• Proceedings of the IEEK Conference
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• 2004.06b
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• pp.407-410
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• 2004

This paper describes an embedded system to put a SoC actuator IP in motion and linux drivers. The If that a embedded linux among embedded OS is ported is implemented as linux driver. The actuator IP is controlled by application programming. To make users use this easily, a QT is ported on the system. Application program can operate the actuator IP device driver on TFT LCD.

• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.3
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• pp.161-168
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• 1998

This paper presents the on-vehicle information system that displays the states of the vehicle in brief words instead of symbols. Main functions of this system include a system check function, trip function, warning function, and clock function. With this system, a driver can obtain all sorts of useful information related to various conditions of the vehicle, and if any problem arises in the vehicle, he can recognize it by the displayed words with a warning sound. Also, this system is very helpful for safety driving because it displays whatever a driver wants to have concerning trip information. By experimental test and driving test, the development system shows good results for each function.

• The Transactions of the Korea Information Processing Society
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• v.2 no.6
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• pp.815-822
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• 1995

In the conventional UNIX system, the all device driver realized in the kern el. Hence, whenever we want to add a new device driver or change the existin g device driver, the modification of kernel is unavoidable. Generally, it is very difficult to modify the kernel codes.As a method of overcoming this difficulty, a TTY device driver model of user-level is presented in this paper. The basic concept of this model is providing a dynamic reconfiguration of TTY device driver by realizing a user-level server process for TTY device driver. In order to verify the proper y of this model, a prototype of TTY device driver has been realized in the SunOS and Linux environment and evaluated its performance.

• Journal of the Ergonomics Society of Korea
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• v.29 no.1
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• pp.17-24
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• 2010

There has been recent interest in intelligent vehicle technologies, such as advanced driver assistance systems (ADASs) or in-vehicle information systems (IVISs) that offer a significant enhancement of safety and convenience to drivers and passengers. However, unsuitable design of HMI (Human Machine Interface) must increase driver distraction and workload, which in turn increase the chance of traffic accidents. Distraction in particular often occurs under a heavy driving workload due to multitasking with various electronic devices like a cell phone or a navigation system while driving. According to the 2005 road traffic accidents in Korea report published by the ROad Traffic Authority (ROTA), more than 60% of the traffic accidents are related to driver error caused by distraction. This paper suggests the structure of vehicle environment for real-time driving behavior monitoring system while driving which is can be used the driver workload management systems (DWMS). On-road experiment results showed the feasibility of the suggested vehicle environment for driving behavior monitoring system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.2
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• pp.134-139
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• 2021

Currently, the autonomous vehicle market is commercializing a level 3 autonomous vehicle, but it still requires the attention of the driver. After the level 3 autonomous driving, the most notable aspect of level 4 autonomous vehicles is vehicle stability. This is because, unlike Level 3, autonomous vehicles after level 4 must perform autonomous driving, including the driver's carelessness. Therefore, in this paper, we propose the Emergency-notification and Driver-response Confirmation System(EDCS) for an autonomousvehicle safety that notifies the driver of an emergency situation and recognizes the driver's reaction in a situation where the driver is careless. The EDCS uses the emergency situation delivery module to make the emergency situation to text and transmits it to the driver by voice, and the driver response confirmation module recognizes the driver's reaction to the emergency situation and gives the driver permission Decide whether to pass. As a result of the experiment, the HMM of the emergency delivery module learned speech at 25% faster than RNN and 42.86% faster than LSTM. The Tacotron2 of the driver's response confirmation module converted text to speech about 20ms faster than deep voice and 50ms faster than deep mind. Therefore, the emergency notification and driver response confirmation system can efficiently learn the neural network model and check the driver's response in real time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.9
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• pp.2153-2159
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• 2013

In order to drive a vehicle safely, driver needs to check status of the car. Many moderns are having trouble to spare time to visit auto mechanic and have car mechanics to check their car other than their office hours. If the car status cannot be inspected regularly, it is likely to cause a big accident threatening the surroundings as well as driver's life. Inspection tool and system help driver to check their own vehicle status personally are required for preventing it. In this paper, it designed and realized system that records driving information based on changing data of vehicle (location and automotive internal data) and allows driver can check the vehicle status easily and further, driver can share the driving information with repair shop via the Internet to receive detailed inspection service for car status.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.859-864
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• 2022

Drowsy driving, one of the biggest causes of traffic accidents every year, is accompanied by various factors. As a general method to check whether or not there is drowsiness, a method of identifying a driver's expression and driving pattern, and a method of analyzing bio-signals are being studied. This paper proposes a driver fatigue detection system using deep learning technology and bio-signal measurement technology. As the first step in the proposed method, deep learning is used to detect the driver's eye shape, yawning presence, and body movement to detect drowsiness. In the second stage, it was designed to increase the accuracy of the system by identifying the driver's fatigue state using the pulse wave signal and body temperature. As a result of the experiment, it was possible to reliably determine the driver's drowsiness and fatigue in real-time images.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.257-263
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• 2021

Though many have studied choosing one of the alternative ways to reach a destination, the factors such as average road speed, distance, and number of traffic signals, traffic congestion, safety, and services still presents an indisputable challenge. This paper proposes two approaches: Appropriate membership function and ambiguous rule-based approach. It aims to tackle the route choice problem faced by almost all drivers in any city. It indirectly helps in tackling the problem of traffic congestion. The proposed approach considers the preference of each driver which is determined in a flexible way like a human and stored in the driver profile. These preferences relate to the criteria for evaluating each candidate route, considering the average speed, distance, safety, and services available. An illustrative case study demonstrates the added value of the proposed approach compared to some other approaches.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.5
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• pp.1303-1310
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• 2010

Recently, researches related with automative mechanism have been widely studied to increase the driver's safety by continuously monitoring the driver's health condition to prevent driver's drowsiness. This paper describes the design of wearable chest belt for ECG and reflectance pulse oximetry for SpO2 sensors based on wireless sensor network to monitor the driver's healthcare status. ECG, SpO2 and heart rate signals can be transmitted via wireless sensor node to base station connected to the server. Intelligent monitoring system is designed at the server to analyze the SpO2 and ECG signals. HRV (Heart Rate Variability) signals can be obtained by processing the ECG and PPG signals. HRV signals are further analyzed based on time and frequency domain to determine the driver's drowsiness status.

• The Transactions of the Korea Information Processing Society
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• v.6 no.7
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• pp.1970-1979
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• 1999

This paper proposes an AVI system which recognizes the license plate and the driver's face simultaneously using passive AVI techniques. For this, firstly, the pro-processing algorithm independent of the environment is proposed and region extraction of the car number plate and the driver's face is described. Secondly, characters are separated and recognition parameters are extracted from target regions. Thirdly, template matching of car number plate is performed and the fuzzy relation matrix of driver face is made for the final recognition processes. The merits of the proposed system are following : Pre-processing is accomplished regardless of the environment. The application areas of conventional AVI system can be expanded in the content that the driver's face is also recognized in the proposed system compared with only the number plast is recognized in the existing systems.