• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.75-80
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• 2005

In this paper, a 3-dimensional analysis of magnetic road and a position sensing system for an autonomous vehicle system is described. Especially, a new position sensing system, end of the important component of an autonomous vehicle, is proposed. In a magnet based autonomous vehicle system, to sense the vehicle position, the sensor measures the field of magnetic road. The field depends on the sensor position of the vehicle on the magnetic road. As the rotation between the magnetic field and the sensor position is highly complex, it is difficult that the relation is stored in memory. Thus, a neural network is used to learn the mapping from th field to the position. The autonomous vehicle system with the proposed position sensing system is tested in experimental setup.

• Journal of Auto-vehicle Safety Association
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• v.16 no.1
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• pp.35-41
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• 2024

In order to verify autonomous driving scenarios and safety, a lot of driving and accident data is needed, so various organizations are conducting classification and analysis of traffic accident types. In this study, it was determined that accident recording devices such as EDR (Event Data Recorder) and DSSAD (Data Storage System for Automated Driving) would become an objective standard for analyzing the causes of autonomous vehicle accidents, and traffic accidents that occurred from 2015 to 2020 were analyzed. Using the database system of IGLAD (Initiative for the Global Harmonization of Accident Data), approximately 360 accident data of EDR-equipped vehicles were classified and their characteristics were analyzed by comparing them with accident types of ADAS (Advanced Driver Assistance System)-equipped vehicles. It will be used to develop autonomous vehicle accident investigation guidelines in the future.

• Annual Conference of KIPS
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• 2023.05a
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• pp.290-291
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• 2023

모빌리티 기술의 발전으로 자율주행 및 센서 데이터 처리를 위한 신뢰할 수 있는 고성능 저장 시스템의 수요가 증가하고 있다. SSD(Solid State Drive)는 빠른 데이터 처리 속도의 장점뿐만 아니라 외부 충격에 강한 내구성과 저전력의 특징 때문에 모빌리티 환경의 저장 시스템으로 사용되고 있다. 그러나 고온에 장시간 노출되면 NAND 플래시 메모리 소자에 손상이 발생할 수 있는 특성 때문에 모빌리티 내부 SSD의 온도를 관리해야 한다. 본 논문에서는 SSD의 외부 및 내부의 온도를 측정하여 저장장치가 고온에 장시간 노출되지 않도록 쿨링 시스템을 설계하고 실험을 통하여 적정 온도를 유지할 수 있는 최적화 방법을 제안한다. 또한 실험을 통해 쿨링 시스템이 SSD의 내부와 외부에 미치는 온도 변화를 측정하여 제안하는 시스템의 효과를 증명한다.

• The Journal of Bigdata
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• v.4 no.2
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• pp.207-220
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• 2019

Recent developments in information and communication technology has enabled the deployment of sensor based data to provide real-time services. In Korea, The Korea Transportation Safety Authority is collecting driving information of all commercial vehicles through a fitted digital tachograph (DTG). This information gathered using DTG can be utilized in various ways in the field of transportation. Notably in autonomous driving, the real-time analysis of this information can be used to prevent or respond to dangerous driving behavior. However, there is a limit to processing a large amount of data at a level suitable for real-time services using a traditional database system. In particular, due to a such technical problem, the processing of large quantity of traffic big data for real-time commercial vehicle operation information analysis has never been attempted in Korea. In order to solve this problem, this study optimized the new database server system and confirmed that a real-time service is possible. It is expected that the constructed database system will be used to secure base data needed to establish digital twin and autonomous driving environments.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.8
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• pp.327-342
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• 2017

In this paper, we introduce an integrated processing system of smart sensor data for IoT service which collects sensor data and efficiently processes it. Based on the technology of collecting sensor data to the development of the IoT field and sending it to the network · Based on the receiving technology, as various projects such as smart homes, autonomous running vehicles progress, the sensor data is processed and effectively An autonomous control system to utilize has been a problem. However, since the data type of the sensor for monitoring the autonomous control system varies according to the domain, a sensor data integration processing system applying the autonomous control system to various different domains is necessary. Therefore, in this paper, we introduce the Smart Sensor Data Integrated Processing System, apply it and use the window as a reference to process internal and external sensor data 1) receiveData, 2) parseData, 3) addToDatabase 3 With the process of the stage, we provide and implement the automatic window opening / closing system "Smart Window" which ventilates to create a comfortable indoor environment by autonomous control system. As a result, standby information is collected and monitored, and machine learning for performing statistical analysis and better autonomous control based on the stored data is made possible.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.11
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• pp.319-328
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• 2023

Unlike cloud computing, edge computing technology analyzes and judges data close to devices and users, providing advantages such as real-time service, sensitive data protection, and reduced network traffic. EdgeX Foundry, a representative open source of edge computing platforms, is an open source-based edge middleware platform that provides services between various devices and IT systems in the real world. EdgeX Foundry provides a service for handling camera devices, along with a service for handling existing sensed data, which only supports simple streaming and camera device management and does not store or process image data obtained from the device inside EdgeX. This paper presents a technique that can store and process image data inside EdgeX by applying some of the services provided by EdgeX Foundry. Based on the proposed technique, a service pipeline for object detection services used core in the field of autonomous driving was created for experiments and performance evaluation, and then compared and analyzed with existing methods.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.169-176
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• 2022

With the continuous development of technologies related to 5G, artificial intelligence, and autonomous vehicle systems, standards and services for V2X and C-ITS environments are being studied a lot. BSM (basic safety message) was adopted as a standard for exchanging data between vehicles based on data collected and generated by vehicle systems in a V2V environment. In this paper, we propose a framework that can safely store BSM messages and effectively check the stored messages using Event-Sourcing and CQRS patterns. The proposed framework can securely store and manage BSM messages using hash functions. And it has the advantage of being able to check the stored BSM data in real time based on the time series and to reproduce the state.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.32-48
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• 2022

This study presented a spatial data serialization technique that can efficiently store and transmit large amounts of spatial data for precision road maps was designed and implemented. For efficient serialization, a binary spatial data structure is defined, and a coordinate value encoding technique without loss of information is designed using the Zigzag-Z-order curve. The spatial data serialization technique designed for precision road maps was tested, and the data size and encoding/decoding speed after encoding were compared with Protocol buffer and Geobuff. As a result, it was confirmed that the designed serialization method was excellent in data weight reduction performance and encoding speed. However, the decoding speed was inferior to other serialization techniques in linestring and polygon type spatial data. Through this study, it was confirmed that spatial data can be efficiently encoded, stored, and transmitted using binary serialization techniques.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.587-598
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• 2021

This study aims to develop a multi-camera based MMS (Mobile Mapping System) technology for building a HD (High Definition) map for autonomous driving and for quick update. To replace expensive lidar sensors and reduce long processing times, we intend to develop a low-cost and efficient MMS by applying multiple cameras and real-time data pre-processing. To this end, multi-camera storage technology development, multi-camera time synchronization technology development, and MMS prototype development were performed. We developed a storage module for real-time JPG compression of high-speed images acquired from multiple cameras, and developed an event signal and GNSS (Global Navigation Satellite System) time server-based synchronization method to record the exposure time multiple images taken in real time. And based on the requirements of each sector, MMS was designed and prototypes were produced. Finally, to verify the performance of the manufactured multi-camera-based MMS, data were acquired from an actual 1,000 km road and quantitative evaluation was performed. As a result of the evaluation, the time synchronization performance was less than 1/1000 second, and the position accuracy of the point cloud obtained through SFM (Structure from Motion) image processing was around 5 cm. Through the evaluation results, it was found that the multi-camera based MMS technology developed in this study showed the performance that satisfies the criteria for building a HD map.