• Journal of Auto-vehicle Safety Association
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• v.15 no.4
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• pp.65-70
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• 2023

In the paper, we propose a design method and process of a hybrid V2X communication module that combines WAVE communication, LTE-V2X communication, and legacy LTE communication in evaluating vehicle V2X electromagnetic compatibility. C-ITS is suitable for safety service applications due to its low latency, and legacy LTE is suitable for applications such as traffic information and infotainment due to its high latency and high capacity. In order to evaluate the V2X communication system, the evaluation equipment must have communication performance of the same level or higher. The main design contents presented in this paper will be applied to the implementation of a hybrid V2X communication module for electromagnetic compatibility evaluation.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.7-13
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• 2020

We describes V2X technology, a connectivity-based recognition technology that is attracting attention as a key technology for implementing autonomous driving technology, and autonomous communication modules that implement ADAS technology, a sensor-based recognition technology. It also explains the trends in V2X technology standardization centered on IEEE 802.11p, which is a WAVE technology standard based on Wi-Fi/DSRC. Finally, we will discuss the market growth trend of V2X communication modules in the United States, the leading V2X technology module, and the development of technology development trends of major domestic and international companies that are leading the global technology market related to V2X communication modules. V2X and ADAS technologies will be the biggest influence on automotive purchasing decisions. In recent years, V2I mandates have been promoted beyond V2V, mainly in developed countries such as the United States. The related industry needs to focus on the development of information transmission network technology that can support high frequency high efficiency(transmission rate) and sophisticated positioning accuracy beyond conventional vehicle communication.

• Journal of Advanced Navigation Technology
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• v.22 no.3
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• pp.213-219
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• 2018

In this paper, we propose a design method and process for hardware and software of hybrid V2X communication module that supports both C-ITS communication protocol designed for vehicle environment and Legacy LTE communication technology. C-ITS is suitable for safety service applications due to its low latency characteristics, and Legacy LTE is a technology suitable for non-safety applications such as traffic information and infotainment due to high latency and high capacity. The hybrid V2X communication module supports multiple communication technologies of WAVE and LTE, in which WAVE supports multiple channels, so that it is designed to transmit road information such as LDM and positioning correction information to an autonomous vehicle in real time. The main design results presented in this paper will be applied to the implementation of future hybrid V2X communication terminals for vehicles.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.395-398
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• 2018

we propose a design method and process for hardware and software of hybrid V2X communication systems that support both C-ITS communication protocol and Legacy LTE communication technology. The hybrid V2X communication systems support multiple communication technologies of WAVE and LTE, in which WAVE supports multiple channels, so that it is designed to transmit road information such as LDM and positioning correction information to an autonomous vehicle in real time.

• Journal of the Korean Vacuum Society
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• v.20 no.6
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• pp.409-415
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• 2011

The method to improve the detection sensitivity of Hand-held XRF (X-Ray Fluorescence) device currently being developed is discussed. To minimize the loss of the intensity due to atmospheric gas molecules, the vacuum module, which can be filled with atmospheric or He gas, between the sample and the detector was installed. And the change of the detection sensitivity was measured in a vacuum and in the He gas-filled state. As a result, the following three important results were obtained; Firstly, XRF intensity was increased 2~4 times in the low energy range (3~4 keV). It is a very important result because the enhancement of the detection sensitivity means shortening of the detection time in Hand-held XRF device. Secondly, the possibility of detection of the elements less than 3 keV in emission energy was confirmed. Thirdly, the absorption by atmospheric gas molecules can be minimized without vacuum- sealed vessel in Hand-held XRF device, if the vacuum module filled with He gas is used. We concluded that all of three results are very meaningful in the development of a Hand-held XRF device.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5842-5861
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• 2019

A current autonomous vehicle determines its driving strategy by considering only external factors (Pedestrians, road conditions, etc.) without considering the interior condition of the vehicle. To solve the problem, this paper proposes "An Optimal Driving Support Strategy(ODSS) based on an Genetic Algorithm for Autonomous Vehicles" which determines the optimal strategy of an autonomous vehicle by analyzing not only the external factors, but also the internal factors of the vehicle(consumable conditions, RPM levels etc.). The proposed ODSS consists of 4 modules. The first module is a Data Communication Module (DCM) which converts CAN, FlexRay, and HSCAN messages of vehicles into WAVE messages and sends the converted messages to the Cloud and receives the analyzed result from the Cloud using V2X. The second module is a Data Management Module (DMM) that classifies the converted WAVE messages and stores the classified messages in a road state table, a sensor message table, and a vehicle state table. The third module is a Data Analysis Module (DAM) which learns a genetic algorithm using sensor data from vehicles stored in the cloud and determines the optimal driving strategy of an autonomous vehicle. The fourth module is a Data Visualization Module (DVM) which displays the optimal driving strategy and the current driving conditions on a vehicle monitor. This paper compared the DCM with existing vehicle gateways and the DAM with the MLP and RF neural network models to validate the ODSS. In the experiment, the DCM improved a loss rate approximately by 5%, compared with existing vehicle gateways. In addition, because the DAM improved computation time by 40% and 20% separately, compared with the MLP and RF, it determined RPM, speed, steering angle and lane changes faster than them.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.2
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• pp.133-139
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• 2017

Vehicles have increasingly evolved and become intelligent with convergence of information and communications technologies (ICT). Vehicle communications (VC) has become one of the major necessities for intelligent vehicles. However, VC suffers from serious security problems that hinder its commercialization. Hence, the IEEE 1609 Wireless Access Vehicular Environment (WAVE) protocol defines a security service for VC. This service includes Advanced Encryption Standard-Counter with CBC-MAC (AES-CCM) for data encryption in VC. A high-speed AES-CCM crypto module is necessary, because VC requires a fast communication rate between vehicles. In this study, we propose and implement an efficient AES-CCM hardware architecture for high-speed VC. First, we propose a 32-bit substitution table (S_Box) to reduce the AES module latency. Second, we employ key box register files to save key expansion results. Third, we save the input and processed data to internal register files for secure encryption and to secure data from external attacks. Finally, we design a parallel architecture for both cipher block chaining message authentication code (CBC-MAC) and the counter module in AES-CCM to improve performance. For implementation of the field programmable gate array (FPGA) hardware, we use a Xilinx Virtex-5 FPGA chip. The entire operation of the AES-CCM module is validated by timing simulations in Xilinx ISE at a speed of 166.2 MHz.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.238-241
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• 2019

In this paper, a "Vehicle Analysis System(VAS) using cloud and data mining" is proposed that store all the sensor data measured in the vehicle in the cloud, analyze the stored data using the classification model, and provide the analyzed data in real time to the driver's display. The VAS consists of two modules. First, Sensor Data Communication Module(SDCM) stores the sensor data measured in the vehicle in a table of the cloud server and transfers the stored data to the analysis module. Second, Sensor Data Analysis Module(SDAM) analyzes the received data using the genetic algorithm and provides analyzed result to the driver in real time. The VAS stores sensor data collected in the vehicle in the cloud server without accumulating it in the vehicle, and stored data is analyzed in the cloud server, so that the sensor data can be quickly and efficiently managed without overloading the vehicle. In addition, the information desired by the driver can be visualized on the display, thereby increasing the stability of the autonomous vehicle.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.152-164
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• 2015

A rapid development of semiconductors, sensors and mobile network technologies has enable that the embedded device includes high sensitivity sensors, wireless communication modules and a video processing module for vehicular environment, and many researchers have been actively studying the smart car technology combined on the high performance embedded devices. The vehicle is increased as the development of society, and the risk of accidents is increasing gradually. Thus, the advanced driver assistance system providing the vehicular status and the surrounding environment of the vehicle to the driver using various sensor data is actively studied. In this paper, we design and implement the smart vehicular camera device providing the V2X communication and gathering environment information. And we studied the method to create the metadata from a received video data and sensor data using video analysis algorithm. In addition, we invent S-ROI, D-ROI methods that set a region of interest in a video frame to improve calculation performance. We performed the performance evaluation for two ROI methods. As the result, we confirmed the video processing speed that S-ROI is 3.0 times and D-ROI is 4.8 times better than a full frame analysis.