• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.12
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• pp.651-658
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• 2000

This paper presents a new method to extract traffic information such as number of passing vehicles and average speed by a pair of stereo road images. The whole process consists of the extraction of vehicles and the tracking of the extracted vehicles. For the extraction of vehicles, the outline of each vehicle is obtained by using binary region growing technique applied to disparity map based on multi-resolution stereo matching. The Kalman filter tracking algorithm is applied to the extracted vehicle outlines to determine the flow of vehicles. Experimental results show that the proposed method significantly improved recognition rate of vehicles over the conventional methods-frame difference and background elimination methods.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.815-818
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• 1997

In this paper, an intelligent control strategy for a mobile vehicle, based on the technology of the artificial neural network in a Neurocomputer, is presented. The mobile vehicle learned recognizing and driving knowledge by a neurocomputer. Moment Invariants computation was used to extract the shape of objects. The technologies of both neurocomputer and Neumann-type computer are applied into the control system, and make the mobile vehicle be capable of tracking designated objects and avoiding obstacles.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.265-274
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• 2012

In this paper, we propose a method for preceding vehicle detection and tracking with motion estimation by radar-vision sensor fusion. The motion estimation proposed results in not only correction of inaccurate lateral position error observed on a radar target, but also adaptive detection and tracking of a preceding vehicle by compensating the changes in the geometric relation between the ego-vehicle and the ground due to the driving. Furthermore, the feature-based motion estimation employed to lessen computational burden reduces the number of deployment of the vehicle validation procedure. Experimental results prove that the correction by the proposed motion estimation improves the performance of the vehicle detection and makes the tracking accurate with high temporal consistency under various road conditions.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.219-230
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• 2017

This paper proposes a vehicle to road tracking algorithm based on vision sensor by using EKF(Extended Kalman Filter). The lateral offset, heading angle, and curvature which are obtained from vehicle to road tracking might be used as inputs to steering controller of LKAS(Lane Keeping Assist System) or for the warning decision logic of LDWS(Lane Departure Warning System). To the end, in this paper, the yaw rate, steering angle, and vehicle speed as well as lane raw points together with considering of vehicle lateral dynamics are utilized to improve the exactness and convergence of the vehicle to road tracking. The proposed algorithm has been tested at a proving ground that consists of straight and curve sections and compared with GPS datum using DGPS-RTK equipment to show the feasibility of the proposed algorithm.

• ETRI Journal
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• v.38 no.2
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• pp.356-365
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• 2016

This research proposes a modified particle filter to increase the accuracy of vehicle tracking in a noisy and occluded medium. In our proposed method for vehicle tracking, the direction angle of a target vehicle is calculated. The angular difference between the motion direction of the target vehicle and each particle of the particle filter is observed. Particles are filtered and weighted depending on their angular distance to the motion direction. Those particles moving in a direction similar to that of the target vehicle are assigned larger weights; this, in turn, increases their probability in a given likelihood function (part of the process of estimation of a target's state parameters). The proposed method is compared against a condensation algorithm. Our results show that the proposed method improves the stability of a particle filter tracker and decreases the particle consumption.

• Journal of Korea Multimedia Society
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• v.24 no.12
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• pp.1632-1640
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• 2021

In order to improve target tracking performance of the conventional electro-optical tracking system (EOTS) in the high speed and high maneuvering vehicle, an EOTS navigation algorithm is proposed, in which an inertial measurement unit(IMU) is included and navigation results of the vehicle are used. The proposed algorithm integrates vehicle's navigation results and the IMU and the time-delay and the scale factor errors are augmented into the integrated Kalman filter. In order to evaluate the proposed navigation algorithm, a land vehicle navigation experiments were performed a navigation grade navigation system, TALIN4000 and a tactical grade IMU, LN-200 and a equipment for roll motion were loaded on the land vehicle. The performance evaluation results show that the proposed algorithm effecting works in high maneuvering environment and for the time-delay.

• The Journal of Korea Robotics Society
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• v.7 no.2
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• pp.113-119
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• 2012

In this paper we propose the method that detects moving objects in autonomous navigation vehicle using LRF sensor data. Object detection and tracking methods are widely used in research area like safe-driving, safe-navigation of the autonomous vehicle. The proposed method consists of three steps: data segmentation, mobility classification and object tracking. In order to make the raw LRF sensor data to be useful, Occupancy grid is generated and the raw data is segmented according to its appearance. For classifying whether the object is moving or static, trajectory patterns are analysed. As the last step, Markov chain Monte Carlo (MCMC) method is used for tracking the object. Experimental results indicate that the proposed method can accurately detect moving objects.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.335-335
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• 2000

Applications such as unmanned aerial vehicles (UAVs), autonomous underwater vehicles (AUVs) and the time varying nature of their navigation, guidance and control systems motivate an integrated approach to trajectory general ion and trajectory tracking for autonomous vehicles. In this paper, an experimental testbed was designed for studying this integrated trajectory control approach. In this paper we apply the separating approach to an autonomous nonlinear vehicle system. A new linear matrix inequality based H$_{\infty}$ control technique for periodic time-varying systems is applied to the role of trajectory tracking. Trajectory general ion is accomplished by exploit ing the differential flatness property of the vehicle system; this at lows product ion of desired feasible nominal or reference trajectories from certain ″flat'system outputs. Simulation and experimental results are presented showing stable tracking of a periodic circular trajectory.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.12
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• pp.1266-1272
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• 2011

For way-point tracking of an autonomous underwater vehicle, a state feedback controller was designed by using pole placement scheme in discrete time domain. In the controller, 4 state variables were used for regulating the depth of the vehicle in z direction, and 3 state variables, for steering the vehicle in xy plane. Assuming constant speed of AUV, we simplified the design of the way-point tracking system. The proposed controller was simulated by MATLAB/Simulink using 6 degree-of-freedom nonlinear model and its performance of way point tracking was shown to be fulfilled within 1 m, nevertheless the proposed controller is quite simple and easy to implement compared to sliding mode controller.

• Journal of Ocean Engineering and Technology
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• v.8 no.2
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• pp.56-63
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• 1994

This paper presents a design method of multivariable robust servo system for tracking control system for AUV(Autonomous Underwater Vehicle). In order to obtain the basic data for the design of the tracking control system, the control algorithm is evaluated in the view of computer simulation results. The tracking control is carried out for an AUV with 2 main thrusters, 2 side thrusters and 2 thrusters for the movement to up-down direction. The results of computer simulation show that the proposed multivariable servo system design method is an efficient method for the control performance of tracking control system of AUV under severe underwater environment.