• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.3
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• pp.245-253
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• 2002

A driver model with nervous neuromuscular system was developed to steer a vehicle along the prescribed path during handling simulations. A 3-dimensional vehicle model with 10 DOF and 3 DOF steering handle are used to perform a computer simulation. PID and fuzzy controller are used to perform single and double lane change, and their tracking abilities were compared. The effects of time delay and preview distance are also investigated, and it is demonstrated that the driver model developed can be an aid far objective evaluation of vehicle handling simulation.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.2
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• pp.71-76
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• 2001

This paper deals with an estimation method for sideslip angle by using an unknown disturbance observation technique in 4WS passenger car systems. Firstly, a 4WS vehicle model with 3DOF is derived under the constant velocity and same tyres properties. The vehicle dynamics is transformed into the linear state space model with considering the external disturbances. Secondly, and unknown disturbance observer is introduced and its property which estimating the states of system without any disturbance information is shown. Lastly, the estimated sideslip angle of the 4WS vehicle system is verified through numerical simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1014-1019
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• 2005

In this paper, a neural network technique for automatic steering control of a four wheel drive autonomous highway snowplow vehicle is presented. Controllers are designed by the LQR method based on the vehicle model. Then, neural network is used as an auxiliary controller to minimize lateral tracking error under the presence of load. Simulation studies of LQR control and neural network control are conducted for the vehicle model under a virtual snowplowing situation. Tracking performances are also compared for two and four wheeled steering vehicles.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.196-196
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• 2000

This paper describes a lateral guidance system of an autonomous vehicle, using a neural network model of magneto-resistive sensor and magnetic fields. The model equation was compared with experimental sensing data. We found that the experimental result has a negligible difference from the modeling equation result. We verified that the modeling equation can be used in simulations. As the neural network controller acquires magnetic field values(B$\_$x/, B$\_$y/, B$\_$z/) from the three-axis, the controller outputs a steering angle. The controller uses the back-propagation algorithms of neural network. The learning pattern acquisition was obtained using computer simulation, which is more exact than human driving. The simulation program was developed in order to verify the acquisition of the teaming pattern, teaming itself, and the adequacy of the design controller. The performance of the controller can be verified through simulation. The real autonomous electric vehicle using neural network controller verified good results.

• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.4
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• pp.160-165
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• 1998

In this paper, We discuss the directional stability of a Mini-bus with varying suspension design parameters. We analyzed the vehicle behavior during the cornering in a transient steering condition. We made a vehicle model by use of DADS, which is dynamic analysis software, in order to carry out many cases of simulation with varying design parameters. The effect of toe-geometry change to vehicle stability is evaluated by computer simulation and the actual test. In order to reduce the under steer characteristics of a mini-bus, the amount of toe geometry change should be less than current value.

• Proceedings of the KSR Conference
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• 1999.05a
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• pp.135-142
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• 1999

This paper deals with dynamic characteristics of automated guideway transit vehicle with rubber tires. Several models for guideway system of LRT(Light Rail Transit) have been Proposed because of the necessity of guideway system for LRT with rubber tires on exclusive rail unlike steel tires. Here, steering system and bogie system are investigated to compare with dynamic characteristics. On selecting guideway system, the way of vehicle operation should be considered and simultaneously the dynamic characteristics of the vehicle must be evaluated with respect to each guideway. The results show that stability is essential for vehicle with steering system, and that single-axle bogie system gives the good stability, though it is necessary to reduce the guide-wheel force

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.6
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• pp.166-174
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• 2004

In urban area narrow commuter vehicles have attracted interest as a possible solution to reduce traffic congestion and parking problems. However, a narrow vehicle has an increased to overturn during hard cornering when compared to conventional vehicles. This tendency can be reduced by tilting it toward the inside of the turn. Two types of automatic tilting control systems which are Direct Tilt Control(DTC) and Steering Tilt Control(STC) have been developed. In this paper as one of the technique to improve the handling performance for the unusual vehicle the control system which blends both the DTC and the STC system is considered. It uses the merits of both the DTC and the STC system. As a control strategy for combination the switching control method is used. Finally, the fact that the unusual vehicle is safe under an emergency situation such as slippery road surface is proved by computer simulation.

• The Journal of Korea Robotics Society
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• v.17 no.4
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• pp.477-483
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• 2022

In this paper, we propose waste collection vehicle system with a safety device for worker safety and an autonomous driving function. The steering system is applied as MDPS (Motor Drive Power Steering) system to control the waste collection vehicle of the internal combustion engine. Safety-related errors is prevented through redundancy brake of the integrated system and the control braking system. In order to ensure safety between workers and waste collection vehicles, work guidelines and safety devices for emergency stop in case of danger are applied to vehicles. In addition, this research is conducted on improving the working efficiency through vehicle condition monitoring system and a short-range control system for field test. This research is aimed to secure stability through demonstration and contribute to the industrialization of unmanned waste collection vehicles.

• International Journal of Automotive Technology
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• v.3 no.2
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• pp.71-78
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• 2002

A new control method far vision-based autonomous vehicle is proposed to determine navigation direction by analyzing lane information from a camera and to navigate a vehicle. In this paper, characteristic featured data points are extracted from lane images using a lane recognition algorithm. Then the vehicle is controlled using new Levenberg-Marquardt neural network algorithm. To verify the usefulness of the algorithm, another algorithm, which utilizes the geometric relation of a camera and vehicle, is introduced. The second one involves transformation from an image coordinate to a vehicle coordinate, then steering is determined from Ackermann angle. The steering scheme using Ackermann angle is heavily depends on the correct geometric data of a vehicle and a camera. Meanwhile, the proposed neural network algorithm does not need geometric relations and it depends on the driving style of human driver. The proposed method is superior than other referenced neural network algorithms such as conjugate gradient method or gradient decent one in autonomous lateral control .

• The Journal of Korea Robotics Society
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• v.18 no.1
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• pp.93-98
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• 2023

In this paper, the development of an autonomous electric vehicle for logistics with a robotic arm is introduced. The manual driving electric vehicle was converted into an electric vehicle platform capable of autonomous driving. For autonomous driving, an encoder is installed on the driving wheels, and an electronic power steering system is applied for automatic steering. The electric vehicle is equipped with a lidar sensor, a depth camera, and an ultrasonic sensor to recognize the surrounding environment, create a map, and recognize the vehicle location. The odometry was calculated using the bicycle motion model, and the map was created using the SLAM algorithm. To estimate the location of the platform based on the generated map, AMCL algorithm using Lidar was applied. A user interface was developed to create and modify a waypoint in order to move a predetermined place according to the logistics process. An A-star-based global path was generated to move to the destination, and a DWA-based local path was generated to trace the global path. The autonomous electric vehicle developed in this paper was tested and its utility was verified in a warehouse.