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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.

Apex: MIDAS is a tool for rapidly developing 3-D models and simulations of human performance in complex operational environments, for example, modeling how an astronaut would use a new display interface. Apex is an autonomy architecture that provides the decision-making model for the simulated human (operator) in MIDAS. Procedural knowledge for each operator is encoded in Apex's Procedure Description Language (PDL). As the MIDAS simulation runs, sensory events (visual and auditory) are passed to Apex, which responds by invoking behaviors in the operator as specified in its active procedures. Apex also includes Sherpa, a visualization tool that provides detailed views of the operator's procedure execution status and event history with task timelines.
 
           
  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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