• Journal of Korean Society of Transportation
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• v.20 no.3
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• pp.159-168
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• 2002

The Highway Capacity Manual(HCM) suggests estimating the average green time for the performance evaluation of the traffic actuated operation and Provides the average green time estimation model. However, the model provides with much room for improvements. This document proposes a new analytical model that overcomes the shortage of the HCM model. The average green times estimated by the HCM model and the proposed model were compared. A computer program using the proposed model was coded for the study, while the ACT348 program was used for the implementation of the HCM model Through the comparison study based on the 1,196 hypothetical simulation data surrogating field data, it was found that the average green times estimated by the proposed model yields much nicer one-to-one linear relationship to the simulation results than the ones from the HCM model in both exclusive-only and shared-permitted cases. The R2 values of the proposed and the HCM models with those cases are 0.90 and 0.56, and 0.86 and 0.57, respectively.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.1
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• pp.1-9
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• 2010

In this paper we propose a scheduling algorithm for supporting Quality of Service(QoS) in IEEE 802.11e HCCA referred to as ASR-DRR and ASD-DRR, which aims at providing improved performance for the support of multimedia traffic. Although We identify the problem of the current IEEE 802.11e HCCA (Hybrid Coordination Function Controlled Channel Access) scheduler and its numerous variations, that the queue information cannot be notified to the Hybrid Coordinator (HC) timely, therefore the uplink delay lengthens unnecessarily. We suggests a simple solution and a couple of implementation practices, namely the Adaptive Scheduler with RTS/CTS (ASR) and Adaptive Scheduler with Data/Ack (ASD). They are both further elaborated to emulate the Deficit Round Robin (DRR) scheduler. They are also compared with existing exemplary schedulers through simulation, and shown to perform well.

• International Journal of Highway Engineering
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• v.16 no.5
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• pp.109-119
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• 2014

PURPOSES : The control delay in seconds per vehicle is the most important traffic operational index to evaluate the level of service of signalized intersections. Thus, it is very critical to calculate accurate control delay because it is used as a basic quantitative evidence for decision makings regarding to investments on traffic facilities. The control delay consists of time-in-queue delay, acceleration delay, and deceleration delay so that it is technically difficult to directly measure it from fields. Thus, diverse analysis tools, including CORSIM, SYNCHRO, T7F, VISTRO, etc. have been utilized so far. However, each analysis tool may use a unique methodology in calculating control delays. Therefore, the estimated values of control delays may be different by the selection of an analysis tool, which has provided difficulties to traffic engineers in making solid judgments. METHODS : This study was initiated to verify the feasibility of diverse analysis tools, including HCM methodology, CORSIM, SYNCHRO, T7F, VISTRO, in calculating control delays by comparing estimated control delays with that measured from a field. RESULTS : As a result, the selected tools produced quite different values of control delay. In addition, the control delay value estimated using a calibrated CORSIM model was closest to that measured from the field. CONCLUSIONS : First, through the in-depth experiment, it was explicitly verified that the estimated values of control delay may depend on the selection of an analysis tool. Second, among the diverse tools, the value of control delay estimated using the calibrated microscopic traffic simulation model was most close to that measured from the field. Conclusively, analysts should take into account the variability of control delay values according to the selection of a tool in the case of signalized intersection analysis.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.5
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• pp.400-404
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• 2009

Native Command Queueing is a technology to maximize throughput of disk system by reordering requests in its command queue. Recent S-ATA 2 standard specifies a protocol for the purpose of dealing with NCQ feature, making most vendors implementing it in their disk devices. However, the new feature, NCQ, may lead to information gap between OS and disk drive. 05 considers that disk will service I/O requests in the order as OS has dispatched. Unfortunately, it isn't true any more since NCQ would simply ignore the policy of OS and reorder the sequence OS has expected. Let us define the term as expectation-discord. Due to the discord, serious performance anomalies or starvation of requests may occur in I/O subsystem. In this paper, we confirm that the expectation-discord actually brings about starvation of requests. We propose a solution to settle it. Our solution is very simple, effective, cheap(not requiring any hardware modification) and portable across various OS. Experimental results show that our solution can balance throughput and response time very well.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.111-120
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• 2018

This study focuses on utilizing drones for performance evaluation of ITS detectors and analyzing economic feasibility when performance evaluation is conducted by the traffic management center's own personnel using drones. The study sites were selected from DSRC, video detector, and radar detector locations and drone filming was conducted to obtain travel speed, queue length, and delay time and compare with the detector data. It was shown that drones can be very effectively used to evaluate performance of major ITS detectors such as DSRC and video detectors. In addition, it was analyzed that a drone operated by the traffic management center's own personnel provides very economic solution for ITS detector performance evaluation when compared to consignment by external agencies.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.585-587
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• 2022

The visual motivation between AP devices is NTP-based visual motivation through the access of the Internet through the internal wired LAN, but this has several seconds of visual difference in hundreds of milliseconds (msec) depending on the network. The frame for the output of the video will vary depending on the application, but usually 24 (image) frames are output to the screen in one second. Therefore, the visual synchronization between peripheral devices can be performed through the adjacent moving camera device, not the wired method. The programming method of generating API for synchronization command when creating an application for visual synchronization and delivering it to AP through MAC may differ from the time in synchronization command according to the environment of the operating system at the transmission side and the situation of the buffer queue of the MAC. Therefore, as a method to solve this problem, the renewal of visual information in the device driver terminal controlling MAC can be much more effective.

• Journal of KIISE:Information Networking
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• v.28 no.4
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• pp.527-539
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• 2001

The wireless asynchronous transfer mode (ATM) system has the advantage of providing the broadband services with various quality-of-service requirements to the mobile terminal efficiently by utilizing the ATM technology developed for the wired ATM system. The available bit rate (ABR) service among various ATM services utilizes the available bandwidth remaining in the ATM link, which allows the efficient bandwidth usage. During the handoff of the mobile terminal, however, the queue length in the access point (AP) which resides in the boundary of the wired ATM network and the wireless ATM network may increase abruptly. In this paper, we propose a scheme which prevents the buffer-overflow and buffer-underflow in the AP during the handoff of the wireless ABR connection in the wireless ATM system using binary feedback rate-based ABR traffic control. This scheme controls the source's cell generation rate during both handoff period and some time interval after the completion of the handoff procedure. The simulation results show that the proposed scheme prevents the buffer-overflow and buffer-underflow. The proposed scheme can contribute to increasing the throughput of the wireless ABR service during handoff by preventing the buffer overflow and underflow during handoff period.

• The Transactions of the Korea Information Processing Society
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• v.3 no.2
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• pp.283-294
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• 1996

To operate the automatic devices of manufacturing process more effectively and to solve the needs of the resource sharing, network technology is applied to the unit control devices located in common manufacturing zone and operated by connecting them. This paper introduces deign and test operation of cell system for the management of multivendor PLC by applying to wall paper process based on the manufacturing standardization of CIM. The analysis of designed multivendor PLC group is performed by selecting the parameters such as variation of data packet size and node number of PLC ladder logic program and variation by analyzing the corresponding variation values of token rotation time and waiting time for the system operation. For the method of the analysis,the equation is considering the overhead such as indicated packet service time and transmission safety margin for PLC network connection in M/G/1 queue model,and it is applied to the cell system and PLC group manage-ment for operation .Through the experiment,it is found that the realtime processing is possible with expanded and better result than the resuit obtained by Jayasumana.Browaka with PLC scan time considered,response lower limit of 10-20 msec. data packet size not more than 50 bytes.and the number of nodes less than 40.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.167-175
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• 2019

Recently, health examination centers have been changing from auxiliary medical facilities to key and independent medical facilities. However, it is not easy to improve medical facilities, including health examination centers, due to the variable characteristics of the relationship between humans and space. Therefore, this study was done to develop a pedestrian-based discrete event simulation analysis program to examine the problems and develop methods for improvement. The program was developed to analyze five evaluation indices and the density of examinees. The problems were derived by analyzing the required time, capacity, and queue size for each examination through simulations. We reduced the examination time and moving distance, increased the capacity, and distributed the queues by adjusting the medical services and relocating the examination rooms. The results were then quantitatively verified by simulations.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.89-106
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• 2022

Recently, the amount of video data collected from smartphones, CCTVs, black boxes, and high-definition cameras has increased rapidly. According to the increasing video data, the requirements for analysis and utilization are increasing. Due to the lack of skilled manpower to analyze videos in many industries, machine learning and artificial intelligence are actively used to assist manpower. In this situation, the demand for various computer vision technologies such as object detection and tracking, action detection, emotion detection, and Re-ID also increased rapidly. However, the object detection and tracking technology has many difficulties that degrade performance, such as re-appearance after the object's departure from the video recording location, and occlusion. Accordingly, action and emotion detection models based on object detection and tracking models also have difficulties in extracting data for each object. In addition, deep learning architectures consist of various models suffer from performance degradation due to bottlenects and lack of optimization. In this study, we propose an video analysis system consists of YOLOv5 based DeepSORT object tracking model, SlowFast based action recognition model, Torchreid based Re-ID model, and AWS Rekognition which is emotion recognition service. Proposed model uses single-linkage hierarchical clustering based Re-ID and some processing method which maximize hardware throughput. It has higher accuracy than the performance of the re-identification model using simple metrics, near real-time processing performance, and prevents tracking failure due to object departure and re-emergence, occlusion, etc. By continuously linking the action and facial emotion detection results of each object to the same object, it is possible to efficiently analyze videos. The re-identification model extracts a feature vector from the bounding box of object image detected by the object tracking model for each frame, and applies the single-linkage hierarchical clustering from the past frame using the extracted feature vectors to identify the same object that failed to track. Through the above process, it is possible to re-track the same object that has failed to tracking in the case of re-appearance or occlusion after leaving the video location. As a result, action and facial emotion detection results of the newly recognized object due to the tracking fails can be linked to those of the object that appeared in the past. On the other hand, as a way to improve processing performance, we introduce Bounding Box Queue by Object and Feature Queue method that can reduce RAM memory requirements while maximizing GPU memory throughput. Also we introduce the IoF(Intersection over Face) algorithm that allows facial emotion recognized through AWS Rekognition to be linked with object tracking information. The academic significance of this study is that the two-stage re-identification model can have real-time performance even in a high-cost environment that performs action and facial emotion detection according to processing techniques without reducing the accuracy by using simple metrics to achieve real-time performance. The practical implication of this study is that in various industrial fields that require action and facial emotion detection but have many difficulties due to the fails in object tracking can analyze videos effectively through proposed model. Proposed model which has high accuracy of retrace and processing performance can be used in various fields such as intelligent monitoring, observation services and behavioral or psychological analysis services where the integration of tracking information and extracted metadata creates greate industrial and business value. In the future, in order to measure the object tracking performance more precisely, there is a need to conduct an experiment using the MOT Challenge dataset, which is data used by many international conferences. We will investigate the problem that the IoF algorithm cannot solve to develop an additional complementary algorithm. In addition, we plan to conduct additional research to apply this model to various fields' dataset related to intelligent video analysis.