• International journal of advanced smart convergence
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• v.1 no.1
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• pp.38-42
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• 2012

Automobilist in South Korea in order to provide car driving information to the insurance company uses 'car driving information device'. They provide car driving information of device to insurers for their premium discount. Currently these devices are used in Korea has inconvenience that this device Installation and the process for send this information to insurance companies. In this paper, Korean smart car driving information system designed using Smart phone and local-range network as a basis the 'Certification Regulations of Driving Information Check Device' of the Korea Insurance Development Institute.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.669-678
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• 2018

This study developed information technology infrastructures for building a driving environment analysis platform using various big data, such as vehicle sensing data, public data, etc. First, a small platform server with a parallel structure for big data distribution processing was developed with H/W technology. Next, programs for big data collection/storage, processing/analysis, and information visualization were developed with S/W technology. The collection S/W was developed as a collection interface using Kafka, Flume, and Sqoop. The storage S/W was developed to be divided into a Hadoop distributed file system and Cassandra DB according to the utilization of data. Processing S/W was developed for spatial unit matching and time interval interpolation/aggregation of the collected data by applying the grid index method. An analysis S/W was developed as an analytical tool based on the Zeppelin notebook for the application and evaluation of a development algorithm. Finally, Information Visualization S/W was developed as a Web GIS engine program for providing various driving environment information and visualization. As a result of the performance evaluation, the number of executors, the optimal memory capacity, and number of cores for the development server were derived, and the computation performance was superior to that of the other cloud computing.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.5
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• pp.1-13
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• 2011

Recently, a number of OBU(On Board Unit) have being spreaded since ETCS(Electronic Toll Collection System)using DSRC(Dedicated Short Range Communication) was installed in the tollgate of the whole country. Many R&D and commercialization related to ITS service using DSRC and OBU mentioned above are ongoing such as traffic information collection and provision and a signal control, and public traffic information and management and so on. Especially, there are many researches conducted(conducting) on traffic information collection and provision using communication between OBU and RSE. However, Standards for both DSRC application and traffic collection and provision are not established clearly yet. So we would like to suggest a method of traffic information collection and provision without changing of standard related to DSRC. This method is to put the traffic messages into the existing Action primitive for ETC, which is described on "Technical criterion IV of basic traffic information exchange" which was notified by Ministry of Land, Transport and Maritime Affairs. Proposed standard application method is applied both to RSE and OBE. It is the same system which ETCS used in highway, currently. We confirmed the efficiency and performance of the system through conducting a variety of driving test using 4 vehicles in real road condition. Result of the real road test shows the effectiveness and validity of this method with about 97% communication success rate and based on studying the cases of 3% communication failure, we can analyse the expected problems in traffic information collection and provision using this method.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1445-1456
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• 2018

Environment perception and three-dimensional (3D) reconstruction tasks are used to provide unmanned ground vehicle (UGV) with driving awareness interfaces. The speed of obstacle segmentation and surrounding terrain reconstruction crucially influences decision making in UGVs. To increase the processing speed of environment information analysis, we develop a CPU-GPU hybrid system of automatic environment perception and 3D terrain reconstruction based on the integration of multiple sensors. The system consists of three functional modules, namely, multi-sensor data collection and pre-processing, environment perception, and 3D reconstruction. To integrate individual datasets collected from different sensors, the pre-processing function registers the sensed LiDAR (light detection and ranging) point clouds, video sequences, and motion information into a global terrain model after filtering redundant and noise data according to the redundancy removal principle. In the environment perception module, the registered discrete points are clustered into ground surface and individual objects by using a ground segmentation method and a connected component labeling algorithm. The estimated ground surface and non-ground objects indicate the terrain to be traversed and obstacles in the environment, thus creating driving awareness. The 3D reconstruction module calibrates the projection matrix between the mounted LiDAR and cameras to map the local point clouds onto the captured video images. Texture meshes and color particle models are used to reconstruct the ground surface and objects of the 3D terrain model, respectively. To accelerate the proposed system, we apply the GPU parallel computation method to implement the applied computer graphics and image processing algorithms in parallel.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.224-239
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• 2023

C-ITS (Cooperative-Intelligent Transportation System) refers to user safety-oriented technology and systems that provide forward traffic situation information based on a two-way wireless communication technology between vehicles or between vehicles and infrastructure. Since the Daejeon-Sejong pilot project in 2016, the C-ITS infrastructure has been installed at various locations to provide C-ITS safety services through highway and local government demonstration projects. In this study, a methodology was developed to verify the effectiveness of the warning information using individual vehicle data collected through the Gwangju Metropolitan City C-ITS demonstration project. The analysis of the effectiveness was largely divided into driving behavior impact analysis and environmental analysis. Compliance analysis and driving safety evaluation were performed for the driving impact analysis. In addition, to supplement the inadequate collection of Probe Vehicle Data (PVD) collected during the C-ITS demonstration project, Digital Tacho Graph ( DTG ) data was additionally collected and used for effect analysis. The results of the compliance analysis showed that drivers displayed reduced driving behavior in response to warning information based on a sufficient number of valid samples. Also, the results of calculating and analyzing driving safety indicators, such as jerk and acceleration noise, revealed that driving safety was improved due to the provision of warning information.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.21-27
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• 2023

This paper discusses a deep learning-based road surface analysis system that collects data by installing vibration sensors on the 4-axis wheel bearings of a vehicle, analyzes the data, and appropriately classifies the characteristics of the current driving road surface for use in the vehicle's control system. The data used for road surface analysis is real-time large-capacity data, with 48K samples per second, and the A2B protocol, which is used for large-capacity real-time data communication in modern vehicles, was used to collect the data. CAN and CAN-FD commonly used in vehicle communication, are unable to perform real-time road surface analysis due to bandwidth limitations. By using A2B communication, data was collected at a maximum bandwidth for real-time analysis, requiring a minimum of 24K samples/sec for evaluation. Based on the data collected for real-time analysis, performance was assessed using deep learning models such as LSTM, GRU, and RNN. The results showed similar road surface classification performance across all models. It was also observed that the quality of data used during the training process had an impact on the performance of each model.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.29-34
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• 2012

Nowadays, the problem of ETCS terminal in becoming popular gradually is that there is no services except for ETC. Therefore, we need new system that provide many type of additional services at one-terminal. In this paper, we study the additory function of ETCS terminal to afford many type of the vehicle administration beside collection and provider of traffic information. We descrived the method of Eco-driving function beside to save fuel signing instant and mean fuel-efficiency, measurement of section fuel-efficiency on OLED and then brings out the best driving habit in people and to prevent dangerous at the wheel as diagnosing engine oil, cooling water, fan belt, the point of changing consumables, diagnoses to an overheated engine, charges on generator through ECU. The multi-services terminal consist of the vehicle diagnosis module base on OBD-II and ETCS terminal.

• Journal of Navigation and Port Research
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• v.28 no.10 s.96
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• pp.881-889
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• 2004

Using the ETC Service, it is now possible to charge a vehicle for driving pass a specific toll booth electronically, without the vehicle even having to slow down. The smart card and card reader used to collect tolls electronically have a serious problem which it dose not have a standard for the ETC system. In this paper, we suggest the ETC system using mobile phone to collect tolls efficiently instead of existing system which is consist of a Interface Module to connect between a mobile phone and OEE, a mobile phone to send the information of tollgate fees and OEE to communication with RSE of roadway in the vehicle. This primary focus of this system is the IM functions and protocol to assist of the existing mobile phone and OBE.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.1
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• pp.47-53
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• 2011

To enable the efficient operation of ITS, it is necessary to collect location data for vehicles on the road. In the case of futuristic transportation systems like ubiquitous transportation and smart highway, a method of data collection that is advanced enough to incorporate road lane recognition is required. To meet this requirement, technology based on radio frequency identification (RFID) has been researched. However, RFID may fail to yield accurate location information during high-speed driving because of the time required for communication between the tag and the reader. Moreover, installing tags across all roads necessarily incurs an enormous cost. One cost-saving alternative currently being researched is to utilize GNSS (global navigation satellite system) carrierbased location information where available. For lane recognition using GNSS, a precise digital map for determining vehicle position by lane is needed in addition to the carrier-based GNSS location data. A "precise digital map" is a map containing the location information of each road lane to enable lane recognition. At present, precise digital maps are being created for lane recognition experiments by measuring the lanes in the test area. However, such work is being carried out through comparison with vehicle driving information, without definitions being established for detailed performance specifications. Therefore, this study analyzes the performance requirements of a precise digital map capable of lane recognition based on the accuracy of GNSS location information and the accuracy of the precise digital map. To analyze the performance of the precise digital map, simulations are carried out. The results show that to have high performance of this system, we need under 0.5m accuracy of the precise digital map.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.1
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• pp.157-167
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• 2020

The big data and artificial intelligence technology, which has provided the foundation for the recent 4th industrial revolution, has become a major driving force in business innovation across industries. In the field of information security, we are trying to develop and improve an intelligent security system by applying these techniques to large-scale log data, which has been difficult to find effective utilization methods before. The quality of security log big data, which is the basis of information security AI learning, is an important input factor that determines the performance of intelligent security system. However, the difference and complexity of log data by various product has a problem that requires excessive time and effort in preprocessing big data with poor data quality. In this study, we research and analyze the cases related to log data collection of various firewall. By proposing firewall log data collection format standard, we hope to contribute to the development of intelligent security systems based on security log big data.