• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.240-257
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• 2022

Autonomous vehicles use various local sensors such as camera, radar, and lidar to perceive the surrounding environment. However, it is difficult to predict the movement of vulnerable road users using only local sensors that are subject to limits in cognitive range. This is true especially when these users are blocked from view by obstacles. Hence, this paper developed an algorithm for collision avoidance with VRU using V2X information. The main purpose of this collision avoidance system is to overcome the limitations of the local sensors. The algorithm first evaluates the risk of collision, based on the current driving condition and the V2X information of the VRU. Subsequently, the algorithm takes one of four evasive actions; steering, braking, steering after braking, and braking after steering. A simulation was performed under various conditions. The results of the simulation confirmed that the algorithm could significantly improve the performance of the collision avoidance system while securing vehicle stability during evasive maneuvers.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.11
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• pp.1291-1297
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• 2014

This paper proposes integrated chassis control (ICC) with electronic stability control (ESC) and active rear steering (ARS). Direct yaw moment control is used to generate a control yaw moment. A weighted pseudo-inverse-based control allocation (WPCA) method is adopted to distribute the control yaw moment into tire forces, generated by ESC and ARS. Simulation-based tuning of variables weights in the WPCA is used to enhance the yaw moment distribution performance. Simulations using the vehicle simulation software $CarSim^{(R)}$ show that the proposed ICC is effective in improving maneuverability and lateral stability.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.4
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• pp.295-301
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• 2012

This paper deals with the design of robust DSMC (Discrete-Time Sliding Mode Control) scheme in order to overcome system uncertainty in steering system with mechanically joined structure. The proposed control scheme is one of robust control schemes based on system dynamics. Therefore, system dynamics required is not obtained from physical law but SCM (Signal Compression Method) through experiment in order to avoid complicate mathematical development and save time. However, SCM has a shortcoming that is the limitation of with $2^{nd}$ order linear model which does not include the dynamic of high-frequency band. Thus, considering system uncertainty, DSMC is designed. In addition, to reduce the chattering problem of DSMC, DSMC is derived from the reaching law and the Lyapunov stability condition. It is found that the proposed control scheme has robustness in spite of the perturbation of system uncertainty through computer simulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.834-841
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• 2020

Among the autonomous driving systems based on visual sensors, the control method using a vanishing point is the most general method for autonomous driving. However, if the lane is lost or does not exist, it is very difficult to detect this and estimate the vanishing point. In this paper, we predict the vanishing point of the road and the vanishing point lines on the left and right sides using CNN for the camera image and design the steering controller for autonomous driving from the predicted results. As a result of the simulation, it was confirmed that the proposed method well tracked the center of the road regardless of the presence or absence of a solid lane, and was superior to the control method using a general method using the vanishing point.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.3
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• pp.645-650
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• 2010

In this paper we present the Bimodal-tram simulator using the PXI embedded real-time controllers. The Bimodal-tram is developed in KRRI (Korea Railroad Research Institute). The vehicle can be automatically operated by navigation control system (NCS). For the automatic driving, the vehicle lanes will be marked with permanent magnets that are placed in the ground. The vehicle is controlled by NCS. NCS governs the manual mode and automatic mode driving. The simulator is designed by an identical conception with the real control condition. The dynamic motion of vehicle is simulated by the nonlinear dynamic model. The control computer calculates the control values. The signal interface is linked by CAN communication. The simulation is processed by real-time base. The test driver can see the graphic motion of vehicle and can operate the steering wheel, gas and brake pedal to control direction and velocity of vehicle during the simulation. At present, the simulator is only operated by manual mode. The automatic mode will be linked after the control algorithm is finished. We will use the simulator to develop the control algorithm in the automatic mode. This paper shows the simulator designed for Bimodal-tram using real-time based controller. The results of the test using the simulator are presented and discussed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.11 s.170
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• pp.1960-1969
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• 1999

This paper presents dynamic modeling and controller design of a tracked vehicle installed with the double rod type ERSU(electro-rheological suspension unit). A 16 degree-of-freedom model for the tracked vehicle is established by Lagrangian method followed by the formulation of a new sky-ground hook controller. This controller takes account for both the ride quality and the steering stability. The weighting parameter between the two performance requirements is adopted to adjust required performance characteristics with respect to the operation conditions such as road excitation. The parameter is appropriately determined by employing a fuzzy algorithm associated with the vehicle motion. Computer simulations are undertaken in order to demonstrate the effectiveness of the proposed control system. Acceleration values at the driver's seat are analyzed under bump road profile, while frequency responses of vertical acceleration are investigated under random road excitation.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.5
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• pp.568-575
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• 2015

A hand-made vehicle with a formula (VF-1) was designed and manufactured with the aim of realizing a lightweight and high-performance vehicle. The driver's body weight and stiffness of the frame were considered. The vehicle was equipped with a one-cylinder Exiv 250 engine with intake manifold potting for realizing weight reduction, high performance, and low cost. The suspension system for the formula was designed through the analyses and tests of vehicle motion and equipment. In a steering system, anti-Ackerman geometry was introduced to increase the transverse force during cornering. A full electric paddle shift system was adopted to decrease the braking distance. For protection against the distortion and warping of the frame, tungsten inert gas (TIG) welding technology was used.

• Journal of Power Electronics
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• v.13 no.4
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• pp.536-545
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• 2013

In this study, an integrated motor control algorithm for an in-wheel electric vehicle is suggested. It consists of slip control that controls the in-wheel motor torque using the road friction coefficient and slip ratio; yaw rate control that controls the in-wheel motor torque according to the road friction coefficient and the yaw rate error; and velocity control that controls the vehicle velocity by a weight factor based on the road friction coefficient and the yaw rate error. A co-simulator was developed, which combined the vehicle performance simulator based on MATLAB/Simulink and the vehicle model of CarSim. Based on the co-simulator, a human-in-the-loop simulation environment was constructed, in which a driver can directly control the steering wheel, the accelerator pedal, and the brake pedal in real time. The performance of the integrated motor control algorithm for the in-wheel electric vehicle was evaluated through human-in-the-loop simulations.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.3
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• pp.253-259
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• 2014

This study proposes a map-based control method to improve a vehicle's lateral stability, and the performance of the proposed method is compared with that of the conventional model-referenced control method. Model-referenced control uses the sliding mode method to determine the compensated yaw moment; in contrast, the proposed map-based control uses the compensated yaw moment map acquired by vehicle stability analysis. The vehicle stability region is calculated by a topological method based on the trajectory reversal method. The performances of model-referenced control and map-based control are compared under various road conditions and driving inputs. Model-referenced control uses a control input to satisfy the linear reference model, and it generates unnecessary tire lateral forces that may lead to worse performance than an uncontrolled vehicle with step steering input on a road with low friction coefficient. The simulation results show that map-based control provides better stability than model-referenced control.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.05a
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• pp.57-62
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• 2003

This paper describes the design and simulation of a multivariable optimal control system for the combined speed, heading and depth control of a Semi-Autonomous Underwater Vehicle (SAUV) developed in Korea Ocean Research and Development Institute (KRODI). The SAUV is a test-bed for the evaluation of the navigation and manipulator technologies developed for a mine disposal vehicle (MDV) in military use and for a light working underwater vehicle in scientific use. The vehicle was designed to control its cruising speed, heading and depth with 4 horizontal thrusters installed at the rear of the hull. Therefore, the decoupled control methods are limited to apply to the SAUV because the thrust forces are highly coupled with the surging, yawing, and pitching motion of the vehicle. The multivariable Linear Quadratic (LQ) control method is chosen to control steering and diving in variable speed motion automatically. A series of simulation is carried out with fully nonlinear six degree of freedom dynamic model to validate the controller.