• Journal of Korean Society of Transportation
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• v.22 no.2 s.73
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• pp.165-175
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• 2004

본 고는 대전광역시 첨단교통모델도시 건설사업의 일환으로 구축된 DSRC(Dedicated Short Range Communication) 기술을 활용한 교통정보시스템 구축 사례를 소개함을 목적으로 한다. 공공부문에서의 구간정보 수집 및 가공 체계 구축은 본 대전 ITS 사업이 처음이며 더욱이 DSRC 기술을 구간정보 수집에 적용한 최초의 시도이다. 이에 시스템 구축과정에서 적지 않은 쟁점이 도출되었고, 많은 시행착오를 통해 그 해법을 찾아가며 현재 운영중인 시스템을 완공하게 되었다. 노변기지국(RSE)과 차량장치(OBE)간의 통신에 의해 수집된 자료는, 필터링, 검지기 지점정보, 패턴데이터 등과의 자료합성, 평활화, 통계정보 및 패턴정보 생성 등의 과정을 거쳐 구간소통정보가 산출된다. 현재 운영중인 본 시스템은 향후 지속적으로 보완 발전시켜 나가야 하며, 이를 위해 프로브 수집체계 보완, 시스템의 성능평가, 패턴데이터의 적절한 유지관리, 알고리즘의 지속적 발전 등을 향후과제로서 제시하였다. 본 고는 ITS사업에 있어 중요 쟁점중에 한 분야인 소통정보의 가공 절차를 공유함으로써, 관련 분야의 기술개발 촉진과 향후 유사시스템 구축의 시행착오를 줄이는데 기여할 수 있으리라 판단된다.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.479-487
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• 2021

In this paper, we propose an Sound Event Detection (SED) model using self-training based on a noisy student model. The proposed SED model consists of two stages. In the first stage, a mean-teacher model based on an Residual Convolutional Recurrent Neural Network (RCRNN) is constructed to provide target labels regarding weakly labeled or unlabeled data. In the second stage, a self-training-based noisy student model is constructed by applying different noise types. That is, feature noises, such as time-frequency shift, mixup, SpecAugment, and dropout-based model noise are used here. In addition, a semi-supervised loss function is applied to train the noisy student model, which acts as label noise injection. The performance of the proposed SED model is evaluated on the validation set of the Detection and Classification of Acoustic Scenes and Events (DCASE) 2020 Challenge Task 4. The experiments show that the single model and ensemble model of the proposed SED based on the noisy student model improve F1-score by 4.6 % and 3.4 % compared to the top-ranked model in DCASE 2020 challenge Task 4, respectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.1-13
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• 2023

This study develops an optimal mobile-communication-based National Highway traffic volume estimation model using an ensemble-based machine learning algorithm. Based on information such as mobile communication data and VDS data, the LightGBM model was selected as the optimal model for estimating traffic volume. As a result of evaluating traffic volume estimation performance from 96 points where VDS was installed, MAPE was 8.49 (accuracy 91.51%). On the roads where VDS was not installed, traffic estimation accuracy was 92.6%.

• Journal of Korean Society of Transportation
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• v.28 no.3
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• pp.169-183
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• 2010

Image-based traffic information collection systems have entered widespread adoption and use in many countries since these systems are not only capable of replacing existing loop-based detectors which have limitations in management and administration, but are also capable of providing and managing a wide variety of traffic related information. In addition, these systems are expanding rapidly in terms of purpose and scope of use. Currently, the utilization of image processing technology in the field of traffic accident management is limited to installing surveillance cameras on locations where traffic accidents are expected to occur and digitalizing of recorded data. Accurately recording the sequence of situations around a traffic accident in a freeway and then objectively and clearly analyzing how such accident occurred is more urgent and important than anything else in resolving a traffic accident. Therefore, in this research, existing technologies, this freeway attribute, velocity changes, volume changes, occupancy changes reflect judge the primary. Furthermore, We pointed out by many past researches while presenting and implementing an active and environmentally adaptive methodology capable of effectively reducing false detection situations which frequently occur even with the Gaussian Mixture model analytical method which has been considered the best among well-known environmental obstacle reduction methods. Therefore, in this way, the accident was the final decision. Also, environmental factors occur frequently, and with the index finger situations, effectively reducing that can actively and environmentally adaptive techniques through accident final judgment. This implementation of the evaluate performance of the experiment road of 12 incidents in simulated and the jang-hang IC's real-time accident experiment. As a result, the do well detection 93.33%, false alarm 6.7% as showed high reliability.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5D
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• pp.635-644
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• 2009

Image processing technique in the outdoor environment is very sensitive, and it tends to lose a lot of accuracy when it rapidly changes by outdoor environment. Therefore, in order to calculate accurate traffic information using the traffic monitoring system, we must resolve removing shadow in transition time, Distortion by the vehicle headlights at night, noise of rain, snow, and fog, and occlusion. In the research, we developed a system to calibrate the amount of traffic, speed, and time occupancy by using image processing technique in a variety of outdoor environments change. This system were tested under outdoor environments at the Gonjiam test site, which is managed by Korea Institute of Construction Technology (www.kict.re.kr) for testing performance. We evaluated the performance of traffic information, volume counts, speed, and occupancy time, with 4 lanes (2 lanes are upstream and the rests are downstream) from the 16th to 18th December, 2008. The evaluation method performed as based on the standard data is a radar detection compared to calculated data using image processing technique. The System evaluation results showed that the amount of traffic, speed, and time occupancy in period (day, night, sunrise, sunset) are approximately 92-97% accuracy when these data compared to the standard data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.1
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• pp.44-57
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• 2020

A dedicated short-range communications (DSRC) traffic information system is a detection system for a section of road using communication between roadside equipment and on-board High-Pass units to collect road traffic information and provide reliable traffic information to drivers. The Ministry of Land, Infrastructure, and Transport announced that a DSRC system must be supported to pass the performance evaluation of an intelligent transportation system (ITS), and the performance evaluation for DSRC systems installed in expressways and national highways is started. Currently, DSRC traffic information systems are only managed for maintenance and functional-monitoring purposes, which means that detailed criteria for the operation of a DSRC traffic information system, such as communication range, the direction of the antenna, and the power of the radio wave, etc., need to be established. In this paper, the criteria of the performance evaluation of a DSRC traffic information system are presented for different road types and road environments. The proposed performance evaluation criteria included the communication range and communication power of roadside equipment. In addition, installation criteria, such as the direction of the antenna, and the height and angle of the installed system, are presented for different road types and road environments. The criteria presented were evaluated for DSRC roadside equipment and documented to improve system maintenance and quality control of the communication system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.10
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• pp.948-956
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• 2014

Today, Intelligent Vehicle Detection System seeks to reduce the negative factors, such as accidents over to get the traffic information of existing system. This paper proposes detection algorithm for the illegal U-turn vehicles which can cause critical accident among violations of road traffic laws. We predicted that if calculated optical flow vectors were shown on the illegal U-turn path, they would be cause of the illegal U-turn vehicles. To reduce the high computational complexity, we use the algorithm of pyramid Lucas-Kanade. This algorithm only track the key-points likely corners. Because of the high computational complexity, we detect center lane first through the color information and progressive probabilistic hough transform and apply to the around of center lane. And then we select vectors on illegal U-turn path and calculate reliability to check whether vectors is cause of the illegal U-turn vehicles or not. Finally, In order to evaluate the algorithm, we calculate process time of the type of algorithm and prove that proposed algorithm is efficiently.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.2 s.3
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• pp.55-64
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• 2003

This research is about executing the suitability evaluation of the data through wireless communication system in comparison with the data through the wire system used in National Highway Traffic Management System. The communication system for the evaluation was established on Peoyngteak-Anjung section(about 19 Km) at Route 38 in southern National Highway of the National Capital region where image detectors with the communication by wire were set up. In the situation, the comparison of the data transmission rates between the wire system and the proposed system was accomplished. Before we evaluate the possibility of application about the proposed system, the elements of wireless systems performed the spot investigations. Traffic data transmission test among the equipments was accomplished on the section of the Route 38 where wireless communication equipments were set up. And then, the test of traffic data transmission between the field equipment and the data collective center of wireless communication system was carried out. It evaluated the reliability of wireless communication data for the suitability evaluation of cable/wireless data collected while 73 days.

• Fire Science and Engineering
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• v.29 no.6
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• pp.51-56
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• 2015

In Korea, measures to maintain sustainable fire safety performance for apartment buildings are insufficient in terms of fire-fighting products, skilled personnel, and maintenance status. Also, because of the particular features of a fire compartment, it has structural problems that are very likely to cause damage to human life when a fire occurs. Currently, problems with the fire supervisory system installed in an apartment building cannot be checked in real time, so it is difficult to identify the location of a fire accurately. Protected areas are also not assigned to each household, and residents cannot be clearly informed of the occurrence of a fire. As a consequence, safety evacuation cannot be secured. In addition, it is impossible to test the operation performance for water detectors in sprinkler fire extinguishing systems outside of the household. Therefore, an experiment was conducted to evaluate the performance of a remote fire supervisory system. The results show that the system satisfies all performance requirements. Also, an household alarm system was installed in each household to alert of any occurrence of a fire accurately, and the performance of the alarm system was improved to ensure that residents were quickly evacuated.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.4
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• pp.11-23
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• 2011

The objective of this paper is to develop a daily pattern clustering algorithm using historical traffic data that can reliably detect under various traffic flow conditions in urban streets. The developed algorithm in this paper is categorized into two major parts, that is to say a macroscopic and a microscopic points of view. First of all, a macroscopic analysis process deduces a daily peak/non-peak hour and emphasis analysis time zones based on the speed time-series. A microscopic analysis process clusters a daily pattern compared with a similarity between individuals or between individual and group. The name of the developed algorithm in microscopic analysis process is called "Two-step speed clustering (TSC) algorithm". TSC algorithm improves the accuracy of a daily pattern clustering based on the time-series speed variation data. The experiments of the algorithm have been conducted with point detector data, installed at a Ansan city, and verified through comparison with a clustering techniques using SPSS. Our efforts in this study are expected to contribute to developing pattern-based information processing, operations management of daily recurrent congestion, improvement of daily signal optimization based on TOD plans.