• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.3
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• pp.28-34
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• 2006

An ACC driving simulator is a virtual reality device which designed to test or evaluate vehicle control algorithm. It is designed and built based on the rapid control prototyping(RCP) concept. Therefore this simulator adopt RCP tools to solve the equation of a vehicle dynamics model and control algorithm in real time, rendering engine to provide real-time visual representation of vehicle behavior and CAN communication to reduce networking load. It can provide also many different driving test environment and driving scenarios.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.5
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• pp.550-557
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• 1999

This paper describes a road-following controller using the proposed neural network for autonomous vehicle. Road-following with visual sensor like camera requires intelligent control algorithm because analysis of relation from road image to steering control is complex. The proposed neural network, relative similarity modular network(RSMN), is composed of some learning networks and a partitioniing network. The partitioning network divides input space into multiple sections by similarity of input data. Because divided section has simlar input patterns, RSMN can learn nonlinear relation such as road-following with visual control easily. Visual control uses two criteria on road image from camera; one is position of vanishing point of road, the other is slope of vanishing line of road. The controller using neural network has input of two criteria and output of steering angle. To confirm performance of the proposed neural network controller, a software is developed to simulate vehicle dynamics, camera image generation, visual control, and road-following. Also, prototype autonomous electric vehicle is developed, and usefulness of the controller is verified by physical driving test.

• Journal of Navigation and Port Research
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• v.28 no.3
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• pp.227-232
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• 2004

Vehicle dynamics control systems are complex and non-linear, so they have difficulties in developing a controller for the anti-lock braking systems and the auto-traction systems. Currently the fuzzy-logic technique to estimate the absolute vehicle speed supplies good results in normal conditions. But the estimation error in severe braking is discontented In this paper, we estimate the absolute vehicle speed of UCT(Unmanned Container Transporter) by using the wheel speed data from standard anti-lock braking system wheel speed sensors. Radial symmetric basis function of the neural network model is proposed to implement and estimate the absolute vehicle speed, and principal component analysis on input data is used 10 algorithms are verified experimentally to estimate the absolute vehicle speed and one of them is perfectly shown to estimate the vehicle speed within 4％ error during a braking maneuver.

• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.3
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• pp.45-53
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• 1998

Traction control systems(TCS) improve vehicle acceleration performance and stability, particularly on slippery roads through engine torque and/or brake torque control. This research mainly deals with the engine control algorithm based on adjustment of the engine throttle valve opening. Hardware-in-the-loop simulation(HWILS) is carried out where the actual hardware is used for the engine/automatic transmission and TCS controller, while various vehicle dynamics are simulated on real-time basis. Also, use of the dynamometer is made in order to implement the tractive force that a road applies to the tire. Although some restrictions are imposed mainly due to the capability of the synamometer, simplified HWILS results show that the slip control algorithm can improve the vehicle acceleration performance for low-friction roads.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.410-413
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• 2004

In this paper, a simulator system for Fuel Cell Hybrid Electric Vehicles(FCHEV) is implemented using DSP boards with CAN bus. The subsystems of a FCHEV i.e., the fuel cell system, the battery system, the vehicle dynamics with the transmission mechanism are coded into 3 DSP boards. The power distribution control algorithm and battery SOC control are also coded into a DSP board. The real-time monitoring program is also developed to examine the control performance of power control and SOC control algorithms.

• Journal of the Korean Society of Mechanical Technology
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• v.13 no.2
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• pp.45-54
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• 2011

A vehicle suspension system performs two functions, the ride quality and the stability, which conflict with each other. Among the various suspension systems, an active suspension system has an external energy source, from which energy is always supplied to the system for continuous control of vehicle motion. In the process of the linearization for the nonlinear active suspension system, the frequency dependent damping method is used for the exact modelling to the real model. The pressure control valve which is controlled by proportional solenoid is the most important component in the active suspension system. The pressure control valve has the dynamic characteristics with 1st order delay. Therefore, It's necessary to adopt the lead compensator to compensate the dynamics of the pressure control valve. The sampling time is also important factor for the control performances. The sampling time value is proposed to satisfy the system performances. After the modelling and simulation for the pressure control valve and vehicle dynamic, the performances of the vehicle ride quality and the stability are enhanced.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.3
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• pp.205-211
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• 2017

To achieve an advanced control of automobiles, it is necessary to acquire the values of the parameters of a vehicle in real time to conduct precise vehicle control practices such as automatic platooning control. Vehicle control is especially required in controlling trucks, as the mass and inertia change widely according to the loading conditions. Thereafter, we propose to estimate the yaw moment of inertia of the truck in real-time during travelling, by applying the dual Kalman filter algorithm, which estimates the state variables and values of the parameters simultaneously in real-time. The simulation results show that the proposed method is effective for the estimation, which uses commercial software for simulating and analyzing the vehicle dynamics.

• Journal of Auto-vehicle Safety Association
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• v.5 no.2
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• pp.24-31
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• 2013

This paper describes a coordinated control algorithm for rear-side collision avoidance. In order to assist driver actively and increase driver's safety, the proposed coordinated control algorithm is designed to combine lateral control using a steering torque overlay by Motor Driven Power Steering (MDPS) and differential braking by Vehicle Stability Control (VSC). The main objective of a combined control strategy is twofold. The one is to prevent the collision between the subject vehicle and approaching vehicle in the adjacent lanes. The other is to limit actuator's control inputs and vehicle dynamics to safe values for the assurance of the driver's comfort. In order to achieve these goals, the Lyapunov theory and LMI optimization methods has been employed. The proposed coordinated control algorithm for rear-side collision avoidance has been evaluated via simulation using CarSim and MATLAB/Simulink.

• Transactions of the Korean Society of Automotive Engineers
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• v.17 no.2
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• pp.1-9
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• 2009

A parking-assist system is defined that a driver adjusts vehicle velocity through brake pedal operation and parking-assist system controls the motion of the vehicle to follow a collision-free path. In this study, a motion control algorithm using Fuzzy inference is proposed to track a maneuvering clothoid parallel path. Simulations are performed under SIMULINK environments using MATLAB and CarSim for a vehicle model. As the vehicle model in MATLAB a bicycle model is used including lateral dynamics. The simulation results show that the path tracking performance is satisfactory under various driving and initial conditions.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.722-728
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• 1998

In this paper real-time estimation methods for identifying the tire-road friction coefficient are presented. Taking advantage of the Magic Formula Tire Model, the similarity technique and the specific model for the vehicle dynamics, a reduced order observer/filtered-regressor-based method is proposed. The Proposed method is evaluated on simulations of a full-vehicle model with an eight state nonlinear vehicle/transmission model and nonlinear suspension model. It has been shown through simulations that it is possible to estimate the tire-road friction from measurements of engine rpm, transmission output speed and wheel speeds using the proposed identification method. The proposed method can be used as a useful option as a part of vehicle collision warning/avoidance systems and will be useful in the implementation of a warning algorithm since the tire-road friction can be estimated only using RPM sensors.