• 자동차안전학회지
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• 제11권3호
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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.

• 전기학회논문지
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• 제59권3호
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• pp.645-650
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• 2010

In this paper we present the Bimodal-tram simulator using the PXI embedded real-time controllers. The Bimodal-tram is developed in KRRI (Korea Railroad Research Institute). The vehicle can be automatically operated by navigation control system (NCS). For the automatic driving, the vehicle lanes will be marked with permanent magnets that are placed in the ground. The vehicle is controlled by NCS. NCS governs the manual mode and automatic mode driving. The simulator is designed by an identical conception with the real control condition. The dynamic motion of vehicle is simulated by the nonlinear dynamic model. The control computer calculates the control values. The signal interface is linked by CAN communication. The simulation is processed by real-time base. The test driver can see the graphic motion of vehicle and can operate the steering wheel, gas and brake pedal to control direction and velocity of vehicle during the simulation. At present, the simulator is only operated by manual mode. The automatic mode will be linked after the control algorithm is finished. We will use the simulator to develop the control algorithm in the automatic mode. This paper shows the simulator designed for Bimodal-tram using real-time based controller. The results of the test using the simulator are presented and discussed.

• International Journal of Automotive Technology
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• 제7권1호
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• pp.25-34
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• 2006

For decades, simulation technique has been well validated in areas such as computer and communication systems. Recently, the technique has been much used in the area of transportation and traffic forecasting. Several methods have been proposed for investigating complex traffic flows. However, the dynamics of vehicles and diversities of driver characteristics have never been considered sufficiently in these methods, although they are considered important factors in traffic flow analysis. In this paper, we propose a traffic simulation tool called Multi-Agent for Traffic Simulation with Vehicle Dynamics Model (MATDYMO). Road transport consultants, traffic engineers and urban traffic control center managers are expected to use MATDYMO to efficiently simulate traffic flow. MATDYMO has four sub systems: the road management system, the vehicle motion control system, the driver management system, and the integration control system. The road management system simulates traffic flow for various traffic environments (e.g., multi-lane roads, nodes, virtual lanes, and signals); the vehicle motion control system constructs the vehicle agent by using various vehicle dynamic models; the driver management system constructs the driver agent capable of having different driving styles; and lastly, the integrated control system regulates the MATDYMO as a whole and observes the agents running in the system. The vehicle motion control system and driver management system are described in the companion paper. An interrupted and uninterrupted flow model were simulated, and the simulation results were verified by comparing them with the results from a commercial software, TRANSYT-7F. The simulation result of the uninterrupted flow model showed that the driver agent displayed human-like behavior ranging from slow and careful driving to fast and aggressive driving. The simulation of the interrupted flow model was implemented as two cases. The first case analyzed traffic flow as the traffic signals changed at different intervals and as the turning traffic volume changed. Second case analyzed the traffic flow as the traffic signals changed at different intervals and as the road length changed. The simulation results of the interrupted flow model showed that the close relationship between traffic state change and traffic signal interval.

• 로봇학회논문지
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• 제12권2호
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• pp.184-193
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• 2017

This work shows how to create an algorithm and implementation for motion and image matching between a vehicle simulator and Unity 3D based virtual object. The motion information of the virtual vehicle is transmitted to the real simulator via a RS232 communication protocol, and the motion is controlled based on the inverse kinematics solution of the platform adopting rotary-type six actuators driving system. Wash-out filters to implement the effective motion of the motion platform are adopted, and thereby reduce the dizziness and increase the realistic sense of motion. Furthermore, the simulator system is successfully designed aiming to reducing size and cost with adaptation of rotary-type six actuators, real driving environment via VR (Virtual Reality), and control schemes which employ a synchronization between 6 motors and 3rd order motion profiles. By providing relatively big sense of motion particularly in impact and straight motions mainly causing simulator sickness, dizziness is remarkably reduced, thereby enhancing the sense of realistic motion.

• International Journal of Aeronautical and Space Sciences
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• 제16권1호
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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.

• Journal of Mechanical Science and Technology
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• 제19권4호
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• pp.985-992
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• 2005

Vehicle Stability Control (VSC) system prevents vehicle from spinning or drifting out mainly by braking intervention. Although a control threshold of conventional VSC is designed by vehicle characteristics and centered on average drivers, it can be a redundancy to expert drivers in critical driving conditions. In this study, a manual adaptation of VSC is investigated by changing the control threshold. A control threshold can be determined by phase plane analysis of side slip angle and angular velocity which is established with various vehicle speeds and steering angles. Since vehicle side slip angle is impossible to be obtained by commercially available sensors, a side slip angle is designed and evaluated with test results. By using the estimated value, phase plane analysis is applied to determine control threshold. To evaluate an effect of control threshold, we applied a 23-DOF vehicle nonlinear model with a vehicle planar motion model based sliding controller. Controller gains are tuned as the control threshold changed. A VSC with various control thresholds makes VSC more flexible with respect to individual driver characteristics.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.115.2-115
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• 2002

A real-time vehicle simulation system is a key element of a driving simulator because accurate prediction of vehicle motion with respect to driver input is required to generate realistic visual, motion, sound and proprioceptive cues. In order to predict vehicle motion caused by various driving actions of the driver on board the simulator, the vehicle model should consist of complete subsystems. On this paper, a tracked vehicle dynamic model with high efficiency and effectiveness is introduced that has been implemented on a training driving simulator. The multi-body vehicle model is based on recursive formulation and has been automatically generated from a symbolic computation package develop...

• 한국기계가공학회지
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• 제19권6호
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• pp.1-8
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• 2020

This paper proposes a method for measuring friction forces and creating a friction model for a rotary motion control system as well as an autonomous vehicle testbed. The friction forces versus the velocity were measured, and the viscous friction, Coulomb friction, and stiction were identified. With a nominal PID (proportional-integral-derivative) controller, we observed the adverse effects due to friction, such as excessive steady-state errors, oscillations, and limit-cycles. By adding an adequate friction model as part of the augmented nonlinear dynamics of a plant, we were able to conduct a simulation study of a motion control system that well matched experimental results. We have observed that the implementation of a model-based friction compensator improves the overall performance of both motion control systems, i.e., the rotary motion control system and the Altino testbed for autonomous vehicle development. By utilizing a better simulation tool with an embedded friction model, we expect that the overall development time and cost can be reduced.

• International Journal of Automotive Technology
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• 제7권4호
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• pp.469-475
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• 2006

In this paper, an optimal suspension system with preview of the road input is synthesized for a half tracked vehicle. The main goal of this research is to improve the ride comfort characteristics of a fast moving tracked vehicle in order to maintain the driver's driving capability. Several different kinds of preview control algorithms are evaluated with active or semi-active suspension systems. The road information estimated from the motion of the 1st road-wheel is adequate to make the best use of the preview control algorithm for tracked vehicles. The ride-comfort characteristics of the tracked vehicle are more dependent on pitching angular acceleration than heaving acceleration. The pitching motion is reduced by the suspension system with hard outer suspensions and soft inner suspensions. Simulation results show that the performance of sky-hook algorithms for ride comfort nearly follow that of full state feedback algorithms.

• 자동차안전학회지
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• 제14권1호
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• pp.20-25
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• 2022

This paper presents a development of simulation environment for validation of autonomous driving (AD) algorithm based on Robot Operating System (ROS). ROS is one of the commonly-used frameworks utilized to control autonomous vehicles. For the evaluation of AD algorithm, a 3D autonomous driving simulator has been developed based on LGSVL. Two additional sensors are implemented in the simulation vehicle. First, Lidar sensor is mounted on the ego vehicle for real-time driving environment perception. Second, GPS sensor is equipped to estimate ego vehicle's position. With the vehicle sensor configuration in the simulation, the AD algorithm can predict the local environment and determine control commands with motion planning. The simulation environment has been evaluated with lane changing and keeping scenarios. The simulation results show that the proposed 3D simulator can successfully imitate the operation of a real-world vehicle.