• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.2
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• pp.188-200
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• 2018

This paper proposes a single control strategy to solve the problem of trans-media vehicle difficult control. The proposed control strategy is just to control the vehicle's air navigation, but not to control the underwater navigation. The hydrodynamic model of a vehicle when entering water obliquely at low speed has been founded to analyze the motion characteristics. Two methods have been used to simulate the vehicle entering water in the same condition: numerical simulation method and theoretical model solving method. And the results of the two methods can validate the hydrodynamic model founded in this paper. The entering water motion in the conditions of different velocity, different angle, and different attack angle has been simulated by this hydrodynamic model and the simulation has been analyzed. And the change rule of the vehicle's gestures and position when entering water has been obtained by analysis. This entering water rule will guide the follow-up of a series of research, such as the underwater navigation, the exiting water process and so on.

• Journal of Auto-vehicle Safety Association
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• v.11 no.3
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• pp.30-36
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• 2019

This paper suggests a car-following algorithm for urban environment, with multiple target candidates. Until now, advanced driver assistant systems (ADASs) and self-driving technologies have been researched to cope with diverse possible scenarios. Among them, car-following driving has been formed the groundwork of autonomous vehicle for its integrity and flexibility to other modes such as smart cruise system (SCC) and platooning. Although the field has a rich history, most researches has been focused on the shape of target trajectory, such as the order of interpolated polynomial, in simple single-lane situation. However, to introduce the car-following mode in urban environment, realistic situation should be reflected: multi-lane road, target's unstable driving tendency, obstacles. Therefore, the suggested car-following system includes both in-lane preceding vehicle and other factors such as side-lane targets. The algorithm is comprised of three parts: path candidate generation and optimal trajectory selection. In the first part, initial guesses of desired paths are calculated as polynomial function connecting host vehicle's state and vicinal vehicle's predicted future states. In the second part, final target trajectory is selected using quadratic cost function reflecting safeness, control input efficiency, and initial objective such as velocity. Finally, adjusted path and control input are calculated using model predictive control (MPC). The suggested algorithm's performance is verified using off-line simulation using Matlab; the results shows reasonable car-following motion planning.

• Journal of information and communication convergence engineering
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• v.11 no.4
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• pp.274-281
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• 2013

In this study, we consider the challenges in motion planning for automated driving systems. Most of the existing online motion-planning algorithms, which take dynamics into account, find it difficult to operate in an environment with narrow passages. Some of the existing algorithms overcome this by offline preprocessing if environment is known. In this work an online algorithm for motion planning with dynamics in an unknown cluttered environment with narrow passages is presented. It utilizes an idea of hybrid planning with sampling- and discretization-based motion planners, which run simultaneously in a full configuration space and a derived reduced space. The proposed algorithm has been implemented and tested with a real autonomous vehicle. It provides significant improvements in computational time performance over basic planning algorithms and allows the generation of smoother paths than those generated by the recently developed hybrid motion planners.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.5
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• pp.95-107
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• 2016

The axle weight of a vehicle in motion can be measured with a low-speed or high-speed weigh-in-motion (WIM). However, the axial load dynamically change depending on the vehicle's characteristics-such as the chassis or axle structure-or the characteristics of the driving environment such as road flatness. The changes in dynamic load lead to differences between the vehicle's weight measured at rest and the vehicle's weight measured in motion. For this Study, an experiment was conducted with an instrumented vehicle to analyze the range of errors caused by uncontrollable environmental factors by identifying the characteristics of the dynamic load changes of a vehicle in motion, and determine the appropriate scale for the accuracy evaluation of a high-speed WIM, as a preparatory research for the introduction of unmanned overweight enforcement systems in the future. The key findings from the experiment are summarized as follows. First, The gross weight of the tested vehicle changed by approximately 1% at low velocities and approximately by 4% at high velocities, and the vehicle's axle weight changed by approximately 1-3%, at low velocities and by 2-9% at high velocities. A single axle showed larger weight changes than individual axles in a group. Secondly, The vehicle's gross weight and the axle weight on the impact section were up to eight times and three-to-twelve times higher, respectively, than its gross weight and the axle weight on the flat section. The vibration frequency of the vehicle's dynamic load was measured at between 2.4 and 5.8Hz, and found to return to the normal amplitude after moving approximately 30 meters.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.5
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• pp.525-530
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• 2016

In this paper, we proposed an image shaking index to evaluate the remote controllability of vision based unmanned vehicles. To analyze the usefulness of the proposed image-shaking index, we perform subjective tests using a virtual unmanned vehicle driving simulator. The developed driving simulator consists of a real-time multibody dynamic software of the unmanned vehicle, a motion simulator, and a driver console. We perform dynamic simulations to obtain the motion of the unmanned vehicle running on the various road surfaces such as ISO roughness level A~E roads. The motion of the vehicle body is reflected in the motion simulator. Then, to enable remote control operation, we offer to operators the image data that was measured using the camera sensor on the simulator. We verify the usefulness of the proposed image-shaking index compared with subjective index provided by operators.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.14-19
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• 2022

This paper presents motion planning algorithm that yields to intervening side lane vehicles in a congested traffic flow based on vehicle to vehicle (V2V) communication. Autonomous driving in dense traffic situation requires advanced driving performance in terms of vehicle interaction and risk mitigation. One of the most important functions necessary for congested traffic autonomous driving is to predict the lane change intention of the side lane target vehicle. However, implementing this function by using only environmental sensors has limitations. In this study, V2V communication is used to overcome the limitations and determine the intention of cut-in vehicles. Lane change intention of the intervening side lane vehicle is inferred by its longitudinal speed, steering angle, and turn signal light information received by the on-board-unit (OBU). Once the yield decision is made, the subject vehicle decelerates to generate sufficient clearance for the target vehicle to enter. Validation of the algorithm was conducted with actual autonomous test vehicles.

• Journal of the korean Society of Automotive Engineers
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• v.14 no.3
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• pp.43-56
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• 1992

This task is to derive the Hamiltonian equations of motion for BMW 323i vehicle. The kinematic relationships are defined. The cut constraint equations are derived. The cut constraint equations are stabilized. The stabilized constraint equations are used to derive the relationships between the independent and dependent coordinates. The Hamiltonian equations of motion are reduced only in terms of the independent generalized coordinates.

• International Journal of Aeronautical and Space Sciences
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• v.16 no.1
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• pp.77-88
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• 2015

The dynamics of relative motion in a perturbed orbital environment are exploited based on Gauss' and Cowell's variational equations. The inertial coordinate frame and relative coordinate frame (Hill frame) are used, and a linear high fidelity model is developed to describe the relative motion. This model takes into account the primary gravitational and atmospheric drag perturbations. Then, this model is used in the design of a navigation, guidance, and control system of a chaser vehicle to approach towards and to depart from a target vehicle in proximity operations. Relative navigation uses an extended Kalman filter based on this relative model to estimate the relative position/velocity of the chaser vehicle with respect to the target vehicle. This filter uses the range and angle measurements of the target relative to the chaser from a simulated LIDAR system. The corresponding measurement models, process noise matrix, and other filter parameters are provided. Numerical simulations are performed to assess the precision of this model with respect to the full nonlinear model. The analyses include the navigation errors and trajectory dispersions.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.1137-1146
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• 1993

In order to analyze lateral control in the forward manuever of a tractor- trailer combination , a human operator model and a kinematic vehicle model were utilized for the operator/vehicle system. By combining the vehicle and operator models, a mathematical model of the closed-loop operator/vehicle system was formulated. A computer program was developed so as to simulate the motion of the tractor-trailer combination . In order to verify the operator/vehicle system model, the results of the field trials were compared with the simulated results. There was found to be reasonably good agreement between the two.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.414-421
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• 2007

This paper presents a engine/brake integrated VDC(Vehicle Dynamic Control) system using neural network algorithm methods for wheel slip and yaw rate control. For stable performance of vehicle, not only is the lateral motion control(wheel slip control) important but the yaw motion control of the vehicle is crucial. The proposed NNPI(Neural Network Proportional-Integral) controller operates at throttle angle to improve the performance of wheel slip. Also, the suggested NNPID controller performs at brake system to improve steering performance. The proposed controller consists of multi-hidden layer neural network structure and PID control strategy for self-learning of gain scheduling. Computer Simulation have been performed to verify the proposed neural network based control scheme of 17 dof vehicle dynamic model which is implemented in MATLAB Simulink.