• Journal of rehabilitation welfare engineering & assistive technology
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• v.8 no.3
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• pp.151-160
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• 2014

In this study, the effect of the automotive haptic-seat technology which can transmit the driving information by the vibro-stimulus from the seat was investigated to overcome previous system's limitation relied on the visual and audial method and to help handicap driving. A prototype haptic seat cover with 30 coin-type motors and driver module were developed for this sake. In an experiment of seat vibration stimulation being performed under virtual driving situation by targeting the elderly aged over 65 years old, average score of test subjects for total vibration recognition was 3.5/4 points and recognition rate of 87.5% was represented. In addition, a result that all the test subjects totally recognized overspeed warning signal of 4 times was represented. As a result of statistical analysis for vibration recognition score by each group depending on TMT score, a significant difference was not found and a result that tactile function of which vibration is recognized even by the aged whose visual, perceptional function is declined showed an equal ability was obtained.. In this study it was shown that the seat vibration stimulus could be used to transfer the old drivers' information while driving.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.105-108
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• 2010

The vehicle navigation system is a representative driver supporting system that available to present searching and guiding path functions, have been increased for usability. Under competition situation because of following the spreaded navigation market, to meet customer's needs about new given services, there are need differentiated services increasing dramatically. Also now, dash board indicates various vehicle's status and driver can aware of that. However it is not easy to know where is abnormal essentially and there are no devices to give warning to driver. Therefore, It is difficult to preserve accidents because it can't deal with various abnormal functions immediately on driving. In this paper, we proposed vehicle diagnosis program within navigation that is available to manage and to make a diagnosis of vehicle. And this program conform OBD-II standard, so it can transmit diagnosis data from ECU to navigation system using Bluetooth wireless communication protocol. Thus this program give enhanced services to customer as well as multimedia and geometry information services.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.70-82
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• 2022

At the current stage of a semi-autonomous vehicle, there are situations in which the vehicle has to request take-over control to the driver quickly. However, current self-driving cars use only simple messages and warning sounds to notify drivers when handing over control, so they do not adequately convey considerations of individual characteristics or explanations of various emergent situations. This study investigated how visual and auditory information and the efficacy of drivers in self-driving cars can improve efficient take-over requests between the car and the driver. We found that there were significant differences in driver's cognitive load, reliability, safety, usability, and usefulness according to the combination of three visual and auditory information provided in the experiment of the take-over request situation. The results of this study are expected to help design self-driving vehicles that can communicate more safely and efficiently with drivers in urgent control transition situations.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.11
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• pp.537-542
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• 2017

Aggressive driving is a major cause of car accidents. Previous studies have mainly analyzed young driver's aggressive driving tendency, yet they were only done through pure clustering or classification technique of machine learning. However, since elderly people have different driving habits due to their fragile physical conditions, it is necessary to develop a new method such as enhancing the characteristics of driving data to properly analyze aggressive driving of elderly drivers. In this study, acceleration data collected from a smartphone of a driving vehicle is analyzed by a newly proposed ECA(Enhanced Clustering method for Acceleration data) technique, coupled with a conventional clustering technique (K-means Clustering, Expectation-maximization algorithm). ECA selects high-intensity data among the data of the cluster group detected through K-means and EM in all of the subjects' data and models the characteristic data through the scaled value. Using this method, the aggressive driving data of all youth and elderly experiment participants were collected, unlike the pure clustering method. We further found that the K-means clustering has higher detection efficiency than EM method. Also, the results of K-means clustering demonstrate that a young driver has a driving strength 1.29 times higher than that of an elderly driver. In conclusion, the proposed method of our research is able to detect aggressive driving maneuvers from data of the elderly having low operating intensity. The proposed method is able to construct a customized safe driving system for the elderly driver. In the future, it will be possible to detect abnormal driving conditions and to use the collected data for early warning to drivers.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1387-1394
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• 2017

As rate in an elderly population and expanding their range of activity rapidly increase, the demographics of the elderly population on a use of transportation also rise. Elderly pedestrians often find it difficult to react promptly to the traffic accidents as they are less perceptive of the dangers present under the situation. More than half of the elderly traffic accidents are elderly pedestrian accidents in road. Therefore, we design and implement smart safety hat for safety of elderly pedestrian. The smart safety hat binds stripe-shaped LED around a hat in order for a driver to perceive pedestrian easy and quickly. Features of smart safety hat include controlling the number of LEDs by using a light sensor and warning through vibration using a sound sensor. Also, we used Bluetooth to communicate with the smartphone to enable user customization of the light and numbers of LEDs.

• Proceedings of the KIPE Conference
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• 1996.06a
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• pp.43-46
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• 1996

The carborne Automatic Train Control(ATC) system keeps automatically optimum train speed code signals from wayside(track) circuit equipment. If there is no response for braking against the over speed detected, the driver will be noticed instantly by visual and audible warning signals. And then the ATC processes into braking mode for safe train operations to prevent any hazards by over speed limit. In this paper we are introduced the novel ATC system which has triple constructed structure made by 32 bit floating point DSP(ADSP21020-20) and process dealed with frequency domain and time domain for detecting signals. Owing to these reason it is no needed several band pass filters used in conventional ATC systems to detect the speed limit frequency. Also system's reliability and tolerance are incremented by adopt to 2 out of 3 logic to the outputs decision.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.110-113
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• 2003

Most traffic accidents are caused by drivers' carelessness and lack of information on the surrounding objects. In this paper we proposed a model of human intention recognition through case-base learning and to build up an experiment system. The system can help us recognize object's intention (e.g. turn left, turn right or straight) by using detected data about human's motion, speed of the car and the distance between the car and the intersection. Furthermore, we included an example using case-base learning in this paper to improve the precision of recognition as well as an example to explain the use of the system. PC can be used to predict the driving reaction beforehand and send a warning signal to the driver in time if there is any danger.

• Proceedings of the KIEE Conference
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• 2000.11a
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• pp.232-235
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• 2000

Design and experiments of a nondestructive system to inspect deterioration of ACSR-OC (ACSR Outdoor Cross-linked Polyethylene Insulated Wire usually used in HV overhead distribution lines presented in this paper. ACSR-OC conductor built to pollutants air for a long period would be easily progress to corrode so that it may lead to the reduction of the effective cross section area of conductors. A fault diagnosis system consisting of a solenoid sensor, a constant current source with RF frequency signal processing unit and a motor driver/controller designed and implemented. This instrument can dot the sensor output variation due to deterioration corrosion, continuously. As a result, it was shown such corrosion detector can readily be utilized estimating the diameter change due to deterioration overhead distribution lines and in giving an warning or inform before severe aged conductor lead to fail.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.10
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• pp.25-34
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• 1999

In this paper, an algorithm is presented to recognize lane and obstacles based on highway road image. The road images obtained by a video camera undergoes a pre-processing that includes filtering, edge detection, and identification of lanes. After this pre-processing, a part of image is grouped into 27 sub-windows and fed into a three-layer feed-forward neural network. The neural network is trained to indicate the road direction and the presence of absence of an obstacle. The proposed algorithm has been tested with the images different from the training images, and demonstrated its efficacy for recognizing lane and obstacles. Based on the test results, it can be said that the algorithm successfully combines the traditional image processing and the neural network principles towards a simpler and more efficient driver warning of assistance system

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.551-557
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• 2004

미래의 텔레매틱스(telematics)환경에서 차량항법과 관련된 주요 핵심 기술은 동적 경로 안내 이외에 차량 자체의 지능화를 통해 운전자에게 주행 중인 도로에서 급경사, 급커브 구간에 대한 정보를 사전에 경고함으로써 사고를 방지하는 운전자 보조 및 경고 시스템(driver assistance and warning system) 구현으로 전망되고 있다. 이와 같은 기술이 구현되기 위해서는 현재 차량항법용 수치도로지도에서 도로의 단순 위치정보만으로는 불가능하며 도로의 곡선구간에서 평면 곡선반경과 같은 도로의 선형설계요소에 대한 정보가 필수적이다. 따라서 본 연구에서는 현재 전국적으로 구축되어있는 1/1000 수치지도의 도로중심선을 이용하여 실제 도로의 평면 선형설계요소를 자동으로 추출하기 위한 알고리즘을 개발하였고 이를 GUI 환경의 프로그램으로 구현함으로써 기존 도로의 정확한 평면 선형정보를 경제적이면서 효율적으로 획득할 수 있게 되었다.