• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.390-396
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• 2007

Fuzzy-CBR Collision Avoidance Support System is a system that finds a solution from past knowledge retrieved from the database and adapted to a new situation. Its algorithm has resulted to an adapting a solution for a new situation. However, ontology is needed in identifying concepts, relations and instances that are involved in a situation in order to improve and facilitate the efficient retrieval of similar cases from the CBR database. This paper proposes the way to apply ontology for identifying the concepts involved in a new environment and use them as inputs, for a ship collision avoidance support system., Similarity will be obtained through document articulation and using abstraction levels. A conceptual model of a maneuvering situation will be built using these ontologies.

• International Journal of Control, Automation, and Systems
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• v.5 no.5
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• pp.539-546
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• 2007

The important field of research in ship operation is related to the high efficiency of transportation, the convenience of maneuvering ships and the safety of navigation. For these purposes, many intelligent technologies for ship automation have been required and studied. In this paper, we propose an intelligent voice instruction-based learning (VIBL) method and discuss the building of a ship's steering control system based on this method. The VIBL system concretely consists of two functions: a text conversion function where an instructor's inputted voice is recognized and converted to text, and a linguistic instruction based learning function where the text instruction is understood through a searching process of given meaning elements. As a study method, the fuzzy theory is adopted to build maneuvering models of steersmen and then the existing LIBL is improved and combined with the voice recognition technology to propose the VIBL. The ship steering control system combined with VIBL is tested in a ship maneuvering simulator and its validity is shown.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1671-1686
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• 2022

Face manipulation tools represented by Deepfake have threatened the security of people's biological identity information. Particularly, manipulation tools with deep learning technology have brought great challenges to Deepfake detection. There are many solutions for Deepfake detection based on traditional machine learning and advanced deep learning. However, those solutions of detectors almost have problems of poor performance when evaluated on different quality datasets. In this paper, for the sake of making high-quality Deepfake datasets, we provide a preprocessing method based on the image pixel matrix feature to eliminate similar images and the residual channel attention network (RCAN) to resize the scale of images. Significantly, we also describe a Deepfake detector named Cascaded-Hop which is based on the PixelHop++ system and the successive subspace learning (SSL) model. By feeding the preprocessed datasets, Cascaded-Hop achieves a good classification result on different manipulation types and multiple quality datasets. According to the experiment on FaceForensics++ and Celeb-DF, the AUC (area under curve) results of our proposed methods are comparable to the state-of-the-art models.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10a
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• pp.359-362
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• 2000

ITS(Intelligent Transportation System)는 도로와 차량 등 기존 교통의 구성요소에 첨단의 전자.정보.통신 기술을 적용시켜 교통시설을 효율적으로 운영하여 통행자에게 유용한 정보를 제공하여 안전하고 편리한 통행과 전체 교통체계의 효율성을 기할 수 있는 기술이다. 이러한 ITS의 핵심기술로는 데이터베이스, 메시지 집합 분야통신방식 분야, 소프트웨어 개발 분야, 교통정보관리 분야, 기타관련 분야 등이 있으며 본 논문에서는 이와 같은 기술의 국내외 시장현황 및 표준화 현황 등에 관하여 상술하고자 한다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.97-113
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• 2023

Swift and appropriate responses in emergency situations like objects falling on the road can bring convenience to road users and effectively reduces secondary traffic accidents. In Korea, current intelligent transportation system (ITS)-based detection systems for emergency road situations mainly rely on loop detectors and CCTV cameras, which only capture road data within detection range of the equipment. Therefore, a new detection method is needed to identify emergency situations in spatially shaded areas that existing ITS detection systems cannot reach. In this study, we propose a ResNet-based algorithm that detects and classifies emergency situations from vehicle camera footage. We collected front-view driving videos recorded on Korean highways, labeling each video by defining the type of emergency, and training the proposed algorithm with the data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.3
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• pp.80-96
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• 2024

This study conducted over two rounds Delphi survey targeting experts in the fields of roads, transportation, automobiles, intelligent transport systems(ITS), and communications to analyze the direction of change in road design, operation, and systems in the Lv.4/4+ autonomous driving era. To construct the Delphi survey items, a basic survey was conducted. The first and second Delphi surveys targeted experts in fields closely related to autonomous driving. The results of the survey revealed an expectation that in the future, transportation operations would change focus to shared autonomous vehicle(AV) and public transportation transfers, and there would be corresponding changes in the cross-sectional configuration. Exclusive lanes for AV are expected to be introduced commencing from highways and general national roads, and there was a consensus that they should be installed in the center of the road rather than on the sides and would use the same lane width as that of the existing road. In terms of facilities for AVs, it was found that it would be necessary to expand pedestrian-vehicle separation facilities, insert communication chips into facilities for location recognition, advance precision maps, and expand roadside communication facilities.

• Journal of the Korea Safety Management & Science
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• v.12 no.4
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• pp.175-181
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• 2010

The government have plans to improve the railway transport capacity and transport hub for the sustainable national transport and logistics system. Specially, there are much efforts to improve transportation capacity such as high speed transportation of rail freight, enlargement of BT train, development of double stack train, etc. between railway transport hubs. If the transport capacity between railway logistics hubs is increased as planned, we must increase the handling capacity of railway hub terminals. But there are limits to enlarge the terminal infrastructure because of investment scale, location circumstances and urban development plans. To ensure the capacity, with the minimum required enlargement of infrastructure, it is necessary to extremely increase the efficiency of terminal operations. For improving the efficiency, we have to introduce the efficient terminal operation systems based on u-IT and operation optimize technologies. In this paper, we analyse the issues and problems of railway terminals(including ICD) and suggest the concept of intelligent railway terminal and the construction components of technology.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.433-437
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• 2005

The goal of our research is to develop a formal modeling methodology for supervisory and controlling systems that have artificially intelligent features. This approach is agent-based and central to the development of the model of mobility agent considering reactivity for real-time purpose and deliberation for optimal realization and safe-fail problems for critical systems like Intelligent Transportation Systems by high-level Petri net. By using nets within nets we investigate the concurrency of the system and the agent in one model without losing the needed abstraction, and synchronous channels are introduced to denote the coordination and communication. Finally an example is demonstrated.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.104-115
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• 2023

User-centered public transportation services such as DRT, Autonomous Transit etc. have been provied but current minimum level of service for public transportation has been evaluated by the operator because there is no data on user's accessibility to use public transportation. This study was performed GRID analysis using altteul transport card data including user's accessibility to use public transportation. The analysis result showed that user's accessibility to use public transportation was different within a same dong area. We proposed improving minimum level of service for public transportation considered by the user. The result of applying the proposed method showed that many area was changed to unsatisfied area for minimum level of service for public transportation

• IE interfaces
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• v.23 no.4
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• pp.349-356
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• 2010

The role of Intelligent Transportation System (ITS) is to efficiently manipulate the traffic flow and reduce the cost in logistics by using the state of the art technologies which combine telecommunication, sensor, and control technology. Especially, the hardware part of ITS is rapidly adapting to the up-to-date techniques in GPS and telematics to provide essential raw data to the controllers. However, the software part of ITS needs more sophisticated techniques to take care of vast amount of on-line data to be analyzed by the controller for their decision makings. In this paper, the authors develop a traffic congestion prediction model based on several different parameters from the sensory data captured in the Vehicle Detection System (VDS). This model uses the neural network technology in analyzing the traffic flow and predicting the traffic congestion in the designated area. This model also validates the results by analyzing the errors between actual traffic data and prediction program.