• Transactions of the Korean Society of Automotive Engineers
• /
• v.9 no.5
• /
• pp.115-121
• /
• 2001

A driving load estimation method for intelligent cruise control(ICC) vehicles has been proposed in this paper. Vehicle driving load is one of the most important factors of perturbations in vehicle control and can affect the control performance critically. The effect of the control with driving load estimation on vehicle-to-vehicle distance control has been presented and investigated via computer simulations and vehicle tests. The results show that vehicle-driving-load-adaptive control can provide an ICC system with a good acceleration tracking performance. In addition, the results show that driving load estimation can compensate not only the variation of driving load but also the modeling errors.

• Proceedings of the KSME Conference
• /
• 2000.11a
• /
• pp.653-658
• /
• 2000

A driving load estimation method for intelligent cruise control(ICC) vehicles has been proposed in this paper. The driving load is one of the most important factors of perturbations in vehicle control and can affect the control performance critically. The Effect of the control with driving load estimation on vehicle-to-vehicle distance control has been presented and investigated via computer simulations and vehicle tests. The results show that the control with driving load estimation can provide ICC system with a good acceleration tracking performance. In addition, the results show that driving load estimation can compensate not only variation of driving load but also the modeling errors.

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

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.27 no.7
• /
• pp.1146-1151
• /
• 2003

In this paper, results of an analysis of driving behavior characteristics and a driver-adaptive control algorithm for adaptive cruise control systems have been described. The analysis has been performed based on real-world driving data. The vehicle longitudinal control algorithm developed in our previous research has been extended based on the analysis to incorporate the driving characteristics of the human drivers into the control algorithm and to achieve natural vehicle behavior of the adaptive cruise controlled vehicle that would feel comfortable to the human driver. A driving characteristic parameters estimation algorithm has been developed. The driving characteristics parameters of a human driver have been estimated during manual driving using the recursive least-square algorithm and then the estimated ones have been used in the controller adaptation. The vehicle following characteristics of the adaptive cruise control vehicles with and without the driving behavior parameter estimation algorithm have been compared to those of the manual driving. It has been shown that the vehicle following behavior of the controlled vehicle with the adaptive control algorithm is quite close to that of the human controlled vehicles. Therefore, it can be expected that the more natural and more comfortable vehicle behavior would be achieved by the use of the driver adaptive cruise control algorithm.

• Journal of Mechanical Science and Technology
• /
• v.15 no.6
• /
• pp.720-726
• /
• 2001

This paper describes a vehicle driving-load estimation method for application to vehicle Intelligent Cruise Control (ICC). Vehicle driving-load consists of aerodynamic force, rolling resistance, and gravitational force due to road slope and is unknown disturbance in a vehicle dynamic model. The vehicle driving-load has been estimated from engine and wheel speed measurements using a vehicle dynamic model a least square method. The estimated driving-load has been used in the adaptation of throttle/brake control law. The performance of the control law has been investigated via both simulation and vehicle tests. The simulation and test results show that the proposed control law can provide satisfactory vehicle-to-vehicle distance control performance for various driving situations.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.27 no.9
• /
• pp.15-22
• /
• 2013

A new LED lamp driving technology with a charge pump instead of a conventional DC-DC converter is proposed. The proposed driving technology is used to control the LED lamp with digital dimming. The power loss in the zener diodes is reduced because the charging process of the capacitors is selectively controlled according to the digital control signal. From the experimental results, when dimming four LED lamps simultaneously, the average driving circuit efficiency of 89% is obtained, regardless of the dimming level. White light with color temperature over a range of 2800~7200K was produced by dimming control of red, green, blue and amber LED lamps with the proposed driving circuit. The characteristics of the driving circuits can be changed depending on the characteristics of the R, G, B, and A LED lamps. The efficiency of the driving circuits up to a maximum 89% can also be obtained depending on the combination of LED lamps. The driving technology with digital dimming control for LED lamps proposed in this paper would be effective for obtaining high efficiency in LED driving circuits and remote control of LED lamps using digital communications.

• Journal of Korea Entertainment Industry Association
• /
• v.13 no.5
• /
• pp.229-238
• /
• 2019

The aim of the research is to investigate relationship between drivers' self-control, driving behavior and driving stress. 180 people who have driver's licence and have experiences in driving in Gwangju and Jeonnam area participated for the research. The survey was conducted from 29^th April 2015 to 24^th July 2015 and data was analysed to figure out the relationship between drivers' self-control, driving behavior and driving stress. As a result, Firstly, drivers' self-control affected mistakes, violations, errors of driving behavior, and driving environment, traffic regulations, accident control, time pressure of driving stress. It showed a statistical significant difference and the higher drivers' self-control is, the lower sub construct factor of driving behavior and driving stress. Secondly, those factors of drivers' self-control, driving behavior and driving stress were correlated. The result showed the relationship between drivers' self-control, driving behavior and driving stress. It is also possible to utilize the information to prevent car accidents. Finally, it is expected to do research further by expanding the participants into multiple areas of people.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.12 no.4
• /
• pp.139-145
• /
• 2004

This paper presents human-in-the-loop evaluations of vehicle stability control(VSC) system using a driving simulator. A driving simulator which contains full vehicle nonlinear model is evaluated by using actual vehicle test data on the same driving conditions. Braking control inputs for Vehicle Stability Control system have been directly derived from the sliding control law based on vehicle planar motion equations with differential braking. Closed-loop simulation results at realistic driving situations have shown that the proposed controller reduces driving effort of a driver and enhances stability of a vehicle.

• International Journal of Automotive Technology
• /
• v.7 no.5
• /
• pp.603-608
• /
• 2006

As an important and relatively easy to implement technology for realizing Intelligent Transportation Systems(ITS), Adaptive Cruise Control(ACC) automatically adjusts vehicle speed and distance to a preceding vehicle, thus enhancing driver comfort and safety. One of the key issues associated with ACC development is usability and user acceptance. Control parameters in ACC should be optimized in such a way that the system does not conflict with driving behavior of the driver and further that the driver feels comfortable with ACC. A driving simulator is a comprehensive research tool that can be applied to various human factor studies and vehicle system development in a safe and controlled environment. This study investigated driving behavior with ACC for drivers with different driving styles using the driving simulator. The ACC simulation system was implemented on the simulator and its performance was evaluated first. The Driving Style Questionnaire(DSQ) was used to classify the driving styles of the drivers in the simulator experiment. The experiment results show that, when driving with ACC, preferred headway-time was 1.5 seconds regardless of the driving styles, implying consistency in driving speed and safe distance. However, the lane keeping ability reduced, showing the larger deviation in vehicle lateral position and larger head and eye movement. It is suggested that integration of ACC and lateral control can enhance driver safety and comfort even further.

• Proceedings of the KSME Conference
• /
• 2000.04a
• /
• pp.505-510
• /
• 2000

Vehicle performances such as fuel consumption and catalyst-out emissions are affected by a driving pattern, which is defined as a driving cycle with the grade in this study. We developed an algorithm to recognize a current driving pattern by using a neural network. And this algorithm can be used in adapting the driving control strategy to the recognized driving pattern. First, we classified the general driving patterns into 6 representative driving patterns, which are composed of 3 urban driving patterns, 2 suburban driving patterns and 1 expressway driving pattern. A total of 24 parameters such as average cycle velocity, positive acceleration kinetic energy, relative duration spent at stop, average acceleration and average grade are chosen to characterize the driving patterns. Second, we used a neural network (especially the Hamming network) to decide which representative driving pattern is closest to the current driving pattern by comparing the inner products between them. And before calculating inner product, each element of the current and representative driving patterns is transformed into 1 and -1 array as to 4 levels. In the end, we simulated the driving pattern recognition algorithm in a temporary pattern composed of 6 representative driving patterns and, verified the reliable recognition performance.