• Journal of Auto-vehicle Safety Association
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• v.15 no.1
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• pp.63-68
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• 2023

A study on the need for a safety system using driver's biometric information, vehicle automatic emergency braking system, and the e-call system that in the event of an unexpected situation such as loss of driving ability due to sudden physical abnormality of elderly drivers and drivers with health problems, and the improvement of laws for the spread of this system were studied.

• IE interfaces
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• v.10 no.1
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• pp.145-154
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• 1997

In developing the HMI(Human-Machine Interface) evaluation system for the IVNS(In-Vehicle Navigation System), design guidelines and evaluation methods are the most crucial problems for its use and efficiency. As the part of this system, focused on the final product of the database, subjective mental workload assessment is seriously considered to evaluate the driver's own driving task using the IVNS. This paper suggests the methodology for the ergonomic assessment of the IVNS that corresponds to the subjective measurement of the driver's mental workload by rating his or her own driving task. For this approach, Revision of NASA-Task Load Index(RNASA-TLX) was developed which translated and revised the version of NASA-TLX that is generally accepted an efficient and powerful method for evaluating the in-vehicle information systems. To verify the RNASA-TLX, an experiment was conducted in a real road situation, because the result of the laboratory approach is uncertain and has the differences from the real road test.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.8
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• pp.1693-1700
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• 2012

Recently, the warning system to aid drivers for safe driving is being developed. The system estimates the distance between the driver's car and the car before it and informs him of safety distance. In this paper, we designed and implemented the collision warning system which detects the car in front on the actual road situation and measures the distance between the cars in order to detect the risk situation for collision and inform the driver of the risk of collision. First of all, using the forward-looking camera, it extracts the interest area corresponding to the road and the cars from the image photographed from the road. From the interest area, it extracts the object of the car in front through the analysis on the critical value of the shadow of the car in front and then alerts the driver about the risk of collision by calculating the distance from the car in front. Based on the results of detecting driving cars and measuring the distance between cars, the collision warning system was designed and realized. According to the result of applying it in the actual road situation and testing it, it showed very high accuracy; thus, it has been verified that it can cope with safe driving.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.66-69
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• 2010

Lately, vehicle combined vehicle and IT(Information Technology) for vehicle's safety and convenience. so, vehicles is equipped with many ECU(Electronic control unit). the ECU's transmit data about each electronic control unit with OBD(On-Board Diagnostics) Network and data about each multimedia with MOST(Media Oriented System Transport) Network. In this paper, Supplementing disadvantage of existing blackbox, Using MOST of in-vehicle multimedia network and OBD-II of in-vehicle control network, blackbox system obtain the vehicle's driving state data. so, blackbox system judge vehicle's driving state and provide vehicle's driving state information to driver. Blackbox system implement the features mentioned above. as a result, blackbox is going to be more accurate blackbox system.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.67 no.2
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• pp.75-81
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• 2018

In this paper for developing and implementing the car driver's front lane attention enhancement developed system using the car camera. The developed system automatically alarm the car driver when front cars make the dangerous situation. We use Raspberry Pi camera module V2 as car camera module, Raspberry Pi 3 board as hardware main board of implementing embedded system and develop the application library module which can be operated on the Raspberry situation. The application library module widely consist of two part, front car recognition part and dangerous situation distinguish part. Our developed system satisfy the performance test of the target system at the software test certification laboratory of TTA(Telecommunication Technology Association). We test four items as attentive car recognition ability at day and night, system performance, response time. We get the performance of developed system based on the four goal. The car driver's front lane attention enhancement system in this paper will be widely used at the ADAS(Advanced Driving Assistance System) because of the better performance and function.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.4
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• pp.88-94
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• 2004

Recently, vehicle simulators are widely used to evaluate driver's responses and driver assistance systems. It needs much effort to construct the virtual driving environment for a vehicle simulator. In this study, it is described how to make effectively the roads and the driving environment for a vehicle simulator. The GIS (Geographic Information System) is used to construct the roads and the environment effectively. Because the GIS is the integrated system of geographical data, it contains useful data to make virtual driving environment. First, the outline and centerline of roads is abstracted from the GIS. From the road outline, the road width is calculated. Using the centerline, the grid model of roads is constructed. The final graphic model of roads is constructed by mapping road image to the grid model according to the number of lanes and the kind of surface. Data of buildings from the GIS are abstracted. Each shape and height of buildings is determined according to kind of buildings, the final graphic model of buildings is constructed. Then, the graphic model of roadside tree is also constructed. Finally, the driving environment for driving simulator is constructed by converting the three graphic models with the graphic format of Direct-X and by joining the three graphic models.

• International Journal of Precision Engineering and Manufacturing
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• v.6 no.4
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• pp.3-7
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• 2005

Recently, vehicle simulators are widely used to evaluate driver s responses and driver assistance systems. It needs much effort to construct the virtual driving environment for a vehicle simulator. In this study, it is described how to make effectively the roads and the driving environment for a vehicle simulator. GIS (Geographic Information System) is used to construct the roads and the environment effectively. Because the GIS is the integrated system of geographical data, it contains useful data to make virtual driving environment. First, boundaries and centerlines of roads are extracted from the GIS. From boundaries, the road width is calculated. Using centerlines, mesh models of roads are constructed. The final graphic model of roads is constructed by mapping road images to those mesh models considering the number of lanes and the kind of surface. Data of buildings from the GIS are extracted. Each shape and height of building is determined considering the kind of building to construct the final graphic model of buildings. Then, the graphic model of roadside trees is constructed to decide their locations. Finally, the driving environment for driving simulator is constructed by converting the three graphic models with the graphic format of Direct-X and by joining the three graphic models.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.8 no.1
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• pp.1-7
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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 covers with 30 coin-type motors and driver module were developed for this sake. A driving simulator on the 6-DOF motion-base was used for driving situation and we executed the seat vibro-stimulus test with 10 young participants who have normal tactile sense. The haptic recognition ratio by 30 locations was measured and analyzed in the result. The intensity of vibro-stimulus was adjusted by input voltage of motors (1.5V,2.5V,3.5V). All vibro-stimulus locations at 2.5V and 3.5V could be recognized by all participants and even in the lowest recognition ratio of 1.5V. The results showed that the seat vibration stimulus could be useful to transfer the drivers' information while driving.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.3
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• pp.217-223
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• 2015

Autonomous driving is no longer atechnology of the future since the development of autonomous vehicles has now been realized, and many technologies have already been developed for the convenience of drivers. For example, autonomous vehicles are one of the most important drive assistant systems. Among these many drive assistant systems, Cruise Control Systems are now a typical technology. This system constantly maintains a vehicle's speed and distance from a vehicle in front by using Radar or LiDAR sensors in real time. Cruise Control Systems do not only serve their original role, but also fulfill another role as a 'Driving Safety' measure as they can detect a situation that a driver did not predict and can intervene by assuming a vehicle's longitude control. However, these systems have the limitation of only focusing on driver safety. Therefore, in this paper, an Intelligent Cruise Control System that utilizes the path planning method and GIS is proposed to overcome some existing limitations.