• Journal of Auto-vehicle Safety Association
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• v.14 no.1
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• pp.39-44
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• 2022

This paper presents a development of throttle and brake controller for autonomous vehicle simulation environment. Most of 3D simulator control autonomous vehicle by throttle and brake command. Therefore additional longitudinal controller is required to calculate pedal input from desired acceleration. The controller consists of two parts, feedback controller and feedforward controller. The feedback controller is designed to compensate error between the actual acceleration and desired acceleration calculated from autonomous driving algorithm. The feedforward controller is designed for fast response and the output is determined by the actual vehicle speed and desired acceleration. To verify the performance of the controller, simulations were conducted for various scenarios, and it was confirmed that the controller can successfully follow the target acceleration.

• International Journal of Automotive Technology
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• v.5 no.2
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• pp.135-144
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• 2004

In this paper, the model-matching control in the longitudinal autonomous driving system is investigated by vehicle dynamics simulation, which contains nonlinear subcomponents and simplified subcomponents. The design of the robust model-matching controller is performed by the characteristics of the 2 degrees of freedom controller, which is composed of the feedforward compensator and the feedback compensator. It makes the characteristics of tractive and brake force to be equivalent to the specific transfer function, which is suggested as the reference model. Mathematical models of vehicle dynamic analysis including the model-matching control are constructed for computer simulation. Then, simple examples on open-loop simulation without any controller and closed loop simulation with the model-matching controller are applied to check the validity of the robust controller. As the practical example, the autonomous driving system in the longitudinal direction is adopted. It is proved that the model-matching control is effective and adequate to the disturbances and the perturbations, which are shown in the responses of the change of a vehicle mass and a road gradient.

• Journal of Auto-vehicle Safety Association
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• v.11 no.2
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• pp.11-16
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• 2019

This paper suggests an algorithm for detecting fault of longitudinal controller in autonomous vehicles. Guaranteeing safety in fault situation is essential because electronic devices in vehicle are dependent each other. Several methods like alarm to driver, ceding control to driver, and emergency stop are considered to cope with fault. This research investigates the fault monitoring process in fail-safe system, for controller which is responsible for accelerating and decelerating control in vehicle. Residual is computed using desired acceleration control command and actual acceleration, and detection of its abnormal increase leads to the decision that system has fault. Before computing residual for controller, health monitoring process of acceleration signal is performed using hardware and analytic redundancy. In fault monitoring process for controller, a process model which is fitted using driving data is considered to improve the performance. This algorithm is simulated via MATLAB tool to verify performance.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.861-866
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• 2007

This paper presents development of a vehicle lateral and longitudinal control for autonomous driving control and test results obtained using an electric vehicle. Sliding control theory has been used to develop a vehicle speed and distance control algorithm. The longitudinal control algorithm that maintains safety and comfort of the vehicle consists of a cruise and STOP&GO control depending on traffic conditions. Desired steering angle is determined through the lateral position error and the yaw angle error based on preview optimal control. Motor control inputs have been directly derived from the sliding control law. The performance of the autonomous driving control which is integrated with a lateral and longitudinal control is investigated by computer simulations and driving test using an electric vehicle. Electric vehicle system consists of DC driving motor, an electric power steering system, main controller (Autobox)

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.73-82
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• 2022

Driver acceptance of autonomous driving is very important. The autonomous driving longitudinal controller, which is one of the factors affecting acceptability, consists of a high-level controller and a low-level controller. The host controller decides the cruise control and the space control according to the situation and creates the required target speed. The sub-controller performs control by creating an acceleration signal to follow the target speed. In this paper, we propose an algorithm to improve the inter-vehicle distance fluctuations that occur in the cruise control and space control switching problems in the host controller. The proposed method is to add an approach algorithm to the cruise control at the time of switching from cruise control to space control so that it is switched to space control at the correct switching distance. Through this, the error was improved from 12m error to 4m, and actual vehicle verification was performed.

• Journal of Auto-vehicle Safety Association
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• v.12 no.2
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• pp.27-32
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• 2020

This paper presents steering system requirements to ensure the stabilized lateral control of autonomous driving vehicles. The two main objectives of a lateral controller in autonomous vehicles are maintenance of vehicle stability and tracking of the desired path. Even if the desired steering angle is immediately determined by the upper level controller, the overall controller performance is greatly influenced by the specification of steering system actuators. Since one of the major inescapable traits that affects controller performance is the time delay of the steering actuator, our work is mainly focused on finding adequate parameters of high level control algorithm to compensate these response characteristics and guarantee vehicle stability. Actual vehicle steering angle response was obtained with Electric Power Steering (EPS) actuator test subject to various longitudinal velocity. Steering input and output response analysis was performed via MATLAB system identification toolbox. The use of system identification is advantageous since the transfer function of the system is conveniently obtained compared with methods that require actual mathematical modeling of the system. Simulation results of full vehicle model suggest that the obtained tuning parameter yields reduced oscillation and lateral error compared with other cases, thus enhancing path tracking performance.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.39-52
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• 2021

This paper presents a longitudinal acceleration controller that can be applied to real vehicles (nonlinear and time-varing systems) with only a simple experiment regardless of the type of vehicle and the control interface structure. The controller consists of a feedforward term for fast response, a zero-throttle acceleration compensation term, and a feedback term (P gain) to compensate for errors in the feedforward term, and another feedback term (I gain) to respond to disturbances such as slope. In order to easily apply it to real vehicles, there are only two tuning parameters, feedforward terms of throttle and brake control. And the remaining parameters can be calculated immediately when the two parameters are decided. The tuning procedure is also unified so that it can be quickly and easily applied to various vehicles. The performance of the controller was evaluated using MATLAB/Simulink and Truksim's European Ben model. In addition, the controller was successfully implemented to 3 medium-sized vehicle (HMC Solati), which is composed of different control interface characteristic. Vehicle driving performance was evaluated on the test track and on the urban roads in Siheung and Seoul.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.129-143
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• 2021

This paper proposes actuator fault detection and adaptive fault-tolerant control algorithms using performance index and human-like learning for longitudinal autonomous vehicles. Conventional longitudinal controller for autonomous driving consists of supervisory, upper level and lower level controllers. In this paper, feedback control law and PID control algorithm have been used for upper level and lower level controllers, respectively. For actuator fault-tolerant control, adaptive rule has been designed using the gradient descent method with estimated coefficients. In order to adjust the control parameter used for determination of adaptation gain, human-like learning algorithm has been designed based on perceptron learning method using control errors and control parameter. It is designed that the learning algorithm determines current control parameter by saving it in memory and updating based on the cost function-based gradient descent method. Based on the updated control parameter, the longitudinal acceleration has been computed adaptively using feedback law for actuator fault-tolerant control. The finite window-based performance index has been designed for detection and evaluation of actuator performance degradation using control error.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.2162-2169
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• 2015

Cruise control is a technology for automatically maintaining a steady speed of vehicle as set by the driver via controlling throttle valve and brake of vehicle. In this paper we investigate cruise controller design method with consideration for distance to vehicle ahead. We employ linear time varying (LTV) model to describe longitudinal vehicle dynamic motion. With this LTV system we approximately model the nonlinear dynamics of vehicle speed by frequent update of the system parameters. In addition we reformulate the LTV system by transforming distance to leading vehicle into variation of system parameters of the model. Note that in conventional control problem formulation this distance is considered as disturbance which should be rejected. Consequently a controller can be designed by pole placement at each instance of parameter update, based on the linear model with the present system parameters. The validity of this design method is examined by simulation study.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.2
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• pp.92-101
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• 2000

The objective of this paper is to design the controller for longitudinal vehicle following which makes the vehicle follow the lead vehicle and keeps a safety distance without human driver operation. This paper presents a sliding mode control algorithm for the ACC system. The controller is based on three sliding surfaces. Each surface plays an individual control-deviation control, throttle control and brake control. In addition to sliding mode control, we propose some additional schemes to enhance controller performance. The first one is a gear shift-down controller which makes tractive force increase with a change of gear ratio. The other is a predictive correction method which reduces slinky effect.