Model of the Human Observer and Controller of a Dynamic System Theory and Model Application to Ship Handling

Wewerinke, P.H.; Tak, C. van der

doi:10.1016/b978-0-08-036226-7.50030-2

Cited by 6 publications

(4 citation statements)

References 2 publications

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“…The main approaches to study overtaking are cellular automata modelling [7][8][9][10][11][12] and differential equation modelling [13,14]. Also, the system theoretic approach and the neural network method are applied to study the human operating behavior in overtaking procedure [15][16][17]. The overtaking distance-based approach is another method which has recently been used [5,[18][19][20].…”

Section: Related Work On Overtaking Moldeingmentioning

confidence: 99%

ANFIS based modeling for overtaking maneuver trajectory in motorcycles and autos

Ghaffari

Alimardani

Khodayari

et al. 2011

2011 IEEE International Conference on Control System, Computing and Engineering

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Overtaking is a common driving maneuver and also the most complex one. Studying this maneuver is considered to be one of the toughest challenges in the development of autonomous vehicles. Here, a novel overtaking model based on adaptive neuro-fuzzy inference system is proposed. This model is designed for two vehicle classes: motorcycles and autos. The presented model is able to simulate and predict the trajectory of the overtaker vehicle in real traffic flow. In this model, important factors such distance, velocity, acceleration and the movement angle of the overtaker vehicle are considered. Using the field data, the performance of the model is validated and compared with the real traffic datasets. The results show very close compatibility between the field and model trajectory.

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Section: Related Work On Overtaking Moldeingmentioning

confidence: 99%

ANFIS based modeling for overtaking maneuver trajectory in motorcycles and autos

Ghaffari

Alimardani

Khodayari

et al. 2011

2011 IEEE International Conference on Control System, Computing and Engineering

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“…The results are given in Ref. (2) and e x used i� the next chapter. In order to include u-terms in eq (4) x e can be augmented resultirig (again) in the standard regulator control problem.…”

Section: Task Environmentmentioning

confidence: 99%

“…A "reasonable" (suboptimal) scanning strat egy to optimize U is given by System performance is governed by the given disturbance input wa nd the control input (see eq (2)). The control input is composed of the regula tor control ur and the maneuver control u m (see eq (23»).…”

Section: Perception and Estimation Of The Future Desired Statementioning

confidence: 99%

Model Of The Human Observer and Controller Of A Dynamic System Theory and model application to ship handling

Wewerinke

Perdok

Tak

Proceedings of the 1988 IEEE International Conference on Systems, Man, and Cybernetics

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ABSmACTThe MMS model presented in this paper describ es rather detailed human control of a dynamic syst em . The model is an int egration and extension of previously developped (validated) (sub)models.The model describes human control' of a dynamic system, involvingi nte rmi t tent control behavior during finite time intervals. and, therefore . deci sion making and planning and continuous regulating. Another central element i3 that the control is based on the perceived visual information from instruments and the outside world. Observing this visual scene is a complex process (e .g. involving preview) and intimately related to the control task. A model for visual scanning render s a useful insi ght in display-and na vigat ional quest ions . The model is being applied to the control of a ship entering a harbor. The preliminary results of this study show that the model adequately describes this complex control task.It is anticipat ed that the MMS model is suffiCient ly genera l to be useful to investigate a variety of man-mach ine systems. e.g. in the important ar'ea of robotics and in the handling of ships. helicopters, etc.

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“…This attention allocation is modeled in [3]. Basically the strategy is to perform the most important task first, so as to achieve the overall goal.…”

Section: Generalmentioning

confidence: 99%

Model analysis of adaptive car driving behavior

Wewerinke

1996 IEEE International Conference on Systems, Man and Cybernetics. Information Intelligence and Systems (Cat. No.96CH35929)

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This paper deals with two modeling approaches to car driving. The first one is a system theoretic approach to describe adaptive human driving behavior. The second approach utilizes neural networks.As an illustrative example the overtaking task is considered and modeled in system theoretic terms. Model results are used to teach a neural network. The results show that a neural network is able to learn this task even when certain task variables change. The next step is to perform an experiment with real human operators in order to assess the validity of both modeling approaches and their relative merit.

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Model of the Human Observer and Controller of a Dynamic System Theory and Model Application to Ship Handling

Cited by 6 publications

References 2 publications

ANFIS based modeling for overtaking maneuver trajectory in motorcycles and autos

ANFIS based modeling for overtaking maneuver trajectory in motorcycles and autos

Model Of The Human Observer and Controller Of A Dynamic System Theory and model application to ship handling

Model analysis of adaptive car driving behavior

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