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  Embedded models- MIDAS
  MIDAS contains representations of human cognitive, perceptual and motor operations in order to simulate control and supervisory behavior. These models describe (within their limits of accuracy) the responses that can be expected of human operators interacting with dynamic automated systems. The fundamental human performance elements of these representations can be applied to any human-machine environment. Tailoring for the particular requirements of a given domain, largely in terms of human operator's knowledge and rule-base is, of course, a necessary step as the model is moved among domains.

Each of the human operators modeled by MIDAS contains the following models and structures, the interaction of which will produce a stream of activities in response to mission requirements, equipment requirements, and models of human performance capabilities and limits.

Physical Representations: An anthropometric model of human figure dimensions and dynamics has been developed in conjuntion with the Graphics Laboratory of the University of Pennsylvania. The model used is called Jack , and is an agent in the overall MIDAS system. The Jack agent's purpose is to represent human figure data (e.g., size and joint limits) in the form of a mannequin which dynamically moves through various postures to represent the physical activities of a simulated human operator. The graphic representation of the Jack agent also assists designers in questions of cockpit geometry, reach accommodation, restraint, egress, and occlusion.

Perception and Attention:The simulated human operator is situated in an environment where data constantly streams into the operator's physical sensors. While auditory, haptic, and proprioceptive systems serve an important role in the perception of information relevant to the operator of vehicles, within MIDAS the present focus has been on modeling visual perception.

In brief, during each simulation cycle, the perception agent computes what environment or cockpit objects are imaged on the operator's retina, tagging them as in/out of the peripheral and foveal fields of view (90 and 5 degrees, respectively), in/out of the attention field of view (variable depending on the task), and in/out of focus, relative to the fixation plane. An environmental object can be in one of several states of perceptual attention. Objects in peripheral visual fields are perceived and attentionally salient changes in their state are passed to the updatable world representation. In order for detailed information to be fully perceived, e.g., reading of textual messages, the data of interest must be in focus, attended, and within the foveal field of view for 200 ms. The perception agent also controls the simulation of commanded eye movements via defined scan, search, fixate, and track modes. Differing stimuli salience and pertinence are also accommodated through a model of pre-attention in which specific attributes, e.g. color or flashing, are monitored to signal an attentional shift.

MicroSaint Sharp (Simulation Engine): Micro Saint Sharp is a full-featured, discrete-event simulation modeling environment that simulates complex processes and solve difficult problems spanning a number of complex application domains. Micro Saint Sharp allows MIDAS to operates according to its hybrid discrete-continuous modeling principle. Micro Saint Sharp allows rapid model development through the use of flow charts and task networks. Micro Saint Sharp selects and sequences operator procedures based on information that is fed to it from the perception model inside of MIDAS. Micro Saint Sharp is a modular and flexible code base that can be used for a variety of applications. Micro Saint Sharp uses a plug-in interface and object-oriented model development, allowing easy integration with other external software applications. Micro Saint Sharp uses the Microsoft C# language which allows more complex mathematical and logical expressions and algorithms to be used in the model allowing more variable options (including integer, floating point, string, boolean, object as well as local and global variables). A key benefit to Micro Saint Sharp is its transparency through its use of an effective visualization environment and its ability to process model components in a multi-threaded fashion.

An example of the interaction between MIDAS and Micro Saint Sharp can be found below. Given vehicle location with respect to a feature in the environment, visibility and lighting levels and scan pattern, the perception model will inform Micro Saint Sharp when the perception level of the operator changes with respect to the feature. Likewise, scan patterns of the crewstation equipment coupled with dwell time effect perception level changes with respect to equipment. Given a perception level change and the operator procedures, Micro Saint Sharp may initiate an operator task to the motor control model such as a reach-object, a speaking task or a change of scan pattern. The figure below also illustrates the visual scan model within MIDAS. This visual scan model currently uses a probabilistic scan pattern that selects from a series of response distributions to accurately reflect a human’s visual scanning performance.

  The other analysis path supported by MIDAS is a dynamic simulation. The Simulation Mode provides facilities whereby specifications of the human operator, cockpit equipment, and mission procedures are run in an integrated fashion. Their execution results in activity traces, task load timelines, information requirements, and mission performance measures which can be analyzed based on manipulations in operator task characteristics, equipment, and mission context.
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