• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.717-722
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• 2003

A driving simulator is a computer-controlled tool to study an interface between a driver and vehicle response by enabling the driver to participate in judging vehicle characteristics. Using the driving simulator, human factor study, vehicle system development and other research can be effectively done under controllable, reproducible and non-dangerous conditions. An Adaptive Cruise Control (ACC) system is generally regarded as a system that can be achieved in the near future without the demanding infrastructure components and technologies. ACC system is an automatic vehicle following system with no human engagement in the longitudinal vehicle direction. And the influence of the driver is substantial in developing the system. Driving characteristic is very different according to the accident riskiness, gender, age and so on. In this research, experiments have been carried out to investigate driving characteristics with the ACC system, using a driving simulator. Participants are 21 male and 19 female. Driving characteristics such as preferred headway-time, lane keeping ability, eye direction, and head movement have been observed and compared between the driving with ACC and the driving without ACC.

• 한국정보디스플레이학회:학술대회논문집
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• 2006.08a
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• pp.393-398
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• 2006

This paper classifies driving technologies for AMOLEDs by the driving TFT conditions in pixels. A saturation region operation type driving TFT circuit provides good stability of OLED because of constant current drive. However, complicated compensation circuits are necessary to avoid effect of the TFT characteristics deviation. On the other hand, a linear region operation type driving TFT circuit provides better uniformity of the display image and lower power consumption. However, the stability of OLED is critical because of constant voltage drive.

• Proceedings of the Korea Society for Simulation Conference
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• 2000.11a
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• pp.192-197
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• 2000

Real-time driving simulation is a comprehensive technology that can be applied effectively to vehicle and traffic safety improvement, by reproducing various driving conditions and situations realistically in a safe and controlled environment. This paper describes PC-based real-time driving simulation technology in terms of design factors and simulation components. It also introduces Kookmin University Driving Simulators developed based on these considerations, which have been applied effectively to ABS HILS and a human factor study concerning sudden acceleration accident reconstruction.

• Journal of Korean Society for Atmospheric Environment
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• v.29 no.6
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• pp.745-756
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• 2013

The purpose of this study is to evaluate representativeness of fuel-based emission factors. Twelve light-duty diesel vehicles which meet Euro-3 to 5 legislative emission limits were selected for emission tests. Second-by-second modal emission rates of vehicles were measured on a standard laboratory chassis dynamometer system. An off-cycle driving cycle was developed as a representative Korean real-world on-road driving cycle. Fuel-based emission factors were developed for short trip segments that involved in the selected driving cycle. Each segment was defined to have unit travel distance, which is 1 km, and characterized by its average speed and Relative Positive Acceleration (RPA). Fuel-based $NO_x$ emission factors demonstrate relatively good representativeness in terms of vehicle operation conditions. $NO_x$ emission factors are estimated to be within ${\pm}20%$ of area-wide emission factor under more than 40% of total driving situations. This result implies that the fuel-based $NO_x$ emission factor could be practically implemented into the on-road emission management strategies, such as a remote sensing device (RSD). High emitting vehicles as well as high emitting operating conditions heavily affect on the mean values and distributions of CO and THC emission factors. Few high emitting conditions are pulling up the mean value and biasing the distributions, which weaken representativeness of fuel-based CO and THC emission factors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5842-5861
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• 2019

A current autonomous vehicle determines its driving strategy by considering only external factors (Pedestrians, road conditions, etc.) without considering the interior condition of the vehicle. To solve the problem, this paper proposes "An Optimal Driving Support Strategy(ODSS) based on an Genetic Algorithm for Autonomous Vehicles" which determines the optimal strategy of an autonomous vehicle by analyzing not only the external factors, but also the internal factors of the vehicle(consumable conditions, RPM levels etc.). The proposed ODSS consists of 4 modules. The first module is a Data Communication Module (DCM) which converts CAN, FlexRay, and HSCAN messages of vehicles into WAVE messages and sends the converted messages to the Cloud and receives the analyzed result from the Cloud using V2X. The second module is a Data Management Module (DMM) that classifies the converted WAVE messages and stores the classified messages in a road state table, a sensor message table, and a vehicle state table. The third module is a Data Analysis Module (DAM) which learns a genetic algorithm using sensor data from vehicles stored in the cloud and determines the optimal driving strategy of an autonomous vehicle. The fourth module is a Data Visualization Module (DVM) which displays the optimal driving strategy and the current driving conditions on a vehicle monitor. This paper compared the DCM with existing vehicle gateways and the DAM with the MLP and RF neural network models to validate the ODSS. In the experiment, the DCM improved a loss rate approximately by 5%, compared with existing vehicle gateways. In addition, because the DAM improved computation time by 40% and 20% separately, compared with the MLP and RF, it determined RPM, speed, steering angle and lane changes faster than them.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08a
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• pp.944-947
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• 2007

The electrooptic characteristics of 32-inch multichannel-structured, mercury-type flat fluorescent lamps have been investigated in detail. The luminance and the lamp current/voltage have been monitored by changing the driving conditions such as duty ratio, backlight conditions. It was found that the efficiency became the maximum at the duty ratio of 50 % with a nearby metal plate.

• Journal of Biosystems Engineering
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• v.37 no.3
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• pp.131-139
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• 2012

In this study, we developed a simulation program for the prediction of tractive performance of a tractor, by applying a widely used empirical model for tractive performance prediction of single tire, Brixius. The tractive performance prediction program can readily predict and estimate tractive performance according to various soil conditions and different specifications of tractors. The program was developed with the considerations of tractor's specification-related parameters (e.g., weight, tire size, and wheelbase of the tractor), a soil parameter (i.e., cone index which represents the soil strength), and operating conditions of the tractor (e.g., theoretical speed and driving types such as 2WD and 4WD). Also, the program was designed to provide tractive performance prediction results of tractors such as gross traction, motion resistance, net traction, and tractive efficiency, in the form of not only numerical values but also graphical visualization. To evaluate the feasibility of the program, we input three different soil conditions (which have different cone indexes each other) and tractor operating conditions to the program and analyzed the tractive performance from each input condition. From the analysis, it can be concluded that the developed program can be effectively utilized to predict the tractive performance under various soil conditions and driving types of tractors with different specifications.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.3
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• pp.65-76
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• 2000

To measure the fuel consumption rate of a vehicle, a car is tested on chassis dynamometer following given driving mode. But the fuel consumption rate measured by this method may be somewhat different from that measured in on-road driving conditions. It may be due to not considering road grade in driving modes. In this study, new driving modes which include road grade are proposed, and the simulation program to estimate the real driving fuel consumption rate of a vehicle is developed. On-road car tests to verify the simulation program are carried out and the results of the simulation are analysed and compared with those of the experiments.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.2
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• pp.38-46
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• 2012

This paper discusses the energy consumption for a mid-size electric vehicle(EV) under various conditions. In order to analyze which driving style is more efficient in terms of the system of the EV, we develop the electric vehicle model and apply several types of speed profiles such as different steady speeds, acceleration/deceleration, and a real world driving cycle including the elevation profile obtained from a GPS device. The results show that the energy consumption of the EV is affected by the operating efficiency of components when driving at low speed, while it depends on required power at wheels when driving at high speed. Also this paper investigates the effect of the elevation of a road and the rate of electrical braking on the energy consumption as well as the fuel economy of a conventional vehicle model under the same conditions.

• Journal of Convergence for Information Technology
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• v.10 no.7
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• pp.223-231
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• 2020

Older drivers have an increased risk of accidents due to poor function, but they also develop self-regulation ability to check their own changes. Thus, information on whether the actual elderly driver responds to changes in driving ability and risk may provide a meaningful basis for the clinic and research of the elderly's driving ability assessment. Therefore, the purpose of this study is to provide basic data for the evaluation of elderly drivers by analyzing the driving risk self-perception characteristics in terms of driving behavior and function with Korean elderly drivers. A self-reporting assessment was conducted on 500 elderly drivers living in the community and the characteristics of driving risk perception were analyzed. As a result, it was confirmed that many elderly drivers are aware of the driving risk when their vision and hearing are impaired or when they find it difficult to adapt to changes in driving conditions. On the other hand, the characteristics of insensitive reactions to changes in medical health conditions, such as drug use or epilepsy, seizures, and loss of consciousness, were identified. The researcher hopes this study will contribute to the safety management of elderly drivers in Korea, where aging is accelerating.