• Journal of the Korean Society for Aviation and Aeronautics
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• v.21 no.1
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• pp.23-29
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• 2013

This paper presents a tracking filter of radar beacon system (RBS) for automatic takeoff and landing of an unmanned aerial vehicle. The proposed tracking filter is designed as the decoupled tracking filter to reduce the computational burden. Also, an adaptive estimation method of the measurement error covariance is proposed to provide an improved tracking performance compared to the conventional decoupled tracking filter whenever the accuracy of RBS observations is degraded. 100 times Monte Carlo runs performed to analyze the performance of the proposed tracking filter in case of normal operation and degraded operations, respectively. The simulation results show that the proposed tracking filter provides the improved tracking accuracy in comparison with the conventional decoupled tracking filter.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.3
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• pp.45-56
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• 2007

Automatic tracking of vehicles is important to accurately estimate the traffic information including vehicle speeds in video-based traffic measurement systems. Because of the limited field of view, the range of visual tracking with a single camera is restricted. In order to enlarge the tracking range for better chance of monitoring the vehicle behaviors, a tracking with consecutive multiple video sequences is necessary. This parer proposes a carefully designed rule-based vehicle racking scheme and apply it for the tracking for two well synchronized video sequences. In the scheme, almost all possible cases that can appear in the video-based vehicle tracking are considered to make rules. Also, the rule based scheme is augmented with Kalman filter. The result of tracking can be successfully used to collect data such as temporal variation of vehicle speed and behavior of individual vehicle behaviors in the enlarged tracking region.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.2
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• pp.133-140
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• 2017

In this paper, we has proposed an automatic vehicle monitoring system based on computer vision technology. The real-time display system has displayed a system that can be performed in automatic monitoring and control while meeting the essential requirements of ITS. Another advantage has that for a powerful vehicle tracking, the main obstacle handing system, which has the shadow tracking of moving objects. In order to obtain all kinds of information from the tracked vehicle image, the vehicle must be clearly displayed on the surveillance screen. Over time, it's necessary to precisely control the vehicle, and a three-dimensional model-based approach has been also necessary. In general, each type of vehicle has represented by the skeleton of the object or wire frame model, and the trajectory of the vehicle can be measured with high precision in a 3D-based manner even if the system has not running in real time. In this paper, we has applied on segmentation method to vehicle, background, and shadow. The validity of the low level vehicle control tracker was also detected through speed tracking of the speeding car. In conclusion, we intended to improve the improved tracking method in the tracking control system and to develop the highway monitoring and control system.

• Journal of Mechanical Science and Technology
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• v.16 no.2
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• pp.137-146
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• 2002

In this paper, a path generation algorithm that uses sensor scannings is described. A scanning algorithm for recognizing the ambient environment of the Automatic Guided Vehicle (AGV) that uses the information from the sensor platform is proposed. An algorithm for computing the real path and obstacle length is developed by using a scanning method that controls rotating of the sensors on the platform. The AGV can recognize the given path by adopting this algorithm. As the AGV with two-wheel drive constitute a nonholonomic system, a linearized kinematic model is applied to the AGV motor control. An optimal controller is designed for tracking the reference path which is generated by recognizing the path pattern. Based on experimental results, the proposed algorithm that uses scanning with a sensor platform employing only a small number of sensors and a low cost controller for the AGV is shown to be adequate for path generation.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.6
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• pp.321-328
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• 2018

This paper presents an automatic target tracking flight system using a PID controller based on velocity command of a multirotor UAV. The automatic flight system includes marker based onboard target detection and an automatic velocity command generation replacing manual controller. A quad-rotor UAV is equipped with a camera and an image processing computer to detect the marker in real time and to estimate the relative distance from the target. The marker tracking system consists of PID controller and generates velocity command based on the relative distance. The generated velocity command is used as the input of the UAV's original flight controller. The operation of the proposed system was verified through actual flight tests using a marker on top of a moving vehicle and tracks it to successfully demonstrate its capability using a quad-rotor UAV.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.4 no.2 s.7
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• pp.1-11
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• 2005

Automatic tracking of vehicles is important to accurately estimate the vehicle speeds in video-based traffic measurement systems and to analyze traffic flows for road construction. This paper proposes a carefully designed rule-based tracking scheme that considers the possible cases that can be appeared in the video-based vehicle racking. The proposed scheme is fast and outperforms the Mean-Shift scheme in terms of accuracy. The accuracy and the speed of the scheme would be increased by combining it with color-based searching and Kalman filters.

• Journal of Drive and Control
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• v.13 no.1
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• pp.18-26
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• 2016

This research is conducted to develop an automatic steering system for parallel parking, and the performance of the system was evaluated by parallel parking a conventional vehicle. The automatic steering system consisted of MDPS (motor driven power steering) to control steering, ESC (electronic stability control) to acquire wheel speed, ultrasonic sensors to recognize the parking space, and a controller to communicate and handle data. The parallel parking process using the automatic steering control consisted of parking space recognition, parking path generation, and parking path tracking. The path for parallel parking was generated based on a kinematic model of a conventional vehicle, and a PI controller was used to control the steering angle for path tracking. Parallel parking using the automatic steering control was conducted according to vehicle speed conditions. The results show that the errors on the x-axis and y-axis were below 0.54 m and 0.14 m, respectively, and the error on the steering angle was less than $1^{\circ}$. Therefore, it is possible to implement parallel parking using an automatic steering control system for conventional vehicles.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1014-1019
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• 2005

In this paper, a neural network technique for automatic steering control of a four wheel drive autonomous highway snowplow vehicle is presented. Controllers are designed by the LQR method based on the vehicle model. Then, neural network is used as an auxiliary controller to minimize lateral tracking error under the presence of load. Simulation studies of LQR control and neural network control are conducted for the vehicle model under a virtual snowplowing situation. Tracking performances are also compared for two and four wheeled steering vehicles.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.710-726
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• 2018

This paper presents an extended particle filter to increase the accuracy and decrease the computation load of vehicle tracking. Particle filter has been the subject of extensive interest in video-based tracking which is capable of solving nonlinear and non-Gaussian problems. However, there still exist problems such as preventing unnecessary particle consumption, reducing the computational burden, and increasing the accuracy. We aim to increase the accuracy without an increase in computation load. In proposed method, we calculate the direction angle of the target vehicle. The angular difference between the direction of the target vehicle and each particle of the particle filter is observed. Particles are filtered and weighted, based on their angular difference. Particles with angular difference greater than a threshold is eliminated and the remaining are stored with greater weights in order to increase their probability for state estimation. Threshold value is very critical for performance. Thus, instead of having a constant threshold value, proposed algorithm updates it online. The first advantage of our algorithm is that it prevents the system from failures caused by insufficient amount of particles. Second advantage is to reduce the risk of using unnecessary number of particles in tracking which causes computation load. Proposed algorithm is compared against camshift, direction-based particle filter and condensation algorithms. Results show that the proposed algorithm outperforms the other methods in terms of accuracy, tracking duration and particle consumption.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2000.05a
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• pp.11-15
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• 2000

This paper provides a basic study on automatic of a trailer type vehicle which consists of two parts such as a tractor and a trailer Backward moving and parking control is very important to automate this type of vehicle. However it is very difficult to control such their motion since a trailer type vehicle is a non-holonomic system. Therefore in this paper we propose the backward path tracking control algorithm for a trailer type vehicle. And also this paper presents the results of simulation to verify the effectiveness of the proposed control algorithm.