• Korean Journal of Culture and Social Issue
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• v.20 no.4
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• pp.281-305
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• 2014

This study investigated the relationship between older driver's safe driving behavior, driving mobility(amount of driving, assessment for driving-related physical ability, confidence for adaptation in driving situation, amount of social activity) and subjective well-being(life satisfaction, positive/negative affect). The data of these variables were collected by questionnaire method based on face-to-face interview. The results can be summarized as followings. First, the older driver who reported higher scores in the self-report safe driving behavior questionnaire tended to show higher level of subjective well-being and driving-based mobility. Second, all the sub-factors in the driving-based mobility questionnaire were positively related to life satisfaction, positive affect but negatively related to negative affect except amount of driving. Finally, it was found that both confidence for adaptation in driving situation and amount of social activity positively mediated the relationship between self-report safe driving behavior and life satisfaction and positive affect, but confidence for adaptation in driving situation negatively mediated the relationship between self-report safe driving behavior and negative affect, Implication and suggestion were discussed.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.409-416
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• 2006

Real-time traveler information disseminated through Variable Message Signs (VMS) is known to have effects on driver route choice decisions. In the past, many studies have attempted to optimize the system performance using VMS message content as the primary control variable of driver route choice. This research proposes a VMS information provision optimization model which searches the best combination of VMS message contents and display sequence to minimize the total travel time on a highway network considered. The driver route choice models under VMS information provision are developed using a stated preference (SP) survey data in order to realistically capture driver response behavior. The genetic algorithm (GA) is used to find the optimal VMS information provision strategies which consists of the VMS message contents and the sequence of message display. In the process of the GA module, the system performance is measured using micro traffic simulation. The experiment results highlight the capability of the proposed model to search the optimal solution in an efficient way. The results show that the traveler information conveyed via VMS can reduce the total travel time on a highway network. They also suggest that as the frequency of VMS message update gets shorter, a smaller number of VMS message contents performs better to reduce the total travel time, all other things being equal.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.2
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• pp.149-156
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• 2005

In this paper, the VR(Virtual Reality) simulation system is developed to analyze driver's perceptive response on the ASV(Advanced Safety Vehicle). The ASV is the vehicle of next generation equipped with various warning systems. For the purpose, the VR simulation system consists of VR database, vehicle dynamic model, graphic/sound system, and driving system. The VR database which generates 3D graphic and sound information is organized for the driving reality. Mathematical models of vehicle dynamic analysis are constructed to represent the dynamic behavior of a vehicle. The driving system and the graphic/sound system provide a driver with the operation of a vehicle and the feedback of a driving situation. Also, the real-time simulation algorithm synchronizes the vehicle dynamic model with the VR database. To check the validity of the developed system, a simple scenario is applied to investigate driver's perceptive response time and vehicle acceleration on an emergency situation. It is confirmed that the proposed system is useful and helpful to design the FVCWS(Forward Vehicle Collision Warning System).

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

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2007.05a
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• pp.409-412
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• 2007

A motorcycle helmet is the best means to protect the head of bike's driver and it is directly connected to a driver's life. Prior to producing of the helmet, it has to be passed the process of impact test to evaluate of its safety. This test evaluates peak acceleration and H.I.C (Head Injury Criteria). This paper analyzes impact test with finite element method to find the behavior of helmet during the test. Also, the effect of impact sites on the helmet was evaluated to improve the thickness distribution of the helmet.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1867-1870
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• 2003

The analysis and simulation are the method to study the behavior, response, and specification of the driver device. This paper proposes brushless DC drive which using the vector control technique. The encoder is used detect the rotor position and decode to Three-phase step signal. The step signal is modulated with triangle signal and change to the pulse width modulation (PWM) signal. The PWM signal is used for control the input power of the motor based on the vector control technique. The experimental results of the driver circuit and motor response performed under the following condition: as the motor was started, change the load torque, and vary the supply voltage. The experimental performs with a dynamometer and the test results are compared to the simulation method is the same result.

• Transactions of Materials Processing
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• v.16 no.5 s.95
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• pp.370-374
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• 2007

A motorcycle helmet is very essential to protect the head of driver and it is directly connected to driver's life. Prior to producing the helmet, it has to be passed the process of impact test to evaluate its safety. This test evaluates peak acceleration and head injury criteria (H.I.C.). This paper simulates the impact test with finite element method to find the behavior of helmet during the test. Also, the effect of impact sites on the helmet was evaluated to improve the thickness distribution of the helmet.

• Journal of the Korean Society of Safety
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• v.23 no.2
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• pp.45-50
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• 2008

The purpose of the present study was to investigate the age difference in driving behavior(more specifically, left-turn). The participants were instructed to report whether they can turn left their car in the T-shape road(road and other vehicles' behavior relating to driver's tasks were recorded in advance and projected the simulation screen) after the leading vehicle passed them(i.e., before the target vehicle arrived). The participants' judgment accuracy and response bias were analyzed by using signal detection theory. The results showed that the old group tended to be less sensitive but more confident in their judgement of turning left their car. In particular, both age groups appeared to more depend on the distance from observation location to approaching vehicle rather than arrival times or driving speeds of the approaching vehicle.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.5
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• pp.125-135
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• 2004

The validity of simulation has been well-established for decades in areas such as computer and communication system. Recently, the technique has become entrenched in specific areas such as transportation and traffic forecasting. Several methods have been proposed for investigating complex traffic flows. However, the dynamics of vehicles and their driver's characteristics, even though it is known that they are important factors for any traffic flow analysis, have never been considered sufficiently. In this paper, the traffic simulation using a multi-agent approach with considering vehicle dynamics is proposed. The multi-agent system is constructed with the traffic environment and the agents of vehicle and driver. The traffic environment consists of multi-lane roads, nodes, virtual lanes, and signals. To ensure the fast calculation, the agents are performed on the based of the rules to regulate their behaviors. The communication frameworks are proposed for the agents to share the information of vehicles' velocity and position. The model of a driver agent which controls a vehicle agent is described in the companion paper. The vehicle model contains the nonlinear subcomponents of engine, torque converter, automatic transmission, and wheels. The simulation has proceeded for an interrupted and uninterrupted flow model. The result has shown that the driver agent performs human-like behavior ranging from slow and careful to fast and aggressive driving behavior, and that the change of the traffic state is closely related with the distance and the signal delay between intersections. The system developed shows the effectiveness and the practical usefulness of the traffic simulation.