• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.2
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• pp.109-114
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• 2007

Skid mark and coefficient of friction are usually utilized to calculate the velocity and behavior of vehicles. For a critical case such as traffic accident reconstruction, however, the initial velocity of the car should be calculated precisely. In this study, the skid marks on dry asphalt pavement were measured, and the velocity at brake onset was precisely recovered. A passenger car with new tires and non-contact optical speedometer were set up for the tests. A new methodology to determine the more precise velocity for Non-ABS vehicle at braking onset were suggested.

• The Journal of Korea Robotics Society
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• v.2 no.2
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• pp.109-118
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• 2007

The thruster is the crucial factor of an underwater vehicle system, because it is the lowest layer in the control loop of the system. In this paper, we propose an accurate and practical thrust modeling for underwater vehicles which considers the effects of ambient flow velocity and angle. In this model, the axial flow velocity of the thruster, which is non-measurable, is represented by ambient flow velocity and propeller shaft velocity. Hence, contrary to previous models, the proposed model is practical since it uses only measurable states. Next, the whole thrust map is divided into three states according to the state of ambient flow and propeller shaft velocity, and one of the borders of the states is defined as Critical Advance Ratio (CAR). This classification explains the physical phenomenon of conventional experimental thrust maps. In addition, the effect of the incoming angle of ambient flow is analyzed, and Critical Incoming Angle (CIA) is also defined to describe the thrust force states. The proposed model is evaluated by comparing experimental data with numerical model simulation data, and it accurately covers overall flow conditions within 2N force error. The comparison results show that the new model's matching performance is significantly better than conventional models'.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.814-819
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• 2010

This paper is presented to study the error minimization of angular velocity for AGV(autonomous ground vehicle). The error minimization of angular velocity is related to localization technique which is the most important technique for autonomous vehicle. Accelerometer, yaw gyro and electronic compass have been used to measure angular velocity. And methods for error minimization of angular velocity have been actively studied through probabilistic methods and sensor fusion for AGVs. However, those sensors still occure accumulated error by mathematical error, system characters of each sensor, and computational cost are increased greatly when several sensor are used to correct accumulated error. Therefore, this paper studies about error minimization of angular velocity that just uses encoder and gyro. To experiment, we use autonomous vehicle which is made by ourselves. In experimental result, we verified that the localization error of proposed method has even less than the localization errors which we just used encoder and gyro respectively.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.316-323
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• 1995

This paper presents an image processing technique to get traffic information such as vehicle volume, velocity, and occupancy for measuring the traffic congestion rate. To obtain these information, two horizontal lines are previously set on the screen. A moving vehicle is detected using the gray level difference on each line, and also template matching method at night. Threshold values are determined by sampling pavement grey level, and updated dynamically to cope with the change of ambient light conditions. These technique is successfully used to calculate vehicle volume, occupancy, and velocity. This study can be applied to traffic signal control system for minimizing traffic congestion in urban areas.

• Bulletin of the Society of Naval Architects of Korea
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• v.25 no.2
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• pp.1-10
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• 1988

An axially marching numerical method is developed for the simulation of the internal waves produced by translation of a submersed vehicle in a density-stratified ocean. The method provides for the direct solution of the primitive variables [$\upsilon,\;p,\;\rho$] for the nonlinear and steady state three-dimensional Euler's equation with a non-constant density term in the vehicle-fixed cartesian co-ordinate system. By utilizing a known potential flow around the vehicle for an estimate of the axial velocity gradient, the present parabolic algorithm local upstreamwise disturbances and axial velocity variation.

• Wind and Structures
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• v.29 no.3
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• pp.149-161
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• 2019

When a railway vehicle runs in crosswinds, the unsteady aerodynamic forces acting on the train induced by the vehicle speed, crosswind velocity and local landforms are a common problem. To investigate the dynamic performance of a railway vehicle due to the influence of unsteady aerodynamic forces caused by local landforms, a vehicle aerodynamic model and vehicle dynamic model were established. Then, a wind-loaded vehicle system model was presented and validated. Based on the wind-loaded vehicle system model, the dynamic response performance of the vehicle, including safety indexes and vibration characteristics, was examined in detail. Finally, the effects of the crosswind velocity and vehicle speed on the dynamic response performance of the vehicle system were analyzed and compared.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.1
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• pp.179-186
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• 2002

The absolute longitudinal speed of a vehicle is estimated by using vehicle acceleration data from an accelerometer and wheel speed data from standard 50-tooth antiknock braking system wheel speed sensors. An intuitive solution to this problem is, "When wheel slip is low, calculate absolute velocities from the wheel speeds; when wheel slip is high, calculate absolute velocity by integrating the accelerometer." Fuzzy logic is introduced to implement the above idea and a new algorithm of "modified velocities with step integration" is proposed. This algorithm is verified experimentally to estimate speed of a vehicle, and is also shown to estimate absolute longitudinal vehicle speed with a 6% worst-case error during a hard braking maneuver lasting three seconds.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.4
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• pp.642-651
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• 2016

For the acceleration and brake systems of an autonomous vehicle, the dynamic models from acceleration (brake) pedal input to driving(braking) torque at the vehicle wheel are represented by a set of linear transfer functions in this paper. We present an experimental method that can identify these models using a single rectangular pulse response data. Various magnitude of inputs with different running speeds are applied to experimental tests. All the identified models are demonstrated by the measured data. Both acceleration and brake models have been also validated by comparing the velocity of a full vehicle model associated with the proposed models with the measured vehicle velocity.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.181-184
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• 1999

Leading vehicle states are useful and essential elements in adaptive cruise control (ACC) system, collision warning (CW) and collision avoidance (CA) system, and automated highway system (AHS). There are many approaches in ACC using Kalman filter. Mostly only distance to leading vehicle and velocity difference are estimated and used for the above systems. Applications in road vehicle in curved road need to obtain more informations such as yaw angle, steering angle which can be estimated using vision system. Since vision system is not robust to environment change, we used Kalman filter to estimate distance, velocity, yaw angle, and steering angle. Application to active tracking of target vehicle is shown.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.23.1-23
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• 2001

The unmanned vehicle is composed of three parts the front & side sensor system for keeping the lane and avoiding obstacles, the acceleration & brake control system for longitudinal motion control, and the steering control system for the lateral motion control. Each system helps the unmanned vehicle of which should take notice of its location and recognize obstacles around the place by itself and make a decision how much fast to proceed according to circumstances. During the operation, the control strategy that the vehicle can detect obstacles and avoid collision on the road involves with vehicle velocity very much. Therefore, We have to define a traction system which is powered by DC motor so that, unmanned vehicle can control its velocity accurately. In this study, we find mechanical and ...