• Journal of Fisheries and Marine Sciences Education
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• v.19 no.2
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• pp.278-287
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• 2007

Since traffic congestion ratio at any given port fluctuates on the number of arriving and departing vessels, the total tonnage of freight volume being handled, and the number of berth in operation and other factors, there exists a need to numerically analyze the waterway traffic volume. However, there are no effective regulations in regards to the waterway traffic analysis prior to expansion of a port facility. The current analysis requires the traffic analysis in relation only to the width of the waterway, which clearly falls short of achieving a comprehensive evaluation study that could be used in consideration of port expansion.This study provides five scenarios to execute a comprehensive evaluation study and base for the sensitivity study by analyzing the scenarios. As a result of the sensitivity analysis, the A, B, and C scenarios varies the average arrival ratio of the berth shows 1.1, 1.19, and 1.28 times of delays respectively. Also, The D and E scenarios take place malfunctions of pier shows 1.21 and 1.53 times of delays respectively. Therefore, various strategies of harbor development and method of harbor management are needed for the flexible correspondence to the environmental changes such as the excessive increasing of the freight volume and often taking place of malfunctioning.

• Journal of the Korea Society for Simulation
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• v.10 no.3
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• pp.47-58
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• 2001

Evaluation of Freeway Congestion Management Using Mesoscopic Traffic Simulator A mesoscopic simulation study to measure the effects of trip generation caused by rampant expansion of residential area around the Kyungbu corridor has been conducted. Some alternatives, which seem to be judgememtally plausible and technically feasible to mitigate such congestion, have been carefully examined and evaluated by the simulation model called INTEGRATION. Alternatives are mostly network improvements. Banpo IC dedicated ramp construction (A1), Seocho IC TSM based weaving elimination (A2), dedicated local and express separation over Seocho-Yangjae segment (A3), Heonleung IC (A4) and Daewang If installations (A5), Pangyo IC improvement (A6), Baikhyun IC (A7) and Dongbaek IC installations (A8) along with Shingal-Pangyo segment capacity addition (A9). The most capital intensive ones are A9, A5, and A4 in that order. A1, A6, A7, and A8 are short in distance but they are also capital intensive and need some construction periods. The least capital driven alternatives are h2 and A3, the h2 is easier to do, but A3 needs traffic diversion scheme during construction. The A1, A7, and A8 have been identified cost effective in terms of speed increase and travel time saving. Along with these results, some limitations and future research agenda regarding simulation have also been presented.

• Journal of Oriental Neuropsychiatry
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• v.32 no.3
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• pp.261-273
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• 2021

The purpose of this study was to introduce effects of Chukyu pharmacopuncture and Brainspotting on knee pain, headaches, and acute stress disorder of a patient with a traffic accident. We treated a patient with Chukyu pharmacopuncture and Brainspotting. Numerical rating scale (NRS), Range of Motion (ROM), Hyperextension Position (HEP), Effusion (Eff), Patella Compression Test (PCT), Frontal Flexion Position (FFP), McMurray (MCM), Lateral Joint Line Tenderness (LJLT), Medial Joint Line Tenderness (MJLT), Anterior Drawer Test (ADT), Lachman Test, Varus/Valgus stress, Beck Anxiety Inventory (BAI), Patient Health Questionnaire-9 (PHQ-9), Pittsburgh Sleep Quality Index (PSQI), Core Seven Emotions Inventory Short Form (CSEI-S), Subjective units of disturbance scale (SUDs), and Heart rate variability (HRV) were used to evaluate the patient. After the patient was treated by Chukyu pharmacopuncture and Brainspotting, the patient showed improvement in NRS, physical examination, and psychological symptom assessment. These results indicate that Chukyu pharmacopuncture and Brainspotting are effective on knee pain, headache, and acute stress disorder after a traffic accident.

• International Journal of Control, Automation, and Systems
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• v.3 no.4
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• pp.509-523
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• 2005

We are developing a novel framework, PRIDE (PRediction In Dynamic Environments), to perform moving object prediction (MOP) for autonomous ground vehicles. The underlying concept is based upon a multi-resolutional, hierarchical approach which incorporates multiple prediction algorithms into a single, unifying framework. The lower levels of the framework utilize estimation-theoretic short-term predictions while the upper levels utilize a probabilistic prediction approach based on situation recognition with an underlying cost model. The estimation-theoretic short-term prediction is via an extended Kalman filter-based algorithm using sensor data to predict the future location of moving objects with an associated confidence measure. The proposed estimation-theoretic approach does not incorporate a priori knowledge such as road networks and traffic signage and assumes uninfluenced constant trajectory and is thus suited for short-term prediction in both on-road and off-road driving. In this article, we analyze the complementary role played by vehicle kinematic models in such short-term prediction of moving objects. In particular, the importance of vehicle process models and their effect on predicting the positions and orientations of moving objects for autonomous ground vehicle navigation are examined. We present results using field data obtained from different autonomous ground vehicles operating in outdoor environments.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.3
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• pp.157-167
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• 2011

Although vehicles become more intelligent for convenience and safety of drivers, traffic accidents are increased more and more. Especially, car-to-car single rear impacts in the urban area are increased rapidly because of driver inattention. To prevent rear impacts in the urban area, commercial automobile vendor applies the low-speed short-distance collision warning system. This paper presents low-speed short-distance collision warning algorithm for the city driving by using sensor fusion of laser sensor and ultrasonic sensor. An experiment using embedded microprocessor in the driving track was used to demonstrate the feasibility of the collision warning algorithm.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.6
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• pp.77-90
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• 2015

An increasing number of vehicles is causing various traffic problems such as chronic congestion of highways and air pollution. Local governments have been managing traffic by constructing systems such as Intelligent Transport Systems (ITS) and Advanced Traffic Management Systems (ATMS) to relieve such problems, but construction of an infrastructure-based traffic system is insufficient in resolving chronic traffic problems. A more sophisticated system with enhanced operational management capabilities added to the existing facilities is necessary at this point. As traffic patterns of the urban traffic flow is time-specific due to the different vehicle populations throughout the time of the day, a local network-wide signal operation plan that can manage such situation-specific traffic patterns is deemed to be necessary. Therefore, this study is conducted for the purpose of establishment of a plan for contextual signal control management through signal optimization at the network level after setting the Frame Signal in accordance to the traffic patterns gathered from the short-term traffic forecast data as a means to mitigate the problems with existing standardized signal operations.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.38-48
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• 2017

Link attributes, such as speed, occupancy, and flow, are essential factors for transportation planning and operation. It is, therefore, one of the most important decision-making problems in intelligent transport system (ITS) to determine the optimal location of a sensor for collecting the information on link attributes. This paper aims to develop a model to determine the optimal location of a sensor to minimize the variability of traffic information on whole networks. To achieve this, a network sensor location model (NSLM) is developed to reflect discrete characteristics of data collection. The variability indices of traffic information are calculated based on the summation of diagonal elements of the variance-covariance matrix. To assess the applicability of the developed model, speed data collected from the dedicated short range communication (DSRC) systems were used in Daegu metropolitan area. The developed model in this study contributes to the enhancement of investment efficiency and the improvement of information accuracy in intelligent transport system (ITS).

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.1
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• pp.1-16
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• 2020

With the advent of the fourth industrial revolution era, there has been a growing interest in deep learning using big data, and studies using deep learning have been actively conducted in various fields. In the transportation sector, there are many advantages to using deep learning in research as much as using deep traffic big data. In this study, a short -term travel speed prediction model using LSTM, a deep learning technique, was constructed to predict the travel speed. The LSTM model suitable for time series prediction was selected considering that the travel speed data, which is used for prediction, is time series data. In order to predict the travel speed more precisely, we constructed a model that reflects both temporal and spatial effects. The model is a short-term prediction model that predicts after one hour. For the analysis data, the 5minute travel speed collected from the Seoul Transportation Information Center was used, and the analysis section was selected as a part of Gangnam where traffic was congested.

• Journal of Convergence Society for SMB
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• v.5 no.4
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• pp.5-10
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• 2015

With the advance of ICT, understanding the condition of network and analysing network monitoring have become an important issue. On the TCP/IP network, SNMP is the typical protocol that catches the condition of network by using polling method. If polling method is implemented for a long period, to catch the change of the condition of the network is not easy. On the other hand, in case of short-term polling, even if it could catch the condition of the network in real time, responsive messages to results of the polling cause the increase of traffic and therefore burden the network. There have been studies to control the overhead of responsive messages by controlling the polling period. However, not considering the characteristics of an agent, and running randomly, they cannot decrease the overhead although they would have an instant effect. This paper suggests an efficient polling method that decreases the traffic overhead of polling and catches the condition of the network in real time. Proposed method an polling for a short period and gave weight based on the characteristics of agents to catch the network condition, and a manager decided polling differentially based on the weight so that it decreased the overhead of polling traffic.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.69-80
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• 2016

Some studies were conducted for the purpose of minimizing total clearance time for rapid evacuation from the indoor spaces when disaster occurs. Most studies took a long time to calculate the optimal evacuation route that derived minimum evacuation time. For this reason, this study proposes an evacuation route assignment algorithm that can shorten the total clearance time in a short operational time. When lots of exits are in the building, this algorithm can shorten the total clearance time by assigning the appropriate pedestrian traffic volume to each exit and balances each exit-load. The graph theory and greedy algorithm were utilized to assign pedestrian traffic volume to each exit in this study. To verify this algorithm, study used a cellular automata-based evacuation simulator and experimented various occupants distribution in a building structure. As a result, the total clearance time is reduced by using this algorithm, compared to the case of evacuating occupants to the exit within shortest distance. And it was confirmed that the operation takes a short time In a large building structure.