• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.57-69
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• 2022

Recently, as interest in self-driving cars has increased worldwide, research and development on the Advanced Driver Assist System is actively underway. Among them, the purpose of Adaptive Cruise Control (ACC) is to minimize the driver's driving fatigue through the control of the vehicle's longitudinal speed and relative distance. In this study, for the research of the ACC test in the real environment, the real-road test was conducted based on domestic-road test scenario proposed in preceding study, considering ISO 15622 test method. In this case, the distance measurement method using the dual camera was verified by comparing and analyzing the result of using the dual camera and the result of using the measurement equipment. As a result of the comparison, two results could be derived. First, the relative distance after stabilizing the ACC was compared. As a result of the comparison, it was found that the minimum error rate was 0.251% in the first test of scenario 8 and the maximum error rate was 4.202% in the third test of scenario 9. Second, the result of the same time was compared. As a result of the comparison, it was found that the minimum error rate was 0.000% in the second test of scenario 10 and the maximum error rate was 9.945% in the second test of scenario 1. However, the average error rate for all scenarios was within 3%. It was determined that the representative cause of the maximum error occurred in the dual camera installed in the test vehicle. There were problems such as shaking caused by road surface vibration and air resistance during driving, changes in ambient brightness, and the process of focusing the video. Accordingly, it was determined that the result of calculating the distance to the preceding vehicle in the image where the problem occurred was incorrect. In the development stage of ADAS such as ACC, it is judged that only dual cameras can reduce the cost burden according to the above derivation of test results.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.11a
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• pp.573-577
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• 2002

A new estimated neural networks are proposed in order to measure nonlinear road environments in realtime. This new neural networks is Error Estimated Neural Networks. The structure of it is similar to recurrent neural networks; a delayed output as the input and a delayed error between the output of plant and neural networks as a bias input. In addition, we compute the desired value of hidden layer by an optimal method instead of transfering desired values by backpropagation and each weights are updated by RLS(Recursive Least Square). Consequently, this neural networks are not sensitive to initial weights and a learning rate, and have a faster convergence rate than conventional neural networks. We can estimate nonlinear models in realtime by the proposed networks and control nonlinear models. To show the performance of this one, we control 7 degree simulation, this controller and driver were proved to be effective to drive a car in the environments of nonlinear road systems.

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.4
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• pp.180-189
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• 2009

Currently, most automobile companies are interested in research on intelligent autonomous vehicle. They are mainly focused on driver's intelligent assistant and driver replacement. In order to develop an autonomous vehicle, lateral and longitudinal control is necessary. This paper presents a lateral and longitudinal control system for autonomous vehicle that has only mono-vision camera. For lane detection, we present a new lane detection algorithm using clothoid parabolic road model. The proposed algorithm in compared with three other methods such as virtual line method, gradient method and hough transform method, in terms of lane detection ratio. For adaptive control, we apply a vanishing point estimation to fuzzy control. In order to improve handling and stability of the vehicle, the modeling errors between steering angle and predicted vanishing point are controlled to be minimized. So, we established a fuzzy rule of membership functions of inputs (vanishing point and differential vanishing point) and output (steering angle). For simulation, we developed 1/8 size robot (equipped with mono-vision system) of the actual vehicle and tested it in the athletics track of 400 meter. Through the test, we prove that our proposed method outperforms 98 % in terms of detection rate in normal condition. Compared with virtual line method, gradient method and hough transform method, our method also has good performance in the case of clear, fog and rain weather.

• Journal of Mechanical Science and Technology
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• v.20 no.1
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• pp.29-41
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• 2006

Nowadays, with the advancement of computers, computer simulation linked with VR (Virtual Reality) technology has become a useful method for designing the automotive driving system. In this paper, the VR simulation system was developed to investigate the driving performances of the ASV (Advanced Safety Vehicle) equipped with an ACC (Adaptive Cruise Control) system. For this purpose, VR environment which generates visual and sound information of the vehicle, road, facilities, and terrain was organized for the realistic driving situation. Mathematical models of vehicle dynamic analysis, which includes the ACC algorithm, have been constructed for computer simulation. The ACC algorithm modulates the throttle and the brake functions of vehicles to regulate their speeds so that the vehicles can keep proper spacing. Also, the real-time simulation algorithm synchronizes vehicle dynamics simulation with VR rendering. With the developed VR simulation system, several scenarios are applied to evaluate the adaptive cruise controlled vehicle for various driving situations.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.4
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• pp.163-172
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• 2004

Nowadays, to analyze the dynamic characteristics of the automotive driving system, the computer simulation linked up with VR(Virtual Reality) technology is treated as the useful method with the improvement of computing ability. In this paper, the VR simulation system has been developed to investigate the driving characteristics of the ASV(Advanced Safety Vehicle) equipped with an ACC(Adaptive Cruise Control) system. For the purpose, VR environment which generates 3D graphic and sound information of the vehicle, the road, the facilities, and the terrain has been organized for the driving reality. Mathematical models of vehicle dynamic analysis including the ACC model have been constructed for computer simulation. The ACC modulates the throttle and brake functions to regulate the vehicle speed so that vehicles could keep proper spacing. Also, the real-time simulation algorithm synchronizes vehicle dynamic simulation with the graphic rendering. With the developed VR simulation system, simple scenarios are applied to analyze the dynamic characteristics. It is shown that the VR simulation system could be useful to evaluate the adaptive cruise controlled vehicle on various driving conditions.

• Journal of the Ergonomics Society of Korea
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• v.35 no.1
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• pp.11-27
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• 2016

Objective: The purpose of this study was to develop and evaluate high technology adaptive driving controls, such as mini steering wheel-lever system and joystick system, for the people with physical disabilities in the driving simulator. Background: The drivers with severe physical disabilities have problems in operation of the motor vehicle because of reduced muscle strength and limited range of motion. Therefore, if the remote control system with driver-by-wire technology is used for adaptive driving controls for people with physical limitations, the disabled people can improve their quality of life by driving a motor vehicle. Method: We developed the remotely controlled driving simulator with drive-by-wire technology, e.g., mini steering wheel-lever system and joystick system, in order to evaluate driving performance in a safe environment for people with severe physical disabilities. STISim Drive 3 software was used for driving test and the customized Labview program was used in order to control the servomotors and the adaptive driving devices. Thirty subjects participated in the study to evaluate driving performance associated with three different driving controls: conventional driving control, mini steering wheel-lever controls and joystick controls. We analyzed the driving performance in three different courses: straight lane course for acceleration and braking performance, a curved course for steering performance, and intersections for coupled performance. Results: The mini steering wheel-lever system and joystick system developed in this study showed no significant statistical difference (p>0.05) compared to the conventional driving system in the acceleration performance (specified speed travel time, average speed when passing on the right), steering performance (lane departure at the slow curved road, high-speed curved road and the intersection), and braking performance (brake reaction time). However, conventional driving system showed significant statistical difference (p<0.05) compared to the mini steering wheel-lever system or joystick system in the heading angle of the vehicle at the completion point of intersection and the passing speed of the vehicle at left turning. Characteristics of the subjects were found to give a significant effect (p<0.05) on the driving performance, except for the braking reaction time (p>0.05). The subjects with physical disabilities showed a tendency of relatively slow acceleration (p<0.05) at the straight lane course and intersection. The steering performance and braking performance were confirmed that there was no statistically significant difference (p>0.05) according to the characteristics of the subjects. Conclusion: The driving performance with mini steering wheel-lever system and joystick control system showed no significant statistical difference compared to conventional system in the driving simulator. Application: This study can be used to design primary controls with driver-by-wire technology for adaptive vehicle and to improve their community mobility for people with severe physical disabilities.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.4
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• pp.267-272
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• 2015

Active noise control (ANC) is a method of cancelling a noise signal in an acoustic cavity by generating an appropriate anti-noise signal via canceling loudspeakers. The continuous progress of ANC involves the development of improved adaptive signal processing algorithms, transducers, and DSP hardware. In this paper, the convergence behavior and the stability of the FxLMS algorithm in ANC systems with real-time implementation is proposed. Specially, The advanced DSP H/W with dual core(DSP+ARM) and API(application programming interface) S/W programming was developed to improve the real-time implementation performance under the FxLMS algorithms of input noise such as road noise environment. The experimental results are found to be in good agreement with the theoretical predictions.

• Journal of Korean Port Research
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• v.14 no.3
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• pp.291-301
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• 2000

T his paper presents the lateral and longitudinal control algorithm for the driving of a 4WS AGV(Automated Guided Vehicle). The control law to the lateral and longitudinal control of the AGV includes adaptive agin tuning ability, that is the controller gain of the gravity compensated PD controller can be changed on a real-time. The gain tuning law is derived from the Lyapunov direct method using the output error of the reference model and the actual model, And to show the performance of the presented lateral and longitudinal control algorithm, we simulate toe nonlinear AGV equations of the motion by deriving the Newton-Euler Method, The read path is from quay yard area to docking position in loading yard area. The quay yard area is where the quay crane loads the container to the AGV and the docking position is where the container is transferred to the gantry crane. The road types are constructed in a straight line and J-turn. When driving the straight line, the driving velocity is 6㎧ and the J-turn is 3㎧.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.1
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• pp.103-111
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• 2016

This paper presents an adaptive variable weights tuning system for an integrated chassis control with electronic stability control (ESC) and active front steering (AFS) for lateral stability enhancement. After calculating the control yaw moment needed to stabilize a vehicle with a controller design method, it is distributed into the tire forces generated by ESC and AFS using weighted pseudo-inverse-based control allocation (WPCA). On a low friction road, lateral stability can deteriorate due to high vehicle speed. To cope with the problem, adaptive tuning rules on variable weights of the WPCA are proposed. To check the effectiveness of the proposed method, a simulation was performed on the vehicle simulation package, CarSim.

• The Journal of Korea Robotics Society
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• v.5 no.3
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• pp.270-277
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• 2010

Various robot platforms have been designed and developed to perform given tasks in a hazardous environment for the purpose of surveillance, reconnaissance, search and rescue, and etc. We have considered a terrain adaptive hybrid robot platform which is equipped with rapid navigation on flat floors and good performance on overcoming stairs or obstacles. Since our special consideration is posed to its flexibility for real application, we devised a design of a transformable robot structure which consists of an ordinary wheeled structure to navigate fast on flat floor and a variable tracked structure to climb stairs effectively. Especially, track arms installed in front side, rear side, and mid side are used for navigation mode transition between flatland navigation and stairs climbing. The mode transition is determined and implemented by adaptive driving mode control of mobile robot. The wheel and track hybrid mobile platform apparatus applied off-road driving mechanism for various professional service robots is verified through experiments for navigation performance in real and test-bed environment.