• Journal of Power System Engineering
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• v.8 no.4
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• pp.57-63
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• 2004

Conventionally, 2WS is used for vehicle steering, which can only steering front wheel. In case of trying to high speed lane change or cornering through this kind of vehicle equipped 2WS, it may occur much of Yaw moment. On the other hand, 4WS makes decreasing of Yawing Moment, outstandingly, so it is possible to support vehicle movement stable. And conventional ABS and TCS can only possible to control the longitudinal movement of braking equipment and drive which can only available to control of longitudinal direction. There after new braking system ESP was developed, which controls both of longitudinal and lateral, with adding of the function of controlling Active Yaw Moment. On this paper, we show about not only designing of improved braking and steering system through establishing of the integrated control system design of 4WS and ESP but also designing of the system contribute to precautious for advanced vehicle stability problem.

• Journal of Auto-vehicle Safety Association
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• v.12 no.4
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• pp.13-22
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• 2020

This paper presents an adaptive feedback based actuator fault detection and tolerant control algorithms for longitudinal functional safety of autonomous driving. In order to ensure the functional safety of autonomous vehicles, fault detection and tolerant control algorithms are needed for sensors and actuators used for autonomous driving. In this study, adaptive feedback control algorithm to compute the longitudinal acceleration for autonomous driving has been developed based on relationship function using states. The relationship function has been designed using feedback gains and error states for adaptation rule design. The coefficients in the relationship function have been estimated using recursive least square with multiple forgetting factors. The MIT rule has been adopted to design the adaptation rule for feedback gains online. The stability analysis has been conducted based on Lyapunov direct method. The longitudinal acceleration computed by adaptive control algorithm has been compared to the actual acceleration for fault detection of actuators used for longitudinal autonomous driving.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.1
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• pp.216-221
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• 2004

This paper describes a fault detection and fault handling algorithm to be used in a longitudinal vehicle cruise control systems. The fault diagnosis system consists of two structures to generate proper residuals and to find that which component has a fault. A systematic design of the fault diagnosis system using model-based techniques is presented. A linear observer is used to create a set of signals sensitive to faults in a radar sensor. The fault handling system consists of two structures to compensate for faults and degraded system performance. Simulation results show that the algorithm is effective for a fault diagnosis and handling in a longitudinal vehicle cruise control system.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.1
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• pp.215-215
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• 2004

This paper describes a fault detection and fault handling algorithm to be used in a longitudinal vehicle cruise control systems. The fault diagnosis system consists of two structures to generate proper residuals and to find that which component has a fault. A systematic design of the fault diagnosis system using model-based techniques is presented. A linear observer is used to create a set of signals sensitive to faults in a radar sensor. The fault handling system consists of two structures to compensate for faults and degraded system performance. Simulation results show that the algorithm is effective for a fault diagnosis and handling in a longitudinal vehicle cruise control system.

• 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 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.

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.4
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• pp.180-189
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• 2009

Currently, most automobile companies are interested in research on intelligent autonomous vehicle. They are mainly focused on driver's intelligent assistant and driver replacement. In order to develop an autonomous vehicle, lateral and longitudinal control is necessary. This paper presents a lateral and longitudinal control system for autonomous vehicle that has only mono-vision camera. For lane detection, we present a new lane detection algorithm using clothoid parabolic road model. The proposed algorithm in compared with three other methods such as virtual line method, gradient method and hough transform method, in terms of lane detection ratio. For adaptive control, we apply a vanishing point estimation to fuzzy control. In order to improve handling and stability of the vehicle, the modeling errors between steering angle and predicted vanishing point are controlled to be minimized. So, we established a fuzzy rule of membership functions of inputs (vanishing point and differential vanishing point) and output (steering angle). For simulation, we developed 1/8 size robot (equipped with mono-vision system) of the actual vehicle and tested it in the athletics track of 400 meter. Through the test, we prove that our proposed method outperforms 98 % in terms of detection rate in normal condition. Compared with virtual line method, gradient method and hough transform method, our method also has good performance in the case of clear, fog and rain weather.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.5
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• pp.137-144
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• 2000

In this paper, a longitudinal control of the lead vehicle for a platoon in IVHS Regulation Layer is proposed. The backstepping method has been used for the controller design. This method has an advantage in that its stability need not be proven since the controller is designed based on the Lyapunov Function. The control object is that the lead vehicle tracks a reference velocity and maintains a safe distance between the inter-platoons while the followers are keeping the speed of the lead vehicle of a platoon. The coordinate of system is transformed to a new coordinate system for its convenience to design controller. The new coordinate system is composed of error and new error variable. The error is the difference between the safe distance and the actual distance of inter-platoons. A new error variable is the difference between the velocity of vehicle and the estimated state of a system operated by the virtual input. The Lyapunov function is obtained based on the variables of new coordinate system. In the computer simulation, several cases have been studied such as when the lead vehicle is tracking the optimal speed. or a lead vehicle of the following platoon tracks the velocity of the previous platoon while maintaining a safe distance. Also a nonlinear engine time constant case has been investigated. All the simulation results show that the designed controller satisfies the control object sufficiently.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.6
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• pp.227-233
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• 2002

A vehicle longitudinal control strategy with guaranteed string stability for vehicle stop-and-go(SG) cruise control is presented in this paper. The SG cruise control systems should be designed such that string stability can be guaranteed in addition to that every vehicle in a string of SG cruise control vehicles must track any bounded acceleration and velocity profile of its preceding vehicle with a bounded spacing and velocity error. An optimal vehicle following control law based on the information of the 1311owing distance (clearance) and its velocity relative to the vehicle ahead (relative velocity) has been used and string stability analysis has been done based on the control law and constant time gap spacing policy, A validated multi-vehicle simulation package has been shown that the string stability analysis using the approximate model of the vehicle servo-loop which includes vehicle powertrain and brake control system dynamics is valid in the design of the SG cruise control law with guaranteed string stability.

• Journal of Advanced Navigation Technology
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• v.11 no.4
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• pp.359-370
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• 2007

Lane tracking and obstacle avoidance are considered two of the key technologies on an unmanned ground vehicle system. In this paper, we propose a method of lane tracking and obstacle avoidance, which can be expressed as vehicle control, modeling, and sensor experiments. First, obstacle avoidance consists of two parts: a longitudinal control system for acceleration and deceleration and a lateral control system for steering control. Each system is used for unmanned ground vehicle control, which notes the vehicle's location, recognizes obstacles surrounding it, and makes a decision how fast to proceed according to circumstances. During the operation, the control strategy of the vehicle can detect obstacle and perform obstacle avoidance on the road, which involves vehicle velocity. Second, we explain a method of lane tracking by means of a vision system, which consists of two parts: First, vehicle control is included in the road model through lateral and longitudinal control. Second, the image processing method deals with the lane tracking method, the image processing algorithm, and the filtering method. Finally, in this paper, we propose a method for vehicle control, modeling, lane tracking, and obstacle avoidance, which are confirmed through vehicles tests.