• 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.

• 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.

• International Journal of Highway Engineering
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• v.14 no.1
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• pp.85-94
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• 2012

The term "incident duration time" is defined as the time from the occurrence of incident to the completion of the handling process. Reductions in incident durations minimize damages by traffic accidents. This study aims to develop models to identify factors that influence incident duration by investigating traffic accidents on highways. For this purpose, four models were established including an integrated model (Model 1) incorporating all accident data and detailed models (Model 2, 3 and 4) analyzing accidents by location such as basic section, bridges and tunnels. The result suggested that the location of incident influences incident duration and the time of arrival of accident treatment vehicles is the most sensitive factor. Also, significant implications were identified with regard to vehicle to vehicle accidents and accidents by trucks, in night or in weekends. It is expected that the result of this study can be used as important information to develop future policies to manage traffic accidents.

• 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.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.3
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• pp.253-262
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• 2016

Recently, UWAC (underwater acoustic communication) has been studied by many scholars and researchers. DS-CDMA, OFDM (orthogonal-frequency division multiplexing), and MIMO (multi-input multi-output), modulation and error correction, and others techniques that can transmit high-speed data are used in UWAC. In this paper, we first briefly present the theoretical background of estimating the arrival time of the first non-background segment in both signals and calculate the temporal difference. We also present the initial experimental result of estimating the arrival time.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.833-839
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• 2019

Bus Information System (BIS) collects information related to the operation of buses and provides information to users through predictive algorithms. Method of predicting through recent information in same section reflects the traffic situation of the section, but cannot reflect the characteristics of the target line. The method of predicting the historical data at the same time zone is limited in forecasting peak time with high volatility of traffic flow. Therefore, we developed a pattern recognition bus arrival time prediction algorithm which could be overcome previous limitation. This method recognize the traffic pattern of target flow and select the most similar past traffic pattern. The results of this study were compared with the BIS arrival forecast information history of Seoul. RMSE of travel time between estimated and observed was approximately 35 seconds (40 seconds in BIS) at the off-peak time and 40 seconds (60 seconds in BIS) at the peak time. This means that there is data that can represent the current traffic situation in other time zones except for the same past time zone.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12A
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• pp.1910-1916
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• 1999

This paper suggested to solve ATM switch performance and service rate which was input buffer managed scheme in ATM network with burst traffic characteristics, For this purpose, ATM multiplexer is prepared before sending for handling burst random input traffic to multiplex and then sort based on cell inter-arrival time and cell processing due time which had been marked after that. The server looks for cell header with the most shortest due time and sends it, thus it is satisfied that real time traffic for instance CBR and rt-VBR was guaranteed cell processing time to send fast than non real time traffic. For analysis of ATM switch performance with cell processing due time and priority, each output port has divided into four different virtual buffer and each buffer has assigned different cell inter-arrival time and processing due time according to ATM Forum for example CBT/rt-VBR, nrt-VBR, ABR and UBR and showed it’s optimal service parameters then analyzed service rate behaviors according to each traffic characteristics.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.6
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• pp.1-12
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• 2016

In this paper, we consider a general discrete-time queueing system with D-BMAP(discrete-time batch Markovian arrival process) and D-policy. An idle single server becomes busy when the total service times of waiting customer group exceeds the predetermined workload threshold D. Once the server starts busy period, the server provides service until there is no customer in the system. The steady-state workload distribution is derived in the form of generating function. Mean workload is derived as a performance measure. Simulation is also performed for the purpose of verification and a simple numerical example is shown.