• Journal of the Korea Society of Computer and Information
• /
• v.24 no.5
• /
• pp.67-72
• /
• 2019

The self-driving cars identify appropriate navigation paths and obstacles to arrive at their destinations without human control. The autonomous cars are capable of sensing driving environments to improve driver and pedestrian safety by sharing with neighbor traffic infrastructure. In this paper, we have focused on pedestrian protection and have designed an improved localization algorithm to track mobile users on roads by interacting with smart traffic lights in vehicle environments. We developed smart traffic lights with the RSSI sensor and built the proposed method by improving the Kalman filter algorithm to localize mobile users accurately. We successfully evaluated the proposed algorithm to improve the mobile user localization with deployed five smart traffic lights.

• The Journal of the Convergence on Culture Technology
• /
• v.3 no.2
• /
• pp.49-54
• /
• 2017

In Korea, partial self-driving feature is added on Genesis G80, Tivoli 2017, and others, and full implementation is under evaluation. Tesla already completed test for full self-driving car, Tesla Model 'X'. Further adoption of self-driving car in market will bring benefits to the elderly and disabled, meanwhile traffic accident will be decreased. However, related regulations for traffic accident with autonomous car including ethical responsibility is not fully established yet. In addition, security and privacy issue of self-driving cars should be improved as well. In this paper, domestic researches and analysis status on autonomous car will be summarized, and proper activation model will be proposed for the previously described issues.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2002.11a
• /
• pp.128-131
• /
• 2002

In this paper, we used the V-Q Lissajous‘ figure for studying on the plasma discharge characteristics of the 42 inches AC-PDP. From the V-Q Lissajous‘ figure, we could observe exactly the driving conditions that the self-erasing discharge takes place. At the time, the total wall charges lessened by self-erasing discharge was calculated quantitatively. Beside of the just observation of self-erasing discharge and calculation of the charges lessened, we could find out the optimum driving conditions for inducing the maximum wall charges accumulated on the dielectric layer with measuring the Wall voltage from the V-Q Lissajous' figure.

• Journal of the Semiconductor & Display Technology
• /
• v.13 no.1
• /
• pp.13-17
• /
• 2014

Since the semiconductor manufacturing requires the silicon wafers with extraordinary degree of surface flatness, the surface polishing of wafers from ingot cutting is an important process for deciding surface quality of wafers. The present study introduces the development of wafer polishing equipment and, especially, the wafer polishing head that employs the forced self-driving of installed silicon wafer as well as the wax wafer mounting technique. A series of wafer polishing tests have been carried out to investigate the effects of self-driving function in wafer polishing head. The test results for wafer planarization showed that the LLS counts and SBIR of polished wafer surfaces were generally improved by adopting the self-driven polishing head in wafer polishing stations.

• Journal of Internet Computing and Services
• /
• v.24 no.1
• /
• pp.39-47
• /
• 2023

The development of autonomous driving and Advanced Driver Assistance System (ADAS) technology has grown rapidly in recent years. As most traffic accidents occur due to human error, self-driving vehicles can drastically reduce the number of accidents and crashes that occur on the roads today. Obviously, technical advancements in autonomous driving can lead to improved public driving safety. However, due to the current limitations in technology and lack of public trust in self-driving cars (and drones), the actual use of Autonomous Vehicles (AVs) is still significantly low. According to prior studies, people's acceptance of an AV is mainly determined by trust. It is proven that people still feel much more comfortable in personalized ADAS, designed with the way people drive. Based on such needs, a new attempt for a customized ADAS considering each driver's driving style is proposed in this paper. Each driver's behavior is divided into two categories: assertive and defensive. In this paper, a novel customized ADAS algorithm with high classification accuracy is designed, which divides each driver based on their driving style. Each driver's driving data is collected and simulated using CARLA, which is an open-source autonomous driving simulator. In addition, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) machine learning algorithms are used to optimize the ADAS parameters. The proposed scheme results in a high classification accuracy of time series driving data. Furthermore, among the vast amount of CARLA-based feature data extracted from the drivers, distinguishable driving features are collected selectively using Support Vector Machine (SVM) technology by comparing the amount of influence on the classification of the two categories. Therefore, by extracting distinguishable features and eliminating outliers using SVM, the classification accuracy is significantly improved. Based on this classification, the ADAS sensors can be made more sensitive for the case of assertive drivers, enabling more advanced driving safety support. The proposed technology of this paper is especially important because currently, the state-of-the-art level of autonomous driving is at level 3 (based on the SAE International driving automation standards), which requires advanced functions that can assist drivers using ADAS technology.

• Korean Journal of Culture and Social Issue
• /
• v.13 no.3
• /
• pp.111-125
• /
• 2007

This study focused on novice drivers. Novice drivers get involved in more traffic accidents than the other drivers because of less driving experience. The aim of this study is to investigate the relationship between driving confidence levels and speeding, drunken driving, and traffic accidents. 192 drivers responded driving confidence levels questionnaire and driving experience items. 'Circumstance Insensibility', 'Unsafe Driving', 'Incautious Driving', and 'Self-efficacy of Driving' had significant relations with speeding in novice divers group. Especially, 'Circumstance Insensibility' showed a significant relation with speeding, drunken driving and traffic accidents. In the result of path analysis, driving confidence levels explained 22% of the speeding, 12% of the drunken driving and 21% of the traffic accidents in novice drivers group. 'Circumstance Insensibility' was most effective for traffic accidents of novice drivers. We verified that 'Self-efficacy of Driving' affects on traffic accidents via speeding.

• Proceedings of the IEEK Conference
• /
• 2000.06b
• /
• pp.48-51
• /
• 2000

We proposed the new driving waveform which has changed the waveform of sustain division to improve luminous efficiency in plasma display panel. This sustain waveform is to add the ramp to the rectangular waveform, resulting in self-erasing discharge in the falling edge region. The proposed waveform has improved the luminous efficiency of 30％ even in low driving frequency(25kHz), whereas the conventional driving waveform using the self-erasing discharge can improve the luminous efficiency only in high driving frequency( >150kHz). Front the results of this paper, we hope that the variety study on frequency and duty ratio, ramp waveform will increase the luminous efficiency.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.3
• /
• pp.861-864
• /
• 2024

The self-driving roller conveyor system, which transports target products by controlling multiple rollers with a motor, is a logistics system suitable for branching and joining logistics and controlling the alignment of target products, and its utilization is increasing, especially in the food manufacturing process. In this paper, we build a simulation environment using Unity software based on 3D graphic modeling of a self-driving roller conveyor system. In a situation where target products are supplied irregularly in terms of time, a method is proposed that can align products to maintain constant spacing by controlling the rollers. Simulation results show that effective alignment of products is possible by controlling the motor that drives the roller based on sensor data of the product position.

• The Journal of Korea Robotics Society
• /
• v.14 no.2
• /
• pp.122-130
• /
• 2019

Collecting a rich but meaningful training data plays a key role in machine learning and deep learning researches for a self-driving vehicle. This paper introduces a detailed overview of existing open-source simulators which could be used for training self-driving vehicles. After reviewing the simulators, we propose a new effective approach to make a synthetic autonomous vehicle simulation platform suitable for learning and training artificial intelligence algorithms. Specially, we develop a synthetic simulator with various realistic situations and weather conditions which make the autonomous shuttle to learn more realistic situations and handle some unexpected events. The virtual environment is the mimics of the activity of a genuine shuttle vehicle on a physical world. Instead of doing the whole experiment of training in the real physical world, scenarios in 3D virtual worlds are made to calculate the parameters and training the model. From the simulator, the user can obtain data for the various situation and utilize it for the training purpose. Flexible options are available to choose sensors, monitor the output and implement any autonomous driving algorithm. Finally, we verify the effectiveness of the developed simulator by implementing an end-to-end CNN algorithm for training a self-driving shuttle.

• Journal of Digital Convergence
• /
• v.19 no.12
• /
• pp.145-150
• /
• 2021

In order to continuously perform quarantine in public places, it is not easy to secure manpower, but using self-driving-based robots can solve problems caused by manpower. Self-driving-based quarantine robots can continuously prevent the spread of harmful viruses and diseases in public institutions and hospitals without additional manpower. The location of the autonomous driving function was estimated by applying the Pinnacle filter algorithm, and the UV sterilization system and chlorine dioxide injection system were applied for quarantine. The driving time is more than 3 hours and the position error is 0.5m.Soon, the stop-avoidance function was operated at 95% and the obstacle detection distance was 1.5 m, and the automatic charge recovery was charged by moving to the charging cradle at the remaining 10% of the battery capacity. As a result of quarantine with an unmanned quarantine system, UV sterilization is 99% and chlorine dioxide is sterilized more than 95%, which can contribute to reducing enormous social costs.