• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.871-875
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• 1996

The Output feedback linear quadratic regulator control is applied to the design of active suspension system using 7 DOF full car model. The performance index reflects the vehicle vertical movement, pitch and roll motion, and minimization of suspension stroke displacements in the rattle space. The elements of gain matrix are approximately decoupled so that each suspension requires only local information to generate the control force. The simulation results indicates that the output feedback LQ controller is more effective than purely passive or full state feedback active LQ controllers in following the road profile at the low frequency range and suppressing the road disturbance at the high frequency ranges.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1332-1335
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• 1996

It is very important to predict the future position for the heavy vehicle with evasive maneuvering. In this paper, we considered for the manual image tracking system. The vehicle images are received from gyro stabilized mirror system, pass through the optical lens, processed, and displayed on the TV monitor. The operator try to lay the reticle to the center of vehicle image. When the vehicle is moving, the mirror platform (actually the line of sight) should follow the vehicle and the angular rate information is picked up from the mirror stabilized system. This rate signal should be used to predict the future vehicle position. The problem is that the visual system of the human operator is in the closed loop system. The rate signals are disturbed by the operator. In addition, there are some non linearities concerned with the control handle bar and the servo control system. The proposed Kalman filter, combined with some modifications for operator disturbance rejection, improved the predication of the future vehicle position when compared with the conventional passive filter used.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.907-913
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• 1999

For an automated transportation system like PRT(Personal Rapid Transit) system or IVHS, an efficient vehicle-merging algorithm is required for smooth operation of the network. For management of merging, collision avoidance between vehicles, ride comfort, and the effect on traffic should be considered. This paper proposes an unmanned vehicle-merging algorithm that consists of two procedures. First, a longitudinal control algorithm is designed to keep a safe headway between vehicles in a single lane. Secondly, 'vacant slot and ghost vehicle' concept is introduced and a decision algorithm is designed to determine the sequence of vehicles entering a converging section considering energy consumption, ride comfort, and total traffic flow. The sequencing algorithm is based on fuzzy rules and the membership functions are determined first by an intuitive method and then trained by a learning method using a neural network. The vehicle-merging algorithm is shown to be effective through simulations based on a PRT model.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.11
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• pp.1065-1071
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• 2012

In this paper, we proposed a method for vehicle monitoring with trajectory reconstruction. For safety, it is important to monitor the driving habit of driver. Every year, many accidents occur due to the reckless driving of the driver. Continuous monitoring of the status of commercial vehicles is needed for safety through the entire path from start point to the destination. To monitor the reckless driving, we try to monitor the trajectory of the vehicle by using vehicle's lateral acceleration data. Compared with steering angle and lateral acceleration, these resemble each other. So, we find the relationship of steering angle and acceleration, and find the global direction of vehicle. We find the position of non-GPS section with EKF (External Kalman Filter) and reconstruct the whole trajectory during vehicle driving.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.6
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• pp.553-558
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• 2010

In this paper, we proposed a teleoperation scheme of unmanned grounded vehicle to improve telepresence. Especially, bilateral control architecture for transmitting realistic steering feeling to the remote driver is investigated. System architecture of the teleoperated remote vehicle is introduced with visual, auditory and kinesthetic haptic channel. Several bilateral control architectures are proposed for transmitting remote steering feeling, and subject tests are done to evaluate the performance. Position-force bilateral control architecture with returning torque compensation algorithm shows best performance.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.4
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• pp.372-378
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• 2009

For effective mobility control of unmanned ground vehicles in outdoor off-road environments, terrain cover classification technology using passive sensors is vital. This paper presents a novel method far terrain classification based on color and texture information of off-road images. It uses a neural network classifier and wavelet features. We exploit the wavelet mean and energy features extracted from multi-channel wavelet transformed images and also utilize the terrain class spatial coordinates of images to include additional features. By comparing the classification performance according to applied features, the experimental results show that the proposed algorithm has a promising result and potential possibilities for autonomous navigation.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.6
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• pp.524-531
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• 2010

The automobile networks consist of the communication bus systems which become independent and heterogeneous each other. Most often, the CAN buses are implemented in a car in order to connect all the electronic control units in various ways. Thus, some gateways are necessary for exchanging the useful information between electronic control units on the buses. The automobile body networks group is divided into two kinds on a large scale, namely the low-speed bus and the high-speed bus. To interchange messages between the two, a CAN signal gateway is designed and implemented in a miniature scale. A network analyzer (called "Vehicle spy") and an oscilloscope monitor network situation to confirm the due operation of CAN signal gateway. The efficiency of the designed gateway is evaluated. The more message thread increased, the more efficiency decreased.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.856-864
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• 2008

This paper describes a vehicle low speed driving assistant (VLDA) system that is composed of laser scanner. This vehicle is designed for following lead vehicle (LV) without driver's operation. The system is made up several component systems that are based on unmanned ground vehicle (UGV). Each component system is applied to use advanced safety vehicle developed to complete UGV system. VLDA system was divided into vehicle control system and obstacle detecting system. The obstacle detecting system calculate distance and angle of LV and transmit these data to vehicle control system using front, left and right laser scanners. Vehicle control system makes vehicle control values such as steering angle, acceleration and brake position and control vehicle's movement with steering, acceleration and brake actuators. In this research, we designed VLDA system like as low speed cruise control system and test it on real road environments.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.828-834
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• 2014

This paper presents a comparison among three types of approaches to an ARC (Active Roll Control) with an AARB(Active Anti-Roll Bar) for a vehicle system. Lateral acceleration and road profile are considered as disturbance. The ARC is designed with an LQ SOF (Linear Quadratic Static Output Feedback) control, $H_{\infty}$ control and SMC (Sliding Mode Control). These approaches are compared in terms of rollover prevention and ride comfort. For comparison, Bode plot analysis based on linear model and frequency response analysis based on CarSim simulation are performed.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.7
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• pp.679-688
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• 2008

This paper presents an algorithm capable of detecting leading vehicles using a forward-looking camera. In fact, the accurate measurements of the contact locations of vehicles with road surface are prerequisites for the intelligent vehicle technologies based on a monocular vision. Relying on multistage processing of relevant edge features to the hypothesis generation of a vehicle, the proposed algorithm creates candidate positions being the left and right boundaries of vehicles, and searches for pairs to be vehicle boundaries from the potential positions by evaluating horizontal symmetry. The proposed algorithm is proven to be successful by experiments performed on images acquired by a moving vehicle.