• Journal of Advanced Marine Engineering and Technology
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• v.41 no.1
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• pp.111-117
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• 2017

The arrival time of rescue ships is very important in the event of distress. This paper presents the development of experimental data to calculate the arrival time of rescue ships. The ship's traffic probability distribution was used. Mokpo Port was selected as the area of study, and AIS data for a 1 year period were used. For the ship's traffic probability distribution, a gateline was established. The lateral range distribution was calculated and fitted to the normal distribution and two Gaussian mixture distributions (GMD2), and each parameter was extracted. After the locations of ${\mu}$, ${\mu}{\pm}1{\sigma}$ of the normal distribution and ${\mu}_1$ of the two Gaussian mixture distribution(GMD2) were set as waypoints, the location and probability were determined. A scenario was established in relation to each type of parameter. Thus, the arrival time can be calculated.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.86-89
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• 2018

This paper introduces a ZigBee network-based four-lane lap time measurement system that can be set up for short-distance races. The instructions "Ready-Set-Go" can be announced at the entry point node when the start button is pushed, and foot switches installed at the exit point node can be stepped on by the runner for lap time measurement of the race. The start and exit point nodes are connected to a ZigBee network to communicate time synchronization packets. The exit point node maintains synchronized local time within 10 ms at most. The system does not need expensive measurement equipment and provides lap time recording in a more convenient manner than conventional lap time measurement methods.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.3
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• pp.1-10
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• 2009

Bus delay time is occurred as the result of traffic condition and important factor to predict bus arrival time. In this paper, transition probability matrixes between bus stops are made by using Markov Chain and it is predicted bus delay time with them. As the results of study, it is confirmed a possibility of adapting the assumption which it has same bus transition probability between stops through paired-samples T-test and overcame the limitation of exiting studies in case there is no scheduled bus arrival time for each stops with using bus interval time. Therefore it will be possible to predict bus arrival time with Markov Chain.

• Journal of Korean Society of Transportation
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• v.20 no.1
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• pp.7-18
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• 2002

To activate public transportation service, Bucheon City built Bus Information System based on Beacon type, and operates it for no.22 line. This research analyzes an effect of BIS operations, and mainly it analyzes far reliability evaluation of bus arrival time information and passenger satisfaction about BIS. As results of reliability evaluation of arrival time information service, it is proven to be practically inappropriate to use as arrival time data because it is not only travel time between each bus stop but also previous travel time history data. In order to improve this matter, neural network model was evaluated as the most outstanding one as result of experiment in applying current arrival time Prediction model. This research cannot help limiting for evaluation of operation effect in Bucheon City because there is no Bus Information System based on GPS type in Korea. For the future ITS model city, in the case of building ITS model city based on GPS type, it is possible to compare two systems relatively. In addition to that, fur the consideration of reliability of bus arrival time information, it is required to develop Predictable model and research factors that affect to bus operation.

• 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.51-59
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• 2005

To improve the quality of bus service, providing bus ravel time information to passenger through station screen. Generally, bus travel time information predict by using previous bus data such as neural network, Kalman filtering, and moving average algorithms. However, when they got a difficulty about bus travel time information because of the missing previous bus data, they use pattern data. Generally, nevertheless the difference of range is big. Hence in this research to calculate the bus travel time information when the bus information is missed, use queue detector's data which set up in link. The application of several factors which influence in bus link travel time, we used CORSIM Version 5.1 simulation package.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.1110-1111
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• 2023

본 논문은 해외 배송 화물에 대하여 실시간 위치와 정확한 도착 예정 시간을 제공하기 위하여 유가와 기상 정보 등 다양한 변수가 선박 항로에 미치는 영향을 분석한다. 기존의 ETA 예측 방법은 GPS 정보와 수기 데이터를 기반으로 하여 낮은 정확도를 보였으나, 극복하기 위한 방안으로 기상 상황 혹은 세계 유가 변동 변수까지 고려하여 인공지능 모델을 구축하였다. 선박의 도착 예측 시간 정확도 향상과 불확실성 해소를 주된 목표로 하며 이를 토대로 육·해상 통합 서비스를 개발하고자 한다. 이러한 예측 정보는 선사가 운영을 최적화하고 비용을 절감하는 데 도움을 주며, 소비자들은 신뢰할 수 있는 정보를 통해 불편과 손실을 최소화할 수 있을 것으로 보인다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.7B
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• pp.1289-1295
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• 1999

본 논문에서는 스위치의 운용 알고리즘에 따라 시뮬레이션 프로그램을 이용하여 입/출력 버퍼의 셀 손실율을 측정하였다. 그 결과 셀 손실에 영향을 주는 요소로서, 셀 도착 간격 시간(k(a))과 SPEEDUP FACTOR(SF) en 가지 요소에 따라 셀손실을 평가할 수 있음을 알 수 있었다. 셀 도착 간격 시간 혹은 주기성은 비트가 셀로 모이는데 걸리는 시간을 의미하며 스위치 속도 SF는 임의의 한 슬롯내에서 한 입력단에서 출력단으로 서비스 가능한 셀의 수를 나타내고 있다. 시뮬레이션의 결과에서 보면 입력 버퍼에서는 주지성에 따라, 출력 버퍼에서는 SF의 크기에 따라 셀손실율이 커진다는 사실을 알 수 있었다. 따라서 보다 정확한 고속 스위칭 향상을 위해서는 입/출력 버퍼의 크기 결정이 중요하다. 본 논문의 시뮬레이션 결과에서는 입력 버퍼가 100x셀 일 때 출력 버퍼가 40x셀 정도의 크기가 적합하다는 것을 얻어내었다. 물론 입/출력 버퍼를 크게 한다면 셀 손실이 작아지지만, 하드웨어를 구성하는데 문제점이 발생될 것이기 때문이다. 그리고 본 논문 결과치중 셀 도착 분포 상황은 변동계수 모델링 성정에 따라 SF가 처리하는 서비스의 셀 도착 분포에 의 \ulcorner달라지지만, 변동계수가 전혀 없는 이상적인 경우(CV=1)를 제외한 경우의 SF값을 만족한다고 하겠다. 끝으로 입/출력 버퍼를 가진 스위치 구조는 단지 출력 버퍼를 갖는 스위치 보다 지연이 크지만, VLSI의 발달로 셀의 처리 속도가 증가하므로 더 많은 장점을 갖게 될 것이다.

• Journal of Korean Society of Transportation
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• v.27 no.1
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• pp.73-81
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• 2009

While various factors in passenger and freight demand analysis affect on destination choice, a key factor, in general. is an attractiveness measure by size variable (e.g., population. employment etc) in destination zone. In order to measure the attractiveness, some empirical studies suggested that disaggregate gravity model are more suitable than aggregate gravity model. This study proposes that truck travelers trip diary data among Korean commodity flow data could be used to estimate the behaviors of incorporating trip departure time, activity duration and attractiveness in destination. As a result, the main findings of size and distance variables coincide with the conventional gravity model having a positive effect of population variable and a negative effect of distance variable. Due to disaggregate gravity modeling, the unique findings of this study reports that small trucks are more likely to choose short distance and early morning, morning peak and afternoon peak departure time choice. On the other hand, large trucks are more likely to choose long distance and night time departure time choice.

• Journal of Korean Society of Transportation
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• v.19 no.4
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• pp.97-108
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• 2001

A dynamic transportation management should be applied specially in AM peak because AM peak is more critical than PM peak in traffic volume and demand. AM peak trip can be characterized by commuting and schooling. which have the high level of usage on public transportation, and constraint on arrival time. So transportation management applied in AM peak could deal with a mode choice and an arrival time constrain. Researchers were involved in the dynamic transportation assignment models for management of congested traffic network. But, there were no models which considered a mode choice and an arrival time constrain should be included in management of AM peak. So there are limits to use exist models to control and analyze AM peak traffic. In this study, it is proposed the combined dynamic transportation model, considering a mode choice and the start time selection with arrival time constrains, based on Ran and Boyce's model. The proposed model is verified the compatibility by applying to the newly designed time space expanded network. The result shows that proposed model consistent with dynamic user optimal travel pattern. From this we certificate the applicability of the proposed model to control and analyze AM peak traffic.

• Journal of the Korean earth science society
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• v.39 no.6
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• pp.593-599
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• 2018

The onset times of P- and S-waves are important information to have reliable earthquake locations, 1D or 3D subsurface velocity structures, and other related studies in seismology. As the number of seismic stations increases significantly in recent years, it becomes a formidable task for network operators to pick phase arrivals manually. This study used a simple method to estimate additional P- and S-wave arrival times for local earthquakes when a priori information (event location and time) is available using the Akaike Information Criterion (AIC). We applied the AIC program to the earthquake data recorded at the seismic station located in Gyeongsan (DAG2). The comparisons of automatically estimated phase arrival times with manually picked onset times showed that 95.1% and 93.7% of P-wave and S-wave arrival time estimations, respectively, are less than 0.1 second difference. The higher percentage of agreement presented the method which can be successfully applied to large data sets recorded by high-density seismic arrays.