• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.11
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• pp.1069-1076
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• 2007

This paper presents the road simulator control technology for reproducing the road input signal to implement the real road data. The simulator consists of the hydraulic pump, servo valve, hydraulic actuator and its control equipment. The QFT(Quantitative Feedback Theory) is utilized to control the simulator effectively. The control system illustrates a tracking performance of the closed-loop controller with low order transfer function G(s) and pre-filter F(s) for a parametric uncertain model. A force controller is designed to communicate the control signal between simulator and digital controller. Tracking specification is satisfied with upper and lower bound tolerances on the steep response of the system to the reference signal. The efficacy of the QFT force controller is verified through the numerical simulation, in which combined dynamics and actuation of the hydraulic servo system are tested. The simulation results show that the proposed control technique works well under uncertain hydraulic plant system. The conventional software (Labview) is used to make up for the real controller in the real-time basis, and the experimental works show that the proposed algorithm works well for a single road simulator.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.97-105
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• 2020

Recently, for a smart city, there is a demand for a technology for acquiring traffic information using an intelligent road infrastructure and managing it. In the meantime, various technologies such as loop detectors, ultrasonic detectors, and image detectors have been used to analyze road traffic information but these have difficulty in collecting various informations, such as traffic density and length of a queue required for building a traffic information DB for moving vehicles. Therefore, in this paper, assuming a smart city built on the basis of a camera infrastructure such as intelligent CCTV on the road, a solution for calculating the traffic DB of moving vehicles using Vision Tracking of road CCTV cameras is presented. Simulation and verification of basic performance were conducted and solution can be usefully utilized in related fields as a new intelligent traffic DB calculation solution that reflects the environment of road-mounted CCTV cameras and moving vehicles in a variable smart city road environment. It is expected to be there.

• Journal of Korean Society of Transportation
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• v.23 no.7 s.85
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• pp.137-148
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• 2005

The position information of individual vehicles on a road at every time instant can be used to analyze the microscopic behaviors of driving of each vehicle. The limited information obtained from previous imaging technology such as traffic volume and interval velocity cannot be used to explore such microscopic traffic conditions. Also, information gathering for the microscopic behaviors by manual analysis of captured video takes large amount of time and man-power. In the paper we develop the rule-based vehicle tracking technology from which the position information of individual vehicles on a road at every time instant can be automatically obtained. Also, we extract the position data of driving vehicles on a road, length of 130m for every 0.05 second, and calculate the velocity of each traced vehicles to compare with the real velocity for the verification of accuracy. In the future, this type of tracking techniques based on video analysis can be widely used to provide the practically important information of road traffic conditions and to analyze the academically important microscopic behaviors of driving patterns.

• The Journal of Korea Robotics Society
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• v.6 no.2
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• pp.182-188
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• 2011

This paper describes a method of road tracking by using a vision and laser with extracting road boundary (road lane and curb) for navigation of intelligent transport robot in structured road environments. Road boundary information plays a major role in developing such intelligent robot. For global navigation, we use a global positioning system achieved by means of a global planner and local navigation accomplished with recognizing road lane and curb which is road boundary on the road and estimating the location of lane and curb from the current robot with EKF(Extended Kalman Filter) algorithm in the road assumed that it has prior information. The complete system has been tested on the electronic vehicles which is equipped with cameras, lasers, GPS. Experimental results are presented to demonstrate the effectiveness of the combined laser and vision system by our approach for detecting the curb of road and lane boundary detection.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.3
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• pp.280-289
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• 2008

This paper presents design of the quantitative feedback control system of the three axes hydraulic road simulator with respect to the dummy wheel for uncertain multiple input-output(MIMO) feedback systems. This simulator has the uncertain parameters such as fluid compressibility, fluid leakage, electrical servo components and nonlinear mechanical connections. This works have reproduced the random input signal to implement the real road vibration's data in the lab. The replaced $m^2$ MISO equivalent control systems satisfied the design specifications of the original $m^*m$ MIMO control system and developed the mathematical method using quantitative feedback theory based on schauder's fixed point theorem. This control system illustrates a tracking performance of the closed-loop controller with low order transfer function G(s) and pre-filter F(s) having the minimum bandwidth for parameters of uncertain plant. The efficacy of the designed controller is verified through the dynamic simulation with combined hydraulic model and Adams simulator model. The Matlab simulation results to connect with Adams simulator model show that the proposed control technique works well under uncertain hydraulic plant system. The designed control system has satisfied robust performance with stability bounds, tracking bounds and disturbance. The Hydraulic road simulator consists of the specimen, hydraulic pump, servo valve, hydraulic actuator and its control equipments

• Journal of KIISE:Software and Applications
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• v.31 no.11
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• pp.1496-1504
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• 2004

In this paper, we propose an algorithm for initializing a target vehicle detection, tracking the vehicle and estimating the distance from it on the stereo images acquired from a forward-looking stereo camera mounted on a road driving vehicle. The process of vehicle detection extracts road region using lane recognition and searches vehicle feature from road region. The distance of tracking vehicle is estimated by TSS correlogram matching from stereo Images. Through the simulation, this paper shows that the proposed method segments, matches and tracks vehicles robustly from image sequences obtained by moving stereo camera.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.1
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• pp.15-23
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• 2020

In this paper, we propose a new method to detect traffic accidents in video from vehicle-mounted cameras (vehicle black box). We use the distance between vehicles to determine whether an accident has occurred. To calculate the position of each vehicle, we use object detection and tracking method. By the way, in a crowded road environment, it is so difficult to decide an accident has occurred because of parked vehicles at the edge of the road. It is not easy to discriminate against accidents from non-accidents because a moving vehicle and a stopped vehicle are mixed on a regular downtown road. In this paper, we try to increase the accuracy of the vehicle accident detection by using not only the motion of the surrounding vehicle but also ego-motion as the input of the Recurrent Neural Network (RNN). We improved the accuracy of accident detection compared to the previous method.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.51-56
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• 2011

The train travels on the track and, thus, the rear wheels precisely follow the paths of the front wheels. On the contrary, in the vehicles running on the road like automobiles, buses and trucks, the front wheels try to drag the rear ones toward them and across the inside of the curve. Off-tracking is defined as the radial offset between the path of the centerline of the front axle and the path of the centerline of the following axle. In the case of the bimodal tram with AWS(all wheel steering), the off-tracking decrease but the rear swing-out values increase because of the rear steering at the reverse phase angle. Thus, in order to determine the swept path width, maximum road width at the minimum turning radius, off-tracking and swing-out should be considered for the bimodal tram. In this paper, trajectory simulations were carried out for the various condition such as front steering, front and rear steering and suppression of swing-out to optimize the swept path width.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.4
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• pp.337-343
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• 2005

In this paper, experimental studies of force control of the crack tracking robot are presented. The crack tracking robot should maintain constant contact with the road to perform cleaning process of the crack effectively. Regulating desired force on the road requires a sophisticated force control algorithm. Here, two main force control algorithms such as the impedance force control and the explicit force control are used. Performances of two force control algorithms are compared.

• Journal of information and communication convergence engineering
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• v.20 no.3
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• pp.226-233
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• 2022

Video surveillance is widely used in security surveillance, military navigation, intelligent transportation, etc. Its main research fields are pattern recognition, computer vision and artificial intelligence. This article uses OpenCV to detect and track vehicles, and monitors by establishing an adaptive model on a stationary background. Compared with traditional vehicle detection, it not only has the advantages of low price, convenient installation and maintenance, and wide monitoring range, but also can be used on the road. The intelligent analysis and processing of the scene image using CAMSHIFT tracking algorithm can collect all kinds of traffic flow parameters (including the number of vehicles in a period of time) and the specific position of vehicles at the same time, so as to solve the vehicle offset. It is reliable in operation and has high practical value.