• 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.

• Journal of Korean Society of Transportation
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• v.29 no.1
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• pp.17-27
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• 2011

This paper investigates some critical errors influencing travel demand estimation in Korea Transportation Data Base (KTDB), and through this investigation reasonable traffic analysis zone (TAZ) size and internal trips ratio are analyzed. With varying zone size, the accuracy of travel demand estimation is studied and appropriate level of zone size in KTDB is also presented. For this purpose zonal structure consisting of location of zone centroid, number of centroid connecters has been constructed by social economic index, and then some descriptive statistical analyses such as F-test, coefficient of correlation are performed. From the results, this paper shows that the optimum levels of zone system were various according to the order and capacity of roads, and also shows that the smaller TAZ, the less error in this research. In conclusion, in order to improve accuracy of traffic demand estimation it is necessary to make zone size smaller.

• International Journal of Highway Engineering
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• v.14 no.5
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• pp.179-188
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• 2012

PURPOSES: The aim of this study is to analyze overloading control effectiveness of enforcing overweighted vehicles using HS-WIM (High-Speed Weigh-in-Motion) at main lane of expressway. METHODS: To analyze the weight distribution statistically, HS-WIM system should has an appropriate weighing accuracy. Thus, the weighing accuracy of the two HS-WIM systems was estimated by applying European specifications and ASTM (American Standards for Testing and Materials) for WIM in this study. Based on the results of accuracy test, overweight enforcement system has been operated at main lanes of two expressway routes in order to provide weight informations of overweighted vehicle in real time for enforcement squad. To evaluate the overloading control effectiveness with enforcement, traffic volume and axle loads of trucks for two months at the right after beginning of the enforcement were compared with data set for same periods before the enforcement. RESULTS: As the results of weighing accuracy test, both WIM systems were accepted to the most precise type that can be useful to applicate not only statistical purpose but enforcing on overweight vehicles directly. After the enforcement, the rate of overweighted trucks that weighed over enforcement limits had been decreased by 27% compared with the rate before the enforcement. Especially, the rate of overweighted trucks that weighed over 48 tons had been decreased by 91%. On the other hand, in counterpoint to decrease of the overweighted vehicle, the rate of trucks that weighed under enforcement limits had been increased by 7%. CONCLUSIONS: From the results, it is quite clear that overloading has been controlled since the beginning of the enforcement.

• Journal of Korean Society of Transportation
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• v.28 no.3
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• pp.75-84
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• 2010

South Korea is seeking for a solution to the problems of traffic congestion and environment: the increase of bicycle use. However many people feel that using a bicycle is inconvenient. Therefore, we developed bicycle level of service model from the user's perspective so that the existing bicycle roads can be evaluated and improved. The purpose of this paper is to develop a bicycle level of service (LOS) model by considering user's satisfaction and multiple factors that affect bicycle LOS. Bicycle LOS criteria is estimated by applying an ordered probit model, which is suitable for research relating to choice. In addition, we determine the bicycle LOS using three-level(A-C) LOS structure from the user position considering the satisfaction level that people can distinguish clearly. The results show that the bicycle LOS is largely determined by the bicycle road width. Other factors are involved as well, including bicycle road type, the number of access and egress point on the bicycle road corridor, pedestrian volume, and frequency of meetings.

• Journal of Korean Society of Transportation
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• v.18 no.4
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• pp.75-85
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• 2000

The Purpose of this study is to analyze wether the composition of training sample have a relation with the Predictive ability and the learning results of ANNs(Artificial Neural Networks) fur predicting one cycle ahead of the queue length(veh.) in a signalized intersection. In this study, ANNs\` training sample is classified into the assumption of two cases. The first is to utilize time-series(Per cycle) data of queue length which would be detected by one detector (loop or video) The second is to use time-space correlated data(such as: a upstream feed-in flow, a link travel time, a approach maximum stationary queue length, a departure volume) which would be detected by a integrative vehicle detection systems (loop detector, video detector, RFIDs) which would be installed between the upstream node(intersection) and downstream node. The major findings from this paper is In Daechi Intersection(GangNamGu, Seoul), in the case of ANNs\` training sample constructed by time-space correlated data between the upstream node(intersection) and downstream node, the pattern recognition ability of an interrupted traffic flow is better.

• Structural Engineering and Mechanics
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• v.76 no.1
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• pp.1-15
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• 2020

The aim of this paper is to simply present live load factor calculation methodology formulation with the addition of a simple new future load projection procedure to previously proposed two methods. For this purpose, Oregon Weigh-in-Motion (WIM) data were used to calculate live load factors by using WIM data. These factors were calculated with two different approaches and by presenting new simple modifications in these methods. A very simple future load projection method is presented in this paper. Using four different WIM sites with different average daily truck traffic (ADTT) volume, and all year data, live load factors were obtained. The live load factors, were proposed as a function of ADTT. ADTT values of these sites correspond to three different levels which are approximately ADTT= 5,000, ADTT = 1,500 and ADTT ≤ 500 cases. WIM data for a full year were used from each site in the calibration procedure. Load effects were projected into the future for the different span lengths considering five-year evaluation period and seventy-five-years design life. The live load factor for ADTT=5,000, AASHTO HS20 loading case and five-year evaluation period was obtained as 1.8. In the second approach, the methodology established in the Manual for Bridge Evaluation (MBE) was used to calibrate the live load factors. It was obtained that the calculated live load factors were smaller than those in the MBE specifications, and smaller than those used in the initial calibration which did not convert to the gross vehicle weight (GVW) into truck type 3S2 defined by AASHTO equivalents.

• Journal of Navigation and Port Research
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• v.33 no.7
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• pp.491-500
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• 2009

In order to attract more transshipment cargoes, Busan Port Authority (BPA) has, since 2003, adopted the volume incentive policy by which more than US$ 10 million annually have been paid back to shipping lines that were called at the port. However, having been a transshipment port for the Northeast region of China, the port of Busan has come under threat from bold Chinese port development projects, notably Shanghai, as northern Chinese regionnl ports place more emphasis on building facilities capable of handling growing trade volumes. Undoubtedly this would lead to a decline in transshipment container traffic moved via Busan. The purpose of this paper is to identify some core factors that have been affecting the increase of transshipment cargoes of Busan and further to recommend BPA an improved incentive scheme with which more T/S cargoes can be attracted into the port of Busan To clarity the reason why T/S cargoes have increased in the port of Busan, several steps are made as follows: The first step is to make a quantitative model for explaining the development of T/S cargoes during the last decade. The second step is to define the dependent and the independent variables for multiple regressions after testing variable significance. For this, data collection and the accuracy of validation have been done by the direct interview with the experienced staffs in shipping companies of both domestic and foreign country. After validating the model with collected data, the final step is to find variables which are explaining the model mostly. In conclusion, 2 variables were clearly identified as core factors that explain well the development of T/S cargoes in the port of Busan: 'Mohring effect' and total cost. It is strongly recommended, by an empirical study, that an incentive scheme be changed to a way which more feeder vessels rather than mother vessels can reduce their direct costs to call in the port of Busan.

• Journal of Korean Society of Transportation
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• v.23 no.5 s.83
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• pp.7-14
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• 2005

Traffic congestion causes enormous social costs as well as loss of travel time and waste of energy. Though the Seoul metropolitan government implemented various forms of transportation policies such as urban road pricing and public transportation reform, traffic volume which across the Seoul metropolitan borders have greatly increased because of housing land development in suburban area. The purpose of this study is to estimate individual's willingness-to-pay(WTP) for extensive implementation of congestion pricing through policy-mix with bus rapid transit(BRT) system. So the field survey interviews carried out. The empirical analysis was done with priority given to the following two topics; derivation of individual WTP and prior evaluation of policy effect from the equity aspect. To estimate individual WTP, we adopted contingent valuation method (CVM). The former is to estimate individual WTP for respondent's maintaining his/her transit pattern when he/she is faced with congestion pricing by using compensating variation(CV) concept. And, the latter aims at evaluating policy effect from the equity aspect by calculating the Proportion of WTP to average income using WTP in income bracket for policy scenarios.

• Journal of Trauma and Injury
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• v.35 no.2
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• pp.108-114
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• 2022

Purpose: The coronavirus disease 2019 (COVID-19) pandemic has had major effects worldwide, including sudden and forceful setbacks to the healthcare system. The COVID-19 pandemic has also led to changes in the plastic and reconstructive management of emergency cases, including those due to road traffic accidents. This study analyzed changes in patterns of plastic surgery emergencies and modifications in consultation policies to minimize the exposure of healthcare workers. Methods: Data on plastic surgery emergency calls received from the trauma and emergency department were collected for a period of 2 months before and during lockdown. The data were then analyzed with respect to the cause, mechanism, and site of the injury, as well as other variables. Results: During lockdown, there was a 40.4% overall decrease in the plastic surgery emergency case volume (168 vs. 100). The average daily number of consultations before lockdown was 2.8 as compared to 1.6 during lockdown. Road traffic accidents remained the most common mechanism of injury in both groups (45.8% vs. 39.0%) but decreased in number during the lockdown (77 vs. 39). Household accidents, including burns, were the second most common cause of injury in both phases (7.7% vs. 20.0%), but their proportion increased significantly from 7.7.% to 20.0% in the lockdown phase (P=0.003). The percentage of minor procedures done in the emergency department increased from 53.5% to 72.0% during lockdown (P=0.002). Procedures in the operating room decreased by 73.1% during lockdown (67 vs. 18, P=0.001). Conclusions: The COVID-19 pandemic and lockdown orders in India greatly influenced trends in traumatic emergencies as observed by the plastic surgery team at our tertiary care center. Amidst all the chaos and limitations of the pandemic period, providing safe and prompt care to the patients presenting to the emergency room was our foremost priority.

• Journal of Navigation and Port Research
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• v.44 no.5
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• pp.382-391
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• 2020

In line with the trend of global transport volume which has increased rapidly over the years, internal transportation in seaports is always conducted with high frequency. Thus, there is always much potential for traffic jams as well as high transportation costs and emissions. Many efforts have been initiated to streamline the inter-terminal container transport (ITT) through the development of automated vehicles and equipment as well as using private transport facilities to overcome these limitations. The purpose of this paper to develop a framework to design, analyze, and validate the efficiency of a new ITT system in a port area based on the monorail network and automatic vehicles. First, the number of shuttles and loaders was determined depending on the transport demand scenario. Next, a simulation model was applied to evaluate the system performance as well as gain more insight into the working process of the ITT system. Finally, by setting goals for the performance indicators, the results showed that the system was highly efficient with 100% of the containers delivered to their destination on time. Besides, a series of other performance tracking was provided to provide insight into the system's capabilities.