• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.11 no.4
• /
• pp.62-67
• /
• 2002

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy-neural network and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized loaming architecture. It is Proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tucking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Journal of the Korean Society of Industry Convergence
• /
• v.17 no.2
• /
• pp.69-76
• /
• 2014

This paper proposes a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, and back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2002.10a
• /
• pp.235-240
• /
• 2002

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, and back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

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

• International Journal of Automotive Technology
• /
• v.3 no.2
• /
• pp.79-88
• /
• 2002

Emergent Collision Avoidance Systems (CAS's) are beginning to assist drivers by performing specific tasks and extending the limits of driver's perception. As CAS's evolve from simple systems handling discrete tasks to complex systems managing interrelated driving tasks, the risk of failure from hidden causes greatly increases. The successful implementation of such a complex system depends upon a robust software architecture. Host of the difficulty in implementing system arises from interconnections between the components. The CAS architecture presented in this paper focuses on these interconnections to mitigate this problem. Moreover, by constructing the GAS architecture through the composition of existing architectural styles, the resulting system will exhibit predictable qualities. Some of the qualities represent limitations that translate into constraints on the system. Others are beneficial aspects that satisfy stakeholder requirements .

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.1130-1133
• /
• 2003

The goal of this research is developing advanced lane detecting algorithm for unmanned vehicle. Previous lane detecting method to bring on error become of the lane loss and noise. Therefore, new algorithm developed to get exact information of lane. This algorithm can be used to AGV(Autonomous Guide Vehicle) and LSWS(Lane Departure Warning System), ACC(Adapted Cruise Control). We used 1/10 scale RC car to embody developed algorithm. A CCD camera is installed on top of vehicle. Images are transmitted to a main computer though wireless video transmitter. A main computer finds information of lane in road image. And it calculates control value of vehicle and transmit these to vehicle. This algorithm can detect in input image marked by 256 gray levels to get exact information of lane. To find the driving direction of vehicle, it search line equation by curve fitting of detected pixel. Finally, author used median filtering method to removal of noise and used characteristic part of road image for advanced of processing time.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2000.10a
• /
• pp.1-8
• /
• 2000

Automotive electronics as we know it today encompasses a wide variety of devices and systems. Key to them all, and those yet to come. is the ability to sense and measure accurately automotive control parameters. In other words, sensors and actuators are the heart of any automotive electronics application. The important of sensors and actuators cannot be overemphasized. The future growth of automotive electronics is arguably more dependent on sufficiently accurate and low-cost sensors and actuators than on computers, controls, displays, and other technologies. Without them, all of controls system - engine. transmission. cruise, braking, traction, suspension, steering, lighting, windshield wipers, air conditioner/hearter - would not be possible. Those controls, of course, are key to car operation and they have made cars over the years more drivable, safe, and reliable. In this lecture, the principle and future trends of electronic control gasoline engine will be discuss.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2004.10a
• /
• pp.207-212
• /
• 2004

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, and back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.3
• /
• pp.57-64
• /
• 2020

The leading technologies of the ADAS (Advanced Driver Assist System) are ACC (Advanced Cruise Control), LKAS (Lane Keeping Assist System), and AEB (Autonomous Emergency Braking). LKAS is a system that uses cameras and infrared sensors to control steering and return to its running lane in the event of unintentional deviations. The actual test is performed for a safety evaluation and verification of the system. On the other hand, research on the system evaluation method is insufficient when an additional steering angle is applied. In this study, a model using Prescan was developed and simulated for the scenarios proposed in the preceding study. Comparative analyses of the simulation and the actual test were performed. As a result, the modeling validity was verified. A difference between the front wheels and the lane occurred due to the return velocity. The results revealed a maximum error of 0.56 m. The error occurred because the lateral velocity of the car was relatively small. On the other hand, the distance from wheels to the lanes displayed a tendency of approximately 0.5 m. This can be verified reliably.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.7 no.6
• /
• pp.165-173
• /
• 1999

HILS system consists of hardwares which are engine and dynamometer and softwares which is vehicle model without the engine. It is well-known that because of engines's nonlinearity it is difficult to describe an engine exactly and not to lose it reality coincidently. But HILS system is the high technology that can compensate this weakness by using a real engine instead of model. The various experiments regarding the ACC which are not normally available for real vehicle tests have been performed by the HILS system. From the results , the HILS system is expected to decrease the experimental accident rate and save costs and time. Compared with simulation, HILS experimental results show similarities and expected to increase road capacity.