• Title/Summary/Keyword: Traffic Volume Distribution

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Time series and deep learning prediction study Using container Throughput at Busan Port (부산항 컨테이너 물동량을 이용한 시계열 및 딥러닝 예측연구)

  • Seung-Pil Lee;Hwan-Seong Kim
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.06a
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    • pp.391-393
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    • 2022
  • In recent years, technologies forecasting demand based on deep learning and big data have accelerated the smartification of the field of e-commerce, logistics and distribution areas. In particular, ports, which are the center of global transportation networks and modern intelligent logistics, are rapidly responding to changes in the global economy and port environment caused by the 4th industrial revolution. Port traffic forecasting will have an important impact in various fields such as new port construction, port expansion, and terminal operation. Therefore, the purpose of this study is to compare the time series analysis and deep learning analysis, which are often used for port traffic prediction, and to derive a prediction model suitable for the future container prediction of Busan Port. In addition, external variables related to trade volume changes were selected as correlations and applied to the multivariate deep learning prediction model. As a result, it was found that the LSTM error was low in the single-variable prediction model using only Busan Port container freight volume, and the LSTM error was also low in the multivariate prediction model using external variables.

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An Analysis of Baggage Demand for Designing Baggage Handling System(BHS) (A Case Study of Incheon International Airport) (수하물처리시설 설계를 위한 수하물 수요분석(인천국제공항의 예))

  • Bae, Byung-Uk;Lee, Hong-Cheol
    • Journal of Korean Society of Transportation
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    • v.22 no.1 s.72
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    • pp.19-30
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    • 2004
  • Once baggage demand of passengers is forecast, BHS requirements must be analyzed, i.e., the number of originating/transferring/terminating bags to be handled, the number of conveyor lines to be installed, the number of containers for baggage make-up, the number of claim devices for baggage claim, and so on. Therefore, the determination of the baggage traffic volume is one of the most important analysis components for the airport design. Accordingly, this research proposes time-based distribution table models in order to accurately estimate BHS requirements to obtain design criteria in airport design phase. As the BHS requirements are ascertained, related requirements of the facilities can be determined by applying actual specifications of devices, i.e., throughput. This research found that the proposed mathematical model gives a good reflection of IIA (Incheon International Airport)'s operational condition. That means the model provides apparent reliability and feasibility. Furthermore, the specifications of devices are the newest figures. This fact supports that the research provides more effcient and reliable results.

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.

On the Analysis of Physical Distribution System in Mokpo Port (목포항 물류시스템의 분석에 관한 연구)

  • Lee, C. Y.;Nam, M. U.
    • Journal of Korean Port Research
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    • v.10 no.1
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    • pp.1-14
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    • 1996
  • Rapid change in the technological environment of marine transportation and the development of the ocean shipping industry have fostered a revolution in the port system. This in turn has caused major changes in the function and use of port in Korea. Aside from this, Mokpo Port, however continues to decline, because the existing port facilities and related subsystem are already obsolete with no chance of regaining operational effectiveness and treatment for proper implementation. Although a few studies have been done on the Mokpo Port, has not been found, any reseach for the analytical approach to the transportation system of it. This paper aims to make an extensive analysis of the physical distribution system in Mokpo Port focusing on the coordination of subsystems such as navigational aids system. The base of introduced simulation tool here is the queueing theory. The overall findings are as follows: 1. Among those vessels called at Mokpo Port in 1994, 556 ships(2,736,669 G/T) are oceangoing while 8155 ships(2,587,217 G/T) are domestic. The average size of oceangoing vessels is 4,922,1 G/T, and the domestic is 317,8 G/T. The average arrival interval and service time of the domestic vessels are 6.0 hours and 24.1 hours respectively marking the berth occupation rate over 100%. Those for oceangoing vessels are 34.5 hours, 120.0 hours and 37.2%. In order to maintainin the berth occupation rate to 70% the capacity considering the 1994 of domestic piers must be extended to 145% and oceangoing vessels must be increased to 165%. 2. The capacity of approaching channel is enough to handle the total traffic volume of 3. Tugs are sufficiently being provided to handle all ships requiring their services 4. The capacity of storage and inland transportation systems are sufficient to handle the throughput and the yard stroage utilization rate of No.1 - No.5 is 4.5% and No.6 is 30% of 1993's. 5. The utilization rate of LLC(Level Looping Crane) and PNT(PNeumaTic) are 2.7% and 18.8%, respectively.

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Estimation of Road Capacity at Two-Lane Freeway Work Zones Considering the Rate of Heavy Vehicles (중차량 비에 따른 편도 2차로 고속도로 공사구간 도로 용량 추정)

  • Ko, Eunjeong;Kim, Hyungjoo;Park, Shin Hyoung;Jang, Kitae
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.2
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    • pp.48-61
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    • 2020
  • The objective of this study is to estimate traffic capacity based on the heavy-vehicle ratio in a two-lane freeway work zone where one lane is blocked by construction. For this, closed circuit television (CCTV) video data of the freeway work zone was collected, and the congestion at an upstream point was observed. The traffic volume at a downstream point was analyzed after a bottleneck was created by the blockage due to the upstream congestion. A distribution model was estimated using observed-time headway, and the road capacity was analyzed using a goodness-of-fit test. Through this process, the general capacity and an equation for capacity based on the heavy-vehicle ratio passing through the work zone were presented. Capacity was estimated to be 1,181~1,422 passenger cars per hour per lane (pcphpl) at Yeongdong, and 1,475~1,589pcphpl at Jungbu Naeryuk. As the ratio of heavy vehicles increased, capacity gradually decreased. These findings can contribute to the proper capacity estimation and efficient traffic operation and management for two-lane freeway work zones that block one lane due to a work zone.

Developing a Traffic Accident Prediction Model for Freeways (고속도로 본선에서의 교통사고 예측모형 개발)

  • Mun, Sung-Ra;Lee, Young-Ihn;Lee, Soo-Beom
    • Journal of Korean Society of Transportation
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    • v.30 no.2
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    • pp.101-116
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    • 2012
  • Accident prediction models have been utilized to predict accident possibilities in existing or projected freeways and to evaluate programs or policies for improving safety. In this study, a traffic accident prediction model for freeways was developed for the above purposes. When selecting variables for the model, the highest priority was on the ease of both collecting data and applying them into the model. The dependent variable was set as the number of total accidents and the number of accidents including casualties in the unit of IC(or JCT). As a result, two models were developed; the overall accident model and the casualty-related accident model. The error structure adjusted to each model was the negative binomial distribution and the Poisson distribution, respectively. Among the two models, a more appropriate model was selected by statistical estimation. Major nine national freeways were selected and five-year dada of 2003~2007 were utilized. Explanatory variables should take on either a predictable value such as traffic volumes or a fixed value with respect to geometric conditions. As a result of the Maximum Likelihood estimation, significant variables of the overall accident model were found to be the link length between ICs(or JCTs), the daily volumes(AADT), and the ratio of bus volume to the number of curved segments between ICs(or JCTs). For the casualty-related accident model, the link length between ICs(or JCTs), the daily volumes(AADT), and the ratio of bus volumes had a significant impact on the accident. The likelihood ratio test was conducted to verify the spatial and temporal transferability for estimated parameters of each model. It was found that the overall accident model could be transferred only to the road with four or more than six lanes. On the other hand, the casualty-related accident model was transferrable to every road and every time period. In conclusion, the model developed in this study was able to be extended to various applications to establish future plans and evaluate policies.

The Study of Volume Data Aggregation Method According to Lane Usage Ratio (차로이용률을 고려한 지점 교통량 자료의 집락화 방법에 관한 연구)

  • An Kwang-Hun;Baek Seung-Kirl;NamKoong Sung
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.4 no.3 s.8
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    • pp.33-43
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    • 2005
  • Traffic condition monitoring system serves as the foundation for all intelligent transportation system operation. Loop detectors and Video Image Processing are the most widely common technology approach to condition monitoring in korea Highways. Lane Usage is defined as the proportion of total link volume served by each lane. In this research, the lane Usage(LU) of two lane link for one day. Interval is 56% : 44%. The LU of three lane link is 39% : 37% : 24%. The LU of four lane link is 25% : 29% : 26% : 21%. These analysis reveal that each lane distributions of link are not same. This research investigates the general concept of lane usage by using collected loop detector data and the investigated that lane distribution is different by traffic lane and lane usage is consistent by time of day.

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Design of Client-Server Model For Effective Processing and Utilization of Bigdata (빅데이터의 효과적인 처리 및 활용을 위한 클라이언트-서버 모델 설계)

  • Park, Dae Seo;Kim, Hwa Jong
    • Journal of Intelligence and Information Systems
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    • v.22 no.4
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    • pp.109-122
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    • 2016
  • Recently, big data analysis has developed into a field of interest to individuals and non-experts as well as companies and professionals. Accordingly, it is utilized for marketing and social problem solving by analyzing the data currently opened or collected directly. In Korea, various companies and individuals are challenging big data analysis, but it is difficult from the initial stage of analysis due to limitation of big data disclosure and collection difficulties. Nowadays, the system improvement for big data activation and big data disclosure services are variously carried out in Korea and abroad, and services for opening public data such as domestic government 3.0 (data.go.kr) are mainly implemented. In addition to the efforts made by the government, services that share data held by corporations or individuals are running, but it is difficult to find useful data because of the lack of shared data. In addition, big data traffic problems can occur because it is necessary to download and examine the entire data in order to grasp the attributes and simple information about the shared data. Therefore, We need for a new system for big data processing and utilization. First, big data pre-analysis technology is needed as a way to solve big data sharing problem. Pre-analysis is a concept proposed in this paper in order to solve the problem of sharing big data, and it means to provide users with the results generated by pre-analyzing the data in advance. Through preliminary analysis, it is possible to improve the usability of big data by providing information that can grasp the properties and characteristics of big data when the data user searches for big data. In addition, by sharing the summary data or sample data generated through the pre-analysis, it is possible to solve the security problem that may occur when the original data is disclosed, thereby enabling the big data sharing between the data provider and the data user. Second, it is necessary to quickly generate appropriate preprocessing results according to the level of disclosure or network status of raw data and to provide the results to users through big data distribution processing using spark. Third, in order to solve the problem of big traffic, the system monitors the traffic of the network in real time. When preprocessing the data requested by the user, preprocessing to a size available in the current network and transmitting it to the user is required so that no big traffic occurs. In this paper, we present various data sizes according to the level of disclosure through pre - analysis. This method is expected to show a low traffic volume when compared with the conventional method of sharing only raw data in a large number of systems. In this paper, we describe how to solve problems that occur when big data is released and used, and to help facilitate sharing and analysis. The client-server model uses SPARK for fast analysis and processing of user requests. Server Agent and a Client Agent, each of which is deployed on the Server and Client side. The Server Agent is a necessary agent for the data provider and performs preliminary analysis of big data to generate Data Descriptor with information of Sample Data, Summary Data, and Raw Data. In addition, it performs fast and efficient big data preprocessing through big data distribution processing and continuously monitors network traffic. The Client Agent is an agent placed on the data user side. It can search the big data through the Data Descriptor which is the result of the pre-analysis and can quickly search the data. The desired data can be requested from the server to download the big data according to the level of disclosure. It separates the Server Agent and the client agent when the data provider publishes the data for data to be used by the user. In particular, we focus on the Big Data Sharing, Distributed Big Data Processing, Big Traffic problem, and construct the detailed module of the client - server model and present the design method of each module. The system designed on the basis of the proposed model, the user who acquires the data analyzes the data in the desired direction or preprocesses the new data. By analyzing the newly processed data through the server agent, the data user changes its role as the data provider. The data provider can also obtain useful statistical information from the Data Descriptor of the data it discloses and become a data user to perform new analysis using the sample data. In this way, raw data is processed and processed big data is utilized by the user, thereby forming a natural shared environment. The role of data provider and data user is not distinguished, and provides an ideal shared service that enables everyone to be a provider and a user. The client-server model solves the problem of sharing big data and provides a free sharing environment to securely big data disclosure and provides an ideal shared service to easily find big data.

Water Quality and Particle Size Distributions of Road Runoff in Storm Event (강우시 도로유출수 수질특성 및 입경분포)

  • Lee, Jun-Ho;Cho, Yong-Jin;Bang, Ki-Woong
    • Journal of Korean Society of Environmental Engineers
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    • v.27 no.7
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    • pp.777-784
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    • 2005
  • The first flush phenomenon is defined as the initial period of road runoff during which the concentration of pollutants was significantly high. Road runoff contains significant loads of micro-particles, heavy metals and organic constituents. There were two major objectives of this study. The first objective was to characterize the road runoff. The second objective was to measure and evaluate particle sire distribution of the road runoff, Stormwater runoff was monitored on two sites of four lane road areas along with traffic volume. A total six storm events were monitored to characterize the road runoff. The quantity of road runoff and quality constituents, including chemical oxygen demand ($COD_{Cr}$), suspended solids(SS), total Kjeldahl nitrogen (TKN), ortho-phosphorus ($PO_4-P$), total phosphorus(TP), heavy metals and particle size distribution were analyzed. The results indicate that the concentration of SS, $COD_{Cr}$, TKN and TP ranges were $45{\sim}2,396\;mg/L$, $40{\sim}931\;mg/L$, $0.1{\sim}19.6\;mg/L$, and $0.2{\sim}25.1\;mg/L$, respectively. The results of the regression analysis between SS and the others constituents shows that $COD_{Cr}$, TP, Cu, Pb were highly correlated. And the results showed that the mean range of particle size and uniformity coefficient for road runoff were $6.7{\sim}23.4{\mu}$ and $6.4{\sim}10.2$, respectively.

Viscoelastic Behaviors of Geosynthetic-Reinforced Asphalt Pavements (섬유보강 아스팔트 포장의 점탄성 거동연구)

  • In, Sik-Youn;Kim, Hyung-Bae;Ann, Sung-Sun;Suh, Young-Chan
    • International Journal of Highway Engineering
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    • v.6 no.2 s.20
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    • pp.37-45
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    • 2004
  • The asphalt concrete pavement takes various advantages of better riding quality, serviceability and easier maintenance. At the same time, it addresses a weak point of the premature failures due to rapid increasement of traffic volume, heavy vehicles and high temperature in summer. It increases the expenditure of maintenance and repair. In order to improve the performance of asphalt pavement avoiding this premature failure, the use reinforcements with geosynthetics have been considered. Geosynthetics are known as an effective reinforcement to restrain fatigue and reflective cracks in asphalt pavements. In this study, a comprehensive parametric study is conducted to capture the efficiency of geosynthetic-reinforcements using viscoelastic properties of the asphalt concrete(AC) layer. The investigated parameters were reinforcement location, AC layer thickness, temperature distribution across the AC layer and modulus of AC and base layer. As a result of observations, that reinforced asphalt concrete could be used effectively for improving resistance against fatigue cracks and permanent deformation. Especially, when a geogrid was placed at the interface between the asphaltic base and the subbase, tensile stress in the horizontal direction was significantly reduced.

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