• International Journal of Automotive Technology
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• v.7 no.1
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.10
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• pp.902-911
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• 2012

This paper proposes a robust adaptive fuzzy backstepping control scheme for trajectory tracking of an electrically driven nonholonomic mobile robot with uncertainties and actuator dynamics. A complete model of an electrically driven nonholonomic mobile robot described in this work includes all models of the uncertain robot kinematics with a nonholonomic constraint, the uncertain robot body dynamics with uncertain frictions and unmodeled disturbances, and the uncertain actuator dynamics with disturbances. The proposed control scheme uses the backstepping control approach through a kinematic controller and a robust adaptive fuzzy velocity tracking controller. The presented control scheme has a voltage control input with an auxiliary current control input rather than a torque control input. It has two FBFNs(Fuzzy Basis Function Networks) to approximate two unknown nonlinear robot dynamic functions and a robust adaptive control input with the proposed adaptive laws to overcome the uncertainties such as parameter uncertainties and external disturbances. The proposed control scheme does not a priori require the accurate knowledge of all parameters in the robot kinematics, robot dynamics and actuator dynamics. It can also alleviate the chattering of the control input. Using the Lyapunov stability theory, the stability of the closed-loop robot control system is guaranteed. Simulation results show the validity and robustness of the proposed control scheme.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.4
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• pp.326-337
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• 2010

This work addresses problems regarding trajectory planning for unmanned aerial vehicle sensors. Such sensors are used for taking measurements of large nonlinear systems. The sensor investigations presented here entails methods for improving estimations and predictions of large nonlinear systems. Thoroughly understanding the global system state typically requires probabilistic state estimation. Thus, in order to meet this requirement, the goal is to find trajectories such that the measurements along each trajectory minimize the expected error of the predicted state of the system. The considerable nonlinearity of the dynamics governing these systems necessitates the use of computationally costly Monte-Carlo estimation techniques, which are needed to update the state distribution over time. This computational burden renders planning to be infeasible since the search process must calculate the covariance of the posterior state estimate for each candidate path. To resolve this challenge, this work proposes to replace the computationally intensive numerical prediction process with an approximate covariance dynamics model learned using a nonlinear time-series regression. The use of autoregressive time-series featuring a regularized least squares algorithm facilitates the learning of accurate and efficient parametric models. The learned covariance dynamics are demonstrated to outperform other approximation strategies, such as linearization and partial ensemble propagation, when used for trajectory optimization, in terms of accuracy and speed, with examples of simplified weather forecasting.

• Korean System Dynamics Review
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• v.14 no.1
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• pp.5-29
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• 2013

This study tries to measure the direct and indirect effects of the Regional Strategic Industry (RSI) promotion projects in Chungbuk Province in Korea. In specific, it critically examines whether there exists policy consistency and connectivity between the hardware-oriented Stage I (2002~2007) and the software-centered Stage II (2008~2012) RSI promotion projects. Applying System Dynamics (SD) techniques, this study examines complex system characteristics of RSI promotion projects, all of which have been derived from the causal and stock-flow models and their simulated results. Major findings are as follows: Firstly, 'the continuous investment' is regarded as the most crucial policy leverage for the strategic industry promotion and regional economic growth. Secondly, without exceptions, the RSI promotion projects should switch their evaluation criteria to performance-oriented ones. Thirdly, in selecting their subprojects, the RSI promotion projects should pay due attention to evaluating technology value and marketability. Fourthly, it should put policy priority in strengthening cluster networking and interconnectivity among projects, inevitably supporting a selective number of virtuous network systems. Fifthly, auxiliary projects such as marketing, technology aid, and knowledge-based services should not be overlooked.

• Journal of The Korean Astronomical Society
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• v.46 no.3
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• pp.133-140
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• 2013

The empirical mass discrepancy-acceleration (MDA) relation of disk galaxies provides a key test for models of galactic dynamics. In terms of modified laws of gravity and/or inertia, the MDA relation quantifies the transition from Newtonian to modified dynamics at low centripetal accelerations $a_c{\lesssim}10^{-10}ms^{-2}$. As yet, neither dynamical models based on dark matter nor proposed modifications of the laws of gravity/inertia have predicted the functional form of the MDA relation. In this work, I revisit the MDA data and compare them to four different theoretical scaling laws. Three of these scaling laws are entirely empirical; the fourth one - the "simple ${\mu}$" function of Modified Newtonian Dynamics - derives from a toy model of gravity based on massive gravitons (the "graviton picture"). All theoretical MDA relations comprise one free parameter of the dimension of an acceleration, Milgrom's constant aM. I find that the "simple ${\mu}$" function provides a good fit to the data free of notable systematic residuals and provides the best fit among the four scaling laws tested. The best-fit value of Milgrom's constant is $a_M=(1.06{\pm}0.05){\times}10^{-10}ms^{-2}$. Given the successful prediction of the functional form of the MDA relation, plus an overall agreement with the observed kinematics of stellar systems spanning eight orders of magnitude in size and 14 orders of magnitude in mass, I conclude that the "graviton picture" is sufficient (albeit probably not a necessary nor unique approach) to describe galactic dynamics on all scales well beyond the scale of the solar system. This suggests that, at least on galactic scales, gravity behaves as if it was mediated by massive particles.

• Journal of the korean Society of Automotive Engineers
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• v.15 no.1
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• pp.73-80
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• 1993

In this study, 3-dimensional linear and non-linear vehicle models are proposed to improve ride quality. The simulations of a vehicle passing over a bump were performed with those two vehicle models. The dynamic responses of the models were analyzed in time-domain and frequency-domain. Then, discomforts in each vibration axis and the combined-axes were evaluated based on the vibrations of the proposed models. The actual vehicle test results in time domain and frequency domain. Also, the discomfort values were compared. Then the validity of those two models were verified. Also, the design parameters of the suspension system are proposed for improving the ride quality.

• Journal of Digital Contents Society
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• v.16 no.3
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• pp.417-424
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• 2015

The research of occupational injury for safety and health is a comparatively recent occurrence. As labor activities took place regarding to employee concerns in industrial uprising, human resources health was tried to enhanced as a labor safety subject. Noticing that traditional statistics approach has limitations in learning future forecasting and major factors causing occupational injuries in each industry, Korean Government initiated a quantitative systematic simulation model project to analyze how the annual injury rate has been dropped and stays in a level for recent years. From this motivation and the project, system dynamics models have been developed to explain the mechanisms for reducing annual injury rate, and the mechanisms quantitatively. The main cause effects for the reduction of annual injury rate were due to the government driven investment on safety facilities. In overall viewpoint the gain achievable from these efforts has been reached a saturated level. However, it could reduce the annual injury rate if you chose the industry and size carefully. The model for forecasting, major injury factors, safety budget and allocation are introduced and analyzed, and Analyzing occupational injury related factors can also reduce employee injury and disease related costs, including medical care, quit, and disability assistance costs.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.5
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• pp.179-187
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• 2001

In this paper, a primary pressure regulating type ratio control system is developed for a metal belt CVT, and the CVT ratio changing characteristics are investigated by simulation and experiment. The hydraulic part of the ratio control system has a simple structure with one 3-way spool valve as a main ratio control valve and one bleed type variable force solenoid as a pilot valve. The mathematical modelling of the CVT hydraulic system is derived by considering the CVT shift dynamics. Simulation results of CVT speed ratio and the primary pressure agree with the experimental results demonstrating the validity of the dynamic models. It is found from the simulation and experimental results that the response time of speed ratio and primary pressure can be shortened by increasing the ratio control valve port area, and the size of feedback orifice of ratio control valve gives a damping effect on the primary pressure oscillation.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.1
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• pp.27-32
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• 2010

In this study, transonic flutter response characteristics have been studied for the AGARD 445.6 wing considering various turbulent models and several angle of attacks. The developed fluid-structure coupled analysis system is applied for flutter computations combining computational structural dynamics(CSD), finite element method(FEM) and computational fluid dynamics(CFD) in the time domain. The flutter boundaries of AGARD 445.6 wing are verified using developed computational system. For the nonlinear unsteady aerodynamics in high transonic flow region, DES turbulent model using the structured grid system have been applied for the wing model. Characteristics of flutter responses have been investigated for various angle of attack conditions. Also, it is typically shown that the current computation approach can yield realistic and practical results for aircraft design and test engineers.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.60-64
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• 1995

The conventional neural network models are a parody of biological neural structures, and have very slow learning. In order to emulate some dynamic functions, such as learning and adaption, and to better reflect the dynamics of biological neurons, M.M. Gupta and D.H. Rao have developed a 'dynamic neural model'(DNU). Proposed neural unit model is to introduce some dynamics to the neuron transfer function, such that the neuron activity depends on internal states. Integrating an dynamic elementry processor within the neuron allows the neuron to act dynamic response Numerical examples are presented for a model system. Those case studies showed that the proposed DNU is so useful in practical sense.