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  MIDAS 1.0
           
  The existing system contains a set of integrated software modules, editors, and analysis tools produced in C, C++, and Lisp, with an architecture based in agent-actors theory.

Each major component, or agent, contains a common message passing interface, a body unique to that agent's purpose, and a common biographer structure which keeps track of important state data or events for analysis.

This uniform representation was chosen to provide modularity. The total system contains 350,000 executable lines of code, with about half of the total associated with a dynamic anthropometry model.

Once a user inputs or specifies operator, task, and equipment characteristics, MIDAS operates in two major modes. The first, Interactive Mode, supports scenario-independent layout of the crew station for assessments of visibility and legibility,examination of anthropometric characteristics, and analyses of cockpit topology and configuration. The output of MIDAS in this mode corresponds to cockpit geometry and external vision design guides, such as MIL-STD-1472 and AS-580B.
 

Image of User view of MIDAS application

User View of MIDAS (Click for Larger View)

 
           
  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.

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.

Updatable World Representation (UWR): In MIDAS, the UWR provides a structure whereby each of the multiple, independent human agents, representing individuals and cooperating teams of pilots and flight crews, accesses its own tailored or personalized information about the operational world. The contents of an UWR are determined, first, by pre-simulation loading of required mission, procedural, and equipment information. Then data is updated in each operator's UWR as a function of the perceptual mechanisms previously described. The data of each operator's UWR is operated on by daemons and rules to guide behavior and are the sole basis for a given operator's activity. Providing each operator with his/her own UWR accounts for the significant operational reality that different members of a cooperating control team have different information about the world in which they operate. Further, the individual operator may, or may not, receive a piece of information available to the sensory apparatus as a function of perceptual focus at the relevant point in the mission. It is of some significance that, while ideally the human operators' representation of the world would be consonant with the state of the world, in fact, this is rarely the case. The capability for both systematic and random deviation from the ground truth of the simulation world is a critically necessary component of any system that intends to represent and analyze non-trivial human performance.

The organization of perceptual data and knowledge about the world in an UWR is accomplished through a semantic net, a linked structure of object nodes that represent concepts. The relationship among these nodes is expressed as a "strength" or relatedness, where the strength of such relationships has been investigated to guide models of memory dynamics, i.e., interference, decay and rehearsal.
           
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