• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.6-6
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• 2000

By using the information obtained from the outputs of MR(MagnetoResistive) sensors for an Unmanned Vehicle Driving System, we develop an algorithm that decides the distance and direction between vehicle and the guideline which is made by the magnet. To improve the robust tracking properties of the closed loop system, we introduce H$\infty$ controller and its application for the Unmanned Vehicle Driving System.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 1998.11a
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• pp.92-98
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• 1998

In this paper various drive characteristics of a AC Servo Motor for EV(electric vehicle) and hybrid system proposed a countermeasure against air polution are presented. Since the transfer function of the plant is nonlinear and very complicated, there are difficultly in driving the system with real time. The performance of these experiments is confirmed by computer simulation results. The high performance and high accuracy of the driving system, Field oriented vector control system is proposed.

• Journal of Auto-vehicle Safety Association
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• v.13 no.1
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• pp.45-50
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• 2021

This study aimed to verify the criteria of the driver monitoring systems proposed by UNECE ACSF informal working group and the ministry of land, infrastructure, and transport of South Korea using driving behavior data. In order to verify the criteria, we investigated the safety regulations of driver monitoring systems in a conditional autonomous vehicle and found that the driver monitoring measures were related to eye blinks times, head movements, and eye closed duration. Thus, we took two different experimental data including real-world driving and simulator-based drowsy driving behaviors in previous studies. The real-world driving data were used for analyzing blink times and head movement intervals, and the drowsiness data were used for eye closed duration. In the drowsy driving study, 10 drivers drove approximately 37 km of a monotonous highway (about 22 min) twice. The results suggested that the appropriate duration of eyes continuously closed was 4 seconds. The results from real-world driving data were presented in the other paper - part 1.

• Journal of KSNVE
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• v.8 no.5
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• pp.929-935
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• 1998

Safety diagnosis of electric train driving system is performed using vibration signals of running electric train. Safety diagnosis is tried on the viewpoints of the appreciation of superannuation and the fault diagnosis of motor, reduction gear and bogie. The appreciation of superannuation is checked by the vibration levels of driving parts and the fault diagnosis is done by analyzing the frequencies of the vibration signals which are measured directly from a running electric train. The results shows that the vibration levels of each parts increase as the train gets older and each parts have their own frequency patterns of the vibration. Vibration propagation path is also investigated using calculated the coherence value between bogie and driving system. As the results, it is known that vibration signal can be utilized successfully for the safety diagnosis of the driving part of electric train.

• Journal of the Korea Society of Computer and Information
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• v.22 no.8
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• pp.33-39
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• 2017

In this paper, we propose a method which implements warning to drivers through real-time analysis of risky and unexpected driver and vehicle behavior using only a smartphone without using data from digital tachograph and vehicle internal sensors. We performed the evaluation of our system that demonstrates the effectiveness and usefulness of our method for risky and unexpected driver and vehicle behavior using three information such as vehicle speed, azimuth and GPS data which are acquired from a smartphone sensors. We confirmed the results and developed the smartphone application for validate and conducted simulation using actual driving data. This novel functionality of the smartphone application enhances drivers' situational awareness, increasing safety and effectiveness of driving.

• Proceedings of the IEEK Conference
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• 2000.06e
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• pp.65-68
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• 2000

We design a new driving system of 5" true color FED using current controlled PWM method. Further more, we successfully developed a 5" FED panel, which resolution is 320$\times$240(Color). When we design a 5" FED driving circuit, FED tips are modeled as R-C for circuit simulator of FED driving circuit. In Video data processing, parallel R, G, B input signals is processed independently, so duty ratio increase and no noise, high quality performance is achieved in display of 5" FED. The luminance is about 100cd/$m^2$, the anode power consumption Is 2.1W and total power of the driving system is 21.54W

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.51-56
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• 2022

This paper presents an Ground Segmentation algorithm to eliminate unnecessary Lidar Point Cloud Data (PCD) in an autonomous driving system. We consider Random Sample Consensus (Ransac) Algorithm to process lidar ground data. Ransac designates inlier and outlier to erase ground point cloud and classified PCD into two parts. Test results show removal of PCD from ground area by distinguishing inlier and outlier. The paper validates ground rejection algorithm in real time calculating the number of objects recognized by ground data compared to lidar raw data and ground segmented data based on the z-axis. Ground Segmentation is simulated by Robot Operating System (ROS) and an analysis of autonomous driving data is constructed by Matlab. The proposed algorithm can enhance performance of autonomous driving as misrecognizing circumstances are reduced.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.109-120
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• 2017

It is important to estimate objectively in the driving test. Especially, the driving test is examined by totally driving ability, rule observation and situational judgement. For this, a grading automation system for driving test was presented by using GPS, sensor data and equipment operation informations. This system is composed of vehicle mounted module, automatic grading terminal, data controller, data storage and processing server. The vehicle mounted module gathters sensor data in the car. The terminal performs automatic grading using the received sensor data according the driving test criterion. To overcome the misposition of vehicle in the map due to GPS error, we proposed the automatic grading system by map matching method, path deviation and return algorithm. In the experimental results, it was possible to grade automatically, display the right position of the car, and return to the right path under 10 seconds when the vehicle was out of the shadow region of the GPS. This system can be also applied to the driving education.

• 전자공학회논문지 IE
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• v.45 no.4
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• pp.33-41
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• 2008

Telematics system includes the "vehicle remote diagnosis technology", "driving pattern analysis technology" which are commercially attractive in the real life. To implement those technologies, we need vehicle signal interface, vehicle diagnosis interface, accelerometer/yaw-rate sensor interface, GPS data processing, driving pattern analysis, and CDMA data processing technique. Based on these technologies, we analyze the error existence by diagnosing the EMS(Engine Management System), TMS(Transmission Management System), ABS/TCS, A/BAG in real time. And we are checking about a driving pattern and management of the vehicle, which are sent to the information center through the wireless communication. These database results will make the efficient vehicle and driver management possible. We show the effectiveness of our results by field driving test after completing the H/W & S/W design and implementation for vehicle remote diagnosis and driving pattern analysis.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.2
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• pp.47-55
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• 2023

Recently, Sensor technologies are emerging to prevent traffic accidents and support safe driving in complex environments where human perception may be limited. The UWS is a technology that uses an ultrasonic sensor to detect objects at short distances. While it has the advantage of being simple to use, it also has the disadvantage of having a limited detection distance. The LDWS, on the other hand, is a technology that uses front image processing to detect lane departure and ensure the safety of the driving path. However, it may not be sufficient for determining the driving environment around the vehicle. To overcome these limitations, a system that utilizes FMCW radar is being used. The BSD radar system using FMCW continuously emits signals while driving, and the emitted signals bounce off nearby objects and return to the radar. The key technologies involved in designing the BSD radar system are tracking algorithms for detecting the surrounding situation of the vehicle. This paper presents a tracking algorithm for designing a BSD radar system, while explaining the principles of FMCW radar technology and signal types. Additionally, this paper presents the target tracking procedure and target filter to design an accurate tracking system and performance is verified through simulation.