• Title/Summary/Keyword: Traffic Volume Data

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An Improvement of Backhaul Transport with the Mathematical Model of Inter-Terminal Transportation Using Buffer Space (완충지역을 활용한 타부두 환적 컨테이너 운송 모형의 복화율 개선 효과 분석)

  • Park, Hyoung-Jun;Shin, Jae-Young
    • Journal of Navigation and Port Research
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    • v.46 no.3
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    • pp.236-242
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    • 2022
  • Busan Port is operated separately by a number of terminal operators, resulting in a large number of ITT (Inter-Terminal Transportation) volumes. The occurrence of ITT volume causes various problems such as additional transportation cost, empty truck trips, truck delays and terminal congestion, weakening Busan Port's competitiveness. Among them, the empty truck trip problem is a representative factor, that exacerbates the cost problem of the ITT operation at Busan Port. But the ITT backhaul rate at Busan Port remains low. To strengthen the transhipment competitiveness of Busan Port, it is necessary to increase the ITT backhaul rate. In this paper, to improve ITT backhaul rate, we present a mathematical model for maximizing backhaul transport using buffer space. And we analyzed the improving effects of backhaul transport using buffer space through experiments based on actual operating data.

An Empirical Study on the Subscribers' Usage and Attitude in the Korean Mobile Service Market (최근 국내 이동통신서비스 이용행태 분석)

  • Yu, J.E.;Lee, S.J.
    • Electronics and Telecommunications Trends
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    • v.37 no.3
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    • pp.74-84
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    • 2022
  • The Korean mobile service market has persistently grown with the number of subscribers and volume of mobile traffic. It shows the slow diffusion of 5G subscribers, and rapid growth of both the MVNO(Mobile Virtual Network Operator) market and unlocked mobile phones. Therefore, this study derives the direction of telcos' strategies and policy implications by empirically analyzing the usage and attitude of LTE and 5G subscribers. Our major findings are as follows: First, our current mobile service subscription market constitutes most long-term customers for their incumbent carriers only by device change from lock-in with bundle services. Mobile tariffs, data speed, and benefits of bundle services are important factors affecting choices and customers' satisfaction with a provider and intentions of churning to another. Second, demand and satisfaction for using 5G are less because speeds and service tariffs act as pain points for 5G services. Third, the users' high preferences for MVNOs and unlocked mobile phones are linked to their subscription to MVNOs' low-cost plans with unlocked mobile phones on online channels. These streams lead to a big change in the market competition that MNO(Mobile Network Operator)s' market shares are expected to decrease and MVNOs' shares will be increased by two times, in the near future. Therefore, MNOs need to change their distribution strategies from offline to online channels and try to resolve the stereotype, "mobile tariffs are expensive," by enhancing their service values. Finally, as consumers prefer one-stop service in the same channel regardless of the distribution channel, policies should focus on the consumers' needs for convenience rather than on the channel separation for perfectly unlocked mobile phones.

Predicting Determinants of Seoul-Bike Data Using Optimized Gradient-Boost (최적화된 Gradient-Boost를 사용한 서울 자전거 데이터의 결정 요인 예측)

  • Kim, Chayoung;Kim, Yoon
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.6
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    • pp.861-866
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    • 2022
  • Seoul introduced the shared bicycle system, "Seoul Public Bike" in 2015 to help reduce traffic volume and air pollution. Hence, to solve various problems according to the supply and demand of the shared bicycle system, "Seoul Public Bike," several studies are being conducted. Most of the research is a strategic "Bicycle Rearrangement" in regard to the imbalance between supply and demand. Moreover, most of these studies predict demand by grouping features such as weather or season. In previous studies, demand was predicted by time-series-analysis. However, recently, studies that predict demand using deep learning or machine learning are emerging. In this paper, we can show that demand prediction can be made a little better by discovering new features or ordering the importance of various features based on well-known feature-patterns. In this study, by ordering the selection of new features or the importance of the features, a better coefficient of determination can be obtained even if the well-known deep learning or machine learning or time-series-analysis is exploited as it is. Therefore, we could be a better one for demand prediction.

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
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    • v.11 no.8
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    • pp.5-14
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    • 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.

Study on Queue Length Estimation using GPS Trajectory Data (GPS 데이터를 이용한 대기행렬길이 산출에 관한 연구)

  • Lee, Yong-Ju;Hwang, Jae-Seong;Lee, Choul-Ki
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.15 no.3
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    • pp.45-51
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    • 2016
  • Existing real-time signal control system was brought up typical problems which are supersaturated condition, point detection system and loop detection system. For that reason, the next generation signal control system of advanced form is required. Following thesis aimed at calculating queue length for the next generation signal control system to utilize basic parameter of signal control in crossing queue instead of the volume of real-time through traffic. Overflow saturated condition which was appeared as limit of existing system was focused to set-up range. Real-time location information of individual vehicle which is collected by GPS data. It converted into the coordinate to apply shock wave model with an linear equation that is extracted by regression model applied by a least square. Through the calculated queue length and link length by contrast, If queue length exceed the link, queue of downstream intersection is included as queue length that upstream queue vehicle is judeged as affecting downstream intersection. In result of operating correlation analysis among link travel time to judge confidence of extracted queue length, Both of links were shown over 0.9 values. It is appeared that both of links are highly correlated. Following research is significant using real-time data to calculate queue length and contributing to signal control system.

A Study on the Economical Analysis Model for Asphalt Pavementin Congestion Area of Metropolitan (대도시 혼잡구간의 아스팔트 포장에 대한 경제성 분석 모델 연구)

  • Jo, Byung Wan;Tae, Ghi Ho;Kim, Do Keun
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.5D
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    • pp.771-781
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    • 2006
  • This Study is about the development of LCC Analysis Model and Evaluation of VE. It was carried out to help the person's intention decision about choosing the pavement construction method that can deal with 'Pavement Life Factor' like Area Character and Traffic Volume efficiently, by considering the total life cycle cost of pavement life cycle happens according to the numbers of public use year. For this, we developed the new LCC Analysis Model by using the Data of Seoul city the representative city in Korea, and carried out VE Evaluation that reflects the opinions of specialists. This Analysis Model consists of cost items that affects directly the choice of pavement construction, except for the common cost items of the various pavement construction. And we investigated the propriety by applying our model to the example line that are used for the public at present. About the base data of cost items that are used for our analysis, we enhanced our model's confidence by using the statistics data of Seoul and the standard data of unit cost calculation.

Time series property of the 30th Design Hourly Factors in National Highways (일반국도 30번째 설계시간계수의 시계열적인 특성 분석에 관한 연구)

  • Oh, Ju-Sam;Im, Sung-Man
    • International Journal of Highway Engineering
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    • v.9 no.4
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    • pp.1-9
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    • 2007
  • To decide the number of road lane is very important and related to the 30th design hourly factor in the design of transportation facilities. But, as the quantitative division of road types is difficult, most planner and designer for deciding the 30th design hourly factors have used the fixed values in our country. In this study, we have analyzed the time series property of the design hourly factors in national highways and developed the model capable of estimating the 30th design hourly factors using real data. The presented model is a simple regression model(DHV = K*AADT), which is applied to the division of road lanes(2 or 4 lanes) and the level of AADT(3 levels). As a results, the simple regression model have better performance than the existing method with respect to MAPE and $R^2$. Also, the variations of the 30th design hourly factors are small. The more traffic volume increase, the more the factors decrease. But, the limitation of this study is to use the exiting method estimating the values of the factors, it is subject to study hereafter.

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A Study on the Safety-Maximizing Design of Exclusive Bus Lanes (안전성 제고를 위한 버스전용차로 디자인 연구)

  • Yang, Chul-Su
    • Journal of Korean Society of Transportation
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    • v.30 no.4
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    • pp.21-32
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    • 2012
  • Exclusive bus lane (EBL) is typically located in the roadway median, and is accessed by weaving across the GPLs(general purpose lanes) before entering from the left lane of the GPLs. To maximize the potential for successful EBL operations, a critical design issue that requires special attention is the length of bus weaving section before entering EBL. The process of developing guidelines for the length of bus weaving section can be supported by a sensitivity analysis of performance measure (safety) with respect to the bus weaving distance. However, field data are difficult to obtain due to inherent complexity in creating performance measure (safety) samples under various interesting flows and bus weaving distance that are keys to research success. In this paper, VISSIM simulation is applied to simulate the operation of roadway weaving areas with EBL, and based on vehicle trajectory data from microscopic traffic simulation models, the Surrogate Safety Assessment Model (SSAM) computes the number of surrogate conflicts (or degree of safety) with respect to the bus weaving distance. Then, a multiple linear regression (MLR) model using safety data (number of surrogate conflicts) is developed. Finally, guidelines for bus weaving distance are established based on the developed MLR. Developed guidelines explicitly indicate that a longer bus weaving distance is required to maintain desired safety as weaving volume increases.

Validation and Calibration of TUNVEN Model (TUNVEN 모형의 검증 및 보정)

  • Cheong, Jang-Pyo;Yoon, Sam-Seok;Yi, Seung-Muk
    • Journal of Korean Society of Environmental Engineers
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    • v.22 no.4
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    • pp.785-796
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    • 2000
  • In this study, the possibility of application of TUNVEN model was investigated through the validation and calibration processes. In order to validate and calibrate the TUNVEN model developed in USA to obtain prediction of the quasi-steady state longitudinal air velocities and the pollutants concentrations by solving the coupled one-dimensional steady state tunnel aerodynamic and advection equations. The major input parameters such as the concentration data for CO and $NO_x$, meteorological data and traffic volume in Hawngryung tunnel were measured. Prior to preparing the input parameters, the sensitivity analysis was conducted to identify the input parameters which need to be most accurately estimated in TUNVEN program. In order to establish the relationships between the model values and the measured values, the linear regression analysis was applied. In linear regression analysis, the model values were taken as independent parameter(X) and the measured values were taken as dependent parameter(Y) for four cases of data sef. From the results of linear regression analysis, the correlation coefficient(r) for four cases were calculated more than 0.91 and the values of slope and interception were analyzed as 0.5~2.2 and 0.01~2.3 respectively. From the above results, we concluded that the suitability of TUNVEN model was identified in prediction the longitudinal pollutant concentrations in tunnel.

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The Statistical Correlation Between Continuous Driving Time and Drowsy Accidents (연속주행시간과 졸음사고간 통계적 상관관계 분석)

  • KIM, Ducknyung;KIM, Sujin;CHOI, Jaeheon;CHO, Jongseok
    • Journal of Korean Society of Transportation
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    • v.35 no.5
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    • pp.423-433
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    • 2017
  • During recent 5 years, it was recorded that 20% of total accident frequency and 30% of total number of death have been occurred due to drowsy driving. Drowsy driving accident is result from the loss of driving ability due to driver's accumulated fatigue. Continuous driving time can be measured as a surrogate variable to quantify the level of fatigue. The main purpose of this research is to investigate statistical correlation between the proportion of continuous driving vehicle (more than 2 hours) and the number of drowsy accidents. To carry this out, continuous driving time was measured using GPS route-guidance trajectory data. Also, accident frequency, traffic volume and segment length were collected to estimate safety performance function (SPF) for Jungbunearuk expressway in Korea. Through various types of estimated SPFs, statistical correlation was analyzed based on estimated statistical indices. This research can provide theoretical background for enforcement to regulate commercial vehicle driver's continuous driving time. In addition, throughout the trajectory data expansion, it is expected that strategy for anti-drowsy driving facilities installation can be established based on the suggested methodology.