• Journal of the Korean Society of Industry Convergence
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• v.27 no.4_2
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• pp.1001-1007
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• 2024

Recent deep learning algorithms for object detection in real-time play a crucial role in various applications such as autonomous driving, traffic monitoring, health care, and water quality monitoring. The size of small objects, in particular, significantly impacts the accuracy of detection models. However, data containing small objects can lead to underfitting issues in models. Therefore, this study developed a deep learning model capable of quickly detecting small objects to provide more accurate predictions. The RE-SOD (Residual block based Small Object Detector) developed in this research enhances the detection performance for small objects by using RGB separation preprocessing and residual blocks. The model achieved an accuracy of 1.0 in image classification and an mAP50-95 score of 0.944 in object detection. The performance of this model was validated by comparing it with real-time detection models such as YOLOv5, YOLOv7, and YOLOv8.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.5
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• pp.62-69
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• 2012

Traffic simulation models have been used for assessing various transportation strategies. Through comparing results from a simulation model and real field data, researchers try to show how close the model can reproduce the real world traffic. This model verification step is one of the most essential tasks in modeling procedure. Traffic counts and speeds have been frequently used for the verification or validation. Authors modeled severe PM peak bottleneck situation on the I-40 corridor in Raleigh, North Carolina using DYNASMART-P, a mesoscopic traffic simulation tool and verified the model. NCDOT has Traffic Information Management System which has archive capability for the traffic speeds on the I-40 corridor. However, the authors selected travel time as the field measure for model verification and collected the data using a GPS equipment because the speed data from NCDOT speed detectors are spot speeds which are not appropriate for comparison with link average speed from the simulation model. This paper describes the GPS field data collection procedure, the model verification method, and the results.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.3
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• pp.59-72
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• 2017

As the part of study which handles the measure to use the individual vehicle information of taxi GPS data on signal controls in order to overcome the limitation of Loop detector-based collecting methods of real-time signal control system, this paper conducted series of evaluations and improvements on link travel time, queue vehicle time estimates and traffic condition decision algorithm from the research introduced in 2016. considering the control group and the other, the link travel time has enhanced the travel time and the length of queue vehicle has enhanced the estimated model taking account of the traffic situation. It is analyzed that the accuracy of the average link travel time and the length of queue vehicle are respectably both approximately 95 % and 85%. The traffic condition decision algorithm reflected the improved travel speed and vehicle length. Smoothing was performed to determine the trend of the traffic situation and reduce the fluctuation of the data, and the algorithms have refined so as to reflect the pass period on overflow judgment criterion.

• Journal of Korean Society of Transportation
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• v.29 no.2
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• pp.111-121
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• 2011

This paper discusses a method for optimizing the semi-actuated traffic signal control system by adjusting the initial interval according to the number of vehicles waiting for the green light in the actuated phase. We also present a Left-Turn actuated traffic signal control strategy that examines the vehicular noise in the detection area and determines the phase extension and the gap-out. In order to detect the vehicles in real-time, an image detector's Video Image Tracking technology was adopted. A 'Zone in Zone'method was implemented, and the image detection area is segmented into three zones: 1) Zone1 for verifying a vehicles obligatory presence, 2) Zone2 for counting the standby vehicles, and 3) Zone3 for examining the number of vehicles that have passed. The on-site assessment of the Left Turn Actuated Control is carried out using CORSIM, and the results show that the Control Delay decreased by 23.10%, 15.06%, and 4.34% compared to the delays resulted from pre-timed control, semi-actuated control-1 and semi-actuated control-2 traffic signal control systems respectively. The Queue Time also decreased by 36.24%, 20.10% and the Total Time by 14.36%, 7.02% for the same scenario. Which clearly demonstrates the operational efficiency. A sensitivity analysis reveals that the improvement from the propose traffic control strategy tends to increase as the through traffic volume reaches a saturated condition and the left-turn traffic volume decreases.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.12
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• pp.1857-1863
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• 2012

The VDS(Vehicle Detection System) collects and transfers information about traffic situations in real time, therefore it makes the traffic management effective. Recently, the VDSs have provided good stability and accuracy in regard to system reliability and functions but they also have showed problems such as raising costs and consuming times when a new system is installed and/or the environmental requirements for the system are set up. The reason of the problems is that up to now the collection of the data and information about the traffic situations has been achieved by the 1:1 information exchange between the traffic control surveillance center and the each traffic field, between equipments and centers, and among data processing equipments and also centers. The communication systems used in the VDS are generally composed of 1 : 1 connection of the lines because the communication protocols are different in the most of the cases mentioned above. Consequently, this makes the number of communication lines become larger and causes the cost for the whole traffic information systems to increase. In this paper, a development of a controller to unify the communication protocols for the VDS is peformed to solve the problems which were mentioned above. Specially, the controller developed in this paper was applied to a radar vehicle detector and tested to show its usefulness. In addition to that, the developed controller was also designed to include functions to transfer the information about weather conditions on the roads.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.6
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• pp.40-52
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• 2011

This paper develops a traffic condition decision algorithm to improve the reliability of traffic information on urban streets. This research is reestablished the criteria of qualitative traffic condition categorization and proposed a new qualitative traffic condition decision types and decision measures. The developed algorithm can be classified into 9 types for qualitative traffic condition in consideration of historical time series of speed changes and traffic patterns. The performance of the algorithm is verified through individual matching analysis using the radar detector data in Ansan city. The results of this paper is expected to help promotion of the traffic information processing system, real-time traffic flow monitoring and management, use of historical traffic information, etc.

• Journal of Korean Society of Transportation
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• v.25 no.5
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• pp.33-42
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• 2007

The current left-turn split model adopted in COSMOS has an inherent limitation when a loop detector in the left-turn lanes was disconnected for a period of time. In this instance, the current model always allocated minimum green time to the left-turn phase, thus optimal split and efficient signal operation for the intersection was not guaranteed. In this paper, four mathmatical models using detector information of the intersection and four empirical models using historical profiles were developed and investigated for different traffic conditions to improve the operational efficiency of the intersection. From the model evaluation test, the empirical model using a four-week historical profile produced the least error among the eight models investigated. NETSIM simulation test results also showed that the proposed model could give significantly reduced delay time as compared to the current model. From these results, the operational efficency of the signalized intersections under the real-time control can be greatly improved by using the model proposed in case of the left-turn detector failure.

• Journal of Korean Society of Transportation
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• v.13 no.1
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• pp.185-203
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• 1995

The purpose of this paper is to develop a microscopic traffic simulation model which is able to both analyze and the evaluate signlaized urban network and to verify its usefulness in comparison with the other model which has alfeady been released. This simulation model adopts the General Motor's 5th model for car-following and introduces an unique lanechanging rule using acceptable gap. It analyzes single and dual-ring signal phases and generates detector information . So it could be applied to dynamic route guidance systems as wel as real time signal control systems. The results derived from Netsim and the observed data from the real network have been used to test the validit of the proposed model. The result of the test has shown that there are no significant differences between the NETSIM model and the proposed model in estimating travel speed and stopped delay. In optimum offset estimatin , it has shown the same results with NETSIM. the measure of effectiveness , however, derived from this model is slightly better than that of the real network situation. This may be due to the fact that the proposed model does not take into account side frictions from interferences and obstacles.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.1
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• pp.15-27
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• 2013

While the vehicle detector is collected from a variety of information was mainly used as a real-time data. Recently scheme of application for archived traffic data has become increasingly important. In this background, this research were conducted on the improvement of the preprocessing for archived traffic data application. The purpose of improving specific preprocessing was reflect transportation phenomena by traffic data. As evaluation result, improvement preprocessing was close to the actual value than exist preprocessing.

• Journal of Korean Port Research
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• v.13 no.1
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• pp.113-122
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• 1999

Congestion and traffic accidents occur on the merge and diverge sections in the interchange of the freeway. Studies have been conducted to reduce the traffic delay and accidents on the merge section in the freeway since 1960s. but a study was not conducted to estimate the speed variation on the merge section construct models estimated for the speed variation and suggest the appropriate measures. The purpose of this study was to identify the traffic flow characteristics on the merge section in the freeway construct the models estimated for the speed variation on the merge section in the freeway and finally establish the appropriate measure for reduction of traffic delay and accidents on the merge section in the freeway. The following results were obtained: I) Speed variations in the urban freeway appeared to be about 3.2mph, 6.5mph and 7.4mph based on the morning peak period, afternoon peak period and 24-hours period but those in the suburban freeway appeared to be about 8.0mph, 11.1mph and 10.1mph based on the same periods respectively. So different speed reduction signs need be installed to reduce delay and accidents on the merge section in the freeway based on the areas and periods as the freeway traffic management system(FTMS). ii) These models estimated for speed variation need to be studied with the changeable message sign(CMS) technique based on the real-time data so that the traffic flow could be maximized and the traffic delay and accidents be on the merge section in the freeway as more efficient freeway traffic management system(FTMS) in the near future.