• Proceedings of the KSME Conference
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• 2007.05a
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• pp.855-860
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• 2007

This paper describes a human driver model developed based on finite preview optimal control method. The human driver steering model is constructed to minimize a performance index which is a quadratic form of lateral position error, yaw angle error and steering input. Simulation studies are conducted using a vehicle simulation software, Carsim. The Carsim vehicle model is validated using vehicle test data. In order to validate the human driving steering model, the human driver steering model is compared to the driving data on a virtual test track(VTT) and the actual vehicle test data. It is shown that human driver steering behaviors can be well represented by the human driver steering model presented in this paper

• Journal of the Korean Society of Safety
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• v.22 no.1 s.79
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• pp.61-66
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• 2007

Car crashes are the leading cause of death for persons of every age. Specially, human-related factor has been known to be the primary causal factor of such crashes than vehicle-and environmental-related factors. There are various studies to analyze driver's behavior and characteristics in driving for reducing the car crashes in many areas of car engineering, psychology, human factor, etc. However, there are almost no studies which analyze mainly the human errors in driving and estimate their probabilities in terms of human reliability analysis. This study estimates the probability of human error in driving, i.e. driver error probability. First, fifty driver errors are investigated through DBQ (Driver Behavior Questionnaire) revision and the error likelihoods in driving are collected which are judged by skillful drivers using revised DBQ. Next, these likelihoods are converted into driver error probabilities using the results that verbal probabilistic expressions are changed into quantitative probabilities. Using these probabilities we can improve the warning effects on drivers by indicating their driving error likelihoods quantitatively. We can also expect the reduction effects of car accident through controlling especially dangerous error groups which have higher probabilities. Like these, the results of this study can be used as the primary materials of safety education on drivers.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.12
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• pp.1186-1191
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• 2007

Human driver monitoring system is one of the most important systems for the safety in driving vehicles, and therefore driver assistance system has gained much attention during the last decade. This paper proposed an intelligent driver assistance system which monitors human driver's states from bio-signals such as ECG and Blood Pressure. The proposed system used mamdani fuzzy inference to evaluate the driver's mental strain and generated warning signals to the driver. The approach using bio-signals in driver assistance system is the main issue of the related systems and the preliminary results showed the possibility of further research topics in developing more intelligent embedded systems with bio-signal feedback.

• Journal of the Korea Safety Management & Science
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• v.14 no.4
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• pp.85-91
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• 2012

To verify the effect of driver's personal characteristics of driver on the accident frequency through railway accidents caused by human errors and the relationship with aptitude test. To prove the relevance between the driver's personal characteristics and human error accidents. Accident data from 2010 to 2011 was analyzed which collected from a train crew department in K national corporation, and 31 drivers gave an personal interview from Sep. 2011 to Nov. 2011 who had controlled a train alone and caused an accident. Compared between driver's personal characteristics and accident rate, and accident induction possibility surveyed from normal person and disqualified in aptitude tests. Accidents was occurred with the age 40s (27%) and 50s (25%), and with the experience between 15 years and 20 years (38%) and over 20 years (30%). Because more aged, more experienced, it can be seen in the correlation between driver's age and accidents induction caused by human errors like illusion. First of all it must be checked whether working conditions and environmental factors are human error-prone. Most accidents occur when received civil complaints or manager at the riding. Therefore accidents can be prevented when investigated through subsequent surveys how often human error happens, even though no accident, and safety device installed based on the error frequency.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.101-111
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• 1998

CNS (Car Navigation System) is the most compatible candidate among various in-vehicle information systems as a provider of ITS (Intelligence Transport Systems) information. It generally consists of remote controller, display, CD-changer, GPS receiver and so on. Among them, display is the most important and critical element of the HMI (Human-Machine Interface) suggesting the digital map to the driver. Therefore, it is certain that the display gives cognitive, physical, mental and visual workloads to the driver which are directly related with the driver's and road safety with the success of ITS. Until now, various human factors techniques have been developed and applied to estimate the driver's workload and to collect the driver's requirements of the CNS digital map, for example, mental workload assessment, visual activity analysis, cognitive analysis and so on. In addition to these kinds of techniques, this research performed the human sensibility ergonomics approach to directly investigate and evaluate the driver's requirements and sensibilities of the real products.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.542-545
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• 2004

The vibration reduction process for the driver comfort of a forklift truck is studied in this study since the related driver comfort is a primary design target in the vehicle design recently. However, the underlying study for a vibration analysis regarding to the driver comfort is still an element stage. Thus, a preceding large work has to be needed to apply the CAE technology for the detail vehicle design, and it prevents the vehicle optimal design. To reduce the proceeding large works, the evaluated process and required data are comply with the accumulated trouble shooting experiences in this study. Since the driver comfort is a human related problem, the human vibration index associated with analysis vibration result is additionally introduced as a driver comfort judgement value.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.646-649
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• 2007

Although the up-to-date(high) technique is developing and automating in many fields, the center of the all fields is closely connected with the human resource. Also, the railway driver is required to have both high technique and high level of mental work. Therefore, this research will grasp the types of the railway driver groups through railway driver's task stress analyze(JCQ and Job Content Questionnaire), and then analyze the human errors which the types can occur. Finally, this research will propose the way to reduce the human errors.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.2
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• pp.216-222
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• 2002

The ergonomic human model can be considered as a tool for the evaluation of ergonomic factors in vehicle design process. The proper anthropometric data on driver's postures are needed in order to apply a human model to vehicle design. Although studies on driver's posture have been carried out for the last few decades, there are still some problems for the posture data to be applied directly to the human model due to the lack of fitness because such studies were not carried out under the conditions for the human model application. In the traditional researches, the joint angles were evaluated by the categorized data, which are not appropriate for the human model application because it is so extensive that it can not explain the posture evaluation data in detail. And the human models require whole-body posture evaluation data rather than joint evaluation data. In this study a postural evaluation function was developed not by category data but by the concept of the loss function in quality engineering. The loss was defined as the discomfort in driver's posture and measured by the magnitude estimation technique in the experiment using a seating buck. Four loss functions for the each joint - knee, hip, shoulder, and elbow were developed and a whole-body postural evaluation function was constructed by the regression analysis using these loss functions as independent factors. The developed postural evaluation function shows a good prediction power for the driver's posture discomfort in validation test. It is expected that the driver's postural evaluation function based on the loss function can be used in the human model application to the vehicle design process.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.5
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• pp.201-209
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• 2003

Virtual human models are widely used to save time and expense in vehicle safety studies. A human model is an essential tool to visualize and simulate a vehicle driver in virtual environments. This research is focused on creation and application of a human model fer virtual reality. The Korean anthropometric data published are selected to determine basic human model dimensions. These data are applied to GEBOD, a human body data generation program, which computes the body segment geometry, mass properties, joints locations and mechanical properties. The human model was constituted using MADYMO based on data from GEBOD. Frontal crash and bump passing test were simulated and the driver's motion data calculated were transmitted into the virtual environment. The human model was organized into scene graphs and its motion was visualized by virtual reality techniques including OpenGL Performer. The human model can be controlled by an arm master to test driver's behavior in the virtual environment.

• International Journal of Automotive Technology
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• v.7 no.1
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• pp.35-41
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• 2006

Driving simulations were performed to evaluate the effect of providing both visual information and body sensory information on changes in steering characteristics and the amount of perspiration in drift cornering. When the driver is provided with body sensory information and visual information, the amount of perspiration increases and the driver can perform drift control with a moderate level of tension. With visual information only, the driver tends to easily go into a spin because drift control is difficult. In this case, the amount of perspiration increases greatly as compared with the case where body sensory information is also provided, reflecting a very high perception of risk. When body sensory information is provided, the driver can control drift adequately, feeding back the roll angle information in steering. The importance of the driver's perception of the state of the vehicle was thus confirmed, and a desirable future direction for driver assistance systems was determined.