• Journal of Advanced Research in Ocean Engineering
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• v.1 no.2
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• pp.134-147
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• 2015

This study proposes a method to determine the effective angular velocity of each motor of a specific four-rows tracked vehicle (FRTV) in order to follow a given turning radius. The configuration of the four-rows tracked vehicle is introduced, and its dynamics analysis model is built using the DAFUL commercial software. The soil has been assumed to be hard ground, and the friction force between the ground and the tracked links is calculated using the Coulomb friction model. This paper uses a simulation to show that the error in the position increased with respect to the angle of the curvatures, so a method is proposed to compensate for the error in the motion of the motors. Various simulations are then carried out to verify the proposed formulation. The effects of the soil characteristics and the driving velocity will be further investigated in future studies.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.3
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• pp.113-121
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• 2011

Rollover accident is one of the serious traffic accident and rollover accident takes high portion of all accident. The most common type of rollover is a tripped rollover which occupy 95% of all type of single-vehicle rollover. Tripped rollover occurs when a vehicle leaves normal road way and tripped by loose gravel, soil of fixed object such as guard rail, curbs and ditches. And the rest of the type of rollover is un-tripped rollover. An un-tripped rollovers that occurs during high-speed collision avoidance maneuvers. In this paper, presents the explanation of the un-tripped rollover test method and procedure, additionally this paper deals with various occurrence in the un-tripped test such as occurring excessive tire camber in the un-tripped test, tire side-wall contact with road surface and roll oscillation. And this paper analyzes the analysis of the roll rate amplitude in specific frequency through the FFT (Fast Fourier Transform) and the roll angle at the steering reverse timing which is the Fishhook test roll rate feedback time. Finally, this paper analyzes the relations between the estimated steady state roll gain and rollover stability.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.10
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• pp.827-836
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• 2001

The PID controller has been widely applied to the most control systems because of its simple structure and east designing. One of the important points to design the PID control system is to tune the approximate control parameters for the given target system. To find the PID parameters using Ziegler Nichols(ZN) method needs a lot of experience and experiments to ensure the optimal performance. In this paper, CMIA(Cell Mediated Immune Algorithm) controller is proposed to drive the autonomous guided vehicle (AGV) more effectively. The proposed controller is based on specific immune responses of the biological immune system which is the cell mediated immunity. To verify the performance of the proposed CMIA controller, some experiments for the control of steering and speed of that AGV are performed. The tracking error of the AGV is mainly investigated for this purpose. As a result, the capability of realization and reliableness are proved by comparing the response characteristics of the proposed CMIA controllers with those of the conventional PID and NNPID(Neural Network PID) controller.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.12
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• pp.997-1003
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• 2016

This paper presents an application of adaptive algorithms for yaw moment distribution with electronic stability control (ESC) and active rear steering (ARS) in integrated chassis control (ICC). Integrated chassis control consists of upper- and lower-level controllers. In the upper-level controller, the control yaw moment is computed with sliding mode control required to stabilize a vehicle. In the lower-level controller, adaptive algorithms are applied to determine the required brake pressure of ESC and the necessary steering angle of ARS, in order to generate the control yaw moment. Simulation is performed using the vehicle simulation package CarSim to validate the proposed method.

• Journal of the Korean Society for Railway
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• v.10 no.3 s.40
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• pp.257-263
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• 2007

The critical speed above which the vehicle become unstable is one of the items that should be verified in the development of a new train. In the case of a high speed tilting train, which requires both higher critical speed and higher curving speed, the critical speed should be more carefully treated because the both requirements are in conflict with each other in the conventional train design. The main purpose of the present work is to estimate the linear and non-linear critical speeds of 200km/h Korean Tilting Train 'Hanbit200' under development. The newly developed self-steering mechanism was attached to the tilting train to ensure that the critical speed falls under the lower yaw stiffness which is needed to secure higher curving performance. The simulation for predicting the critical speed was done by a commercially available vehicle dynamics software. A full scale roller rig test was carried out to validate the numerical results and to verify the effectiveness of the self-steering mechanism.

• Journal of Sensor Science and Technology
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• v.10 no.2
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• pp.134-141
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• 2001

This paper describes a method to steer an autonomous electric vehicle using magnetic fields. Magnets are embeded along the center of the road and a magneto-resistive sensor is mounted beneath the front bumper of the vehicle. As the vehicle moves along the road neural network controller controls the vehicle using measured magnetic field variation. Based on a single magnets modeling equation, we analyzed three dimensional magnetic field distributions of embeded magnets in series on the center of the road and performed a computer simulation using this results. In simulation study, straight and curved road was configured. The steering controller for the vehicle was designed using neural network and experiment was performed on the real embeded magnets using real autonomous electric vehicle. At the experiment we compensated the earth's magnetic fields and showed a good result driving an autonomous vehicle using proposed method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.219-230
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• 2017

This paper proposes a vehicle to road tracking algorithm based on vision sensor by using EKF(Extended Kalman Filter). The lateral offset, heading angle, and curvature which are obtained from vehicle to road tracking might be used as inputs to steering controller of LKAS(Lane Keeping Assist System) or for the warning decision logic of LDWS(Lane Departure Warning System). To the end, in this paper, the yaw rate, steering angle, and vehicle speed as well as lane raw points together with considering of vehicle lateral dynamics are utilized to improve the exactness and convergence of the vehicle to road tracking. The proposed algorithm has been tested at a proving ground that consists of straight and curve sections and compared with GPS datum using DGPS-RTK equipment to show the feasibility of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.487-490
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• 2003

In this research, we will devise an obstacle avoidance algorithm for a previously unmanned vehicle. Whole systems consist mainly of the vehicle system and the control system. The two systems are separated; this system can communicate with the vehicle system and the control system through wireless RF (Radio Frequency) modules. These modules use wireless communication. And the vehicle system is operated on PIC Micro Controller. Obstacle avoidance method for unmanned vehicle is based on the Virtual Force Field (VFF) method. An obstacle exerts repulsive forces and the lane center point applies an attractive force to the unmanned vehicle. A resultant force vector, comprising of the sum of a target directed attractive force and repulsive forces from an obstacle, is calculated for a given unmanned vehicle position. With resultant force acting on the unmanned vehicle, the vehicle's new driving direction is calculated, the vehicle makes steering adjustments, and this algorithm is repeated.

• Journal of Mechanical Science and Technology
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• v.16 no.10
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• pp.1253-1263
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• 2002

The control system design and modeling of an unmanned vehicle by means of a new concept for better performance through a tole-operation system is suggested by sensor fusion. But, the control of a real vehicle is very difficult, because the system identification of the vehicle is hard to find the unknown factors and the disturbances of the experimental environment. For the longitudinal and lateral controls, the traction system and steering system models are set up and a tuning method to find the gain of the controller by experiments is presented. In this research, mechanical and electronic parts are implemented to operate the unmanned vehicle and data reconstruction method of information about the environment data coming from several sensors is presented by data plot for the vehicle navigation. This paper focuses on the integration of tole-operated unmanned vehicle. This vehicle mainly controlled lateral and longitudinal directions with actuators for controlling vehicle movement and sensors for the closed-loop controlled system.

• Journal of Auto-vehicle Safety Association
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• v.10 no.1
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• pp.38-44
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• 2018

This paper presents an analysis on driving safety in lane change situation based on road driving data. Autonomous driving is a global trend in vehicle industry. LKAS technologies are already applied in commercial vehicle and researches about lane change maneuver have been actively studied. In autonomous vehicle, not only safety control issue but also imitating human driving maneuver is important. Driving data analysis in lane change situation has been usually dealt with ego vehicle information such as longitudinal acceleration, yaw rate, and steering angle. For this reason, developing safety index according to surrounding vehicle information based on human driving data is needed. In this research, driving data is collected from perception module using LIDAR, radar and RT-GPS sensors. By analyzing human driving pattern in lane change maneuver, safety index that considers both ego vehicle and surrounding vehicle state by using relative velocity and longitudinal clearance has been designed.