Journal of the Korean earth science society
    • /
    • v.43 no.2
    • /
    • pp.283-302
    • /
    • 2022
  • Despite the nationwide COVID-19 lockdown in China since January 23, 2020, haze days with high PM10 levels of 88-98 ㎍ m-3 occurred on February 1 and 2, 2020. During these haze days, the East Asian region was affected by a warm and stagnant air mass with positive air temperature anomalies and negative zonal wind anomalies at 850 hPa. The Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) was used to analyze the variation of regional PM10 aerosol transport in Korea due to decreased anthropogenic emissions in East Asia. The base experiment (BASE), which applies the basic anthropogenic emissions in the WRF-Chem model, and the control experiment (CTL) applied by reducing the anthropogenic emission to 50%, were used to assess uncertainty with ground-based PM10 measurements in Korea. The index of agreement (IOA) for the CTL simulation was 0.71, which was higher than that of BASE (0.67). A statistical analysis of the results suggests that anthropogenic emissions were reduced during the COVID-19 lockdown period in China. Furthermore, BASE and CTL applied to zero-out anthropogenic emissions outside Korea (BASE_ZEOK and CTL_ZEOK) were used to analyze the variations of regional PM10 aerosol transport in Korea. Regional PM10 transport in CTL was reduced by only 10-20% compared to BASE. Synthetic weather variables may be another reason for the non-linear response to changes in the contribution of regional transport to PM10 in Korea with the reduction of anthropogenic emissions in East Asia. Although the regional transport contribution of other inorganic aerosols was high in CTL (80-90%), sulfate-nitrate-ammonium (SNA) aerosols showed lower contributions of 0-20%, 30-60%, and 30-60%, respectively. The SNA secondary aerosols, particularly nitrates, presumably declined as the Chinese lockdown induced traffic.