The Midas Human Performance Model

Abstract

A unique software tool for conducting human factors analyses of complex human-machine systems has been developed at NASA Ames Research Center. Called the Man-Machine Integration Design and Analysis System (MIDAS), this simulation system contains models of human performance that can be used to evaluate candidate procedures, controls, and displays prior to more expensive and time consuming hardware simulators and human subject experiments. While this tool has been successfully applied to research issues in several domains, particularly in aeronautics, a desire to expand its functionality and its ease of use has led to the construction of a new object-oriented system. This new version of MIDAS contains a substantially modified human performance model, one that is aimed at being more consistent with empirical data on human behavior and more natural for designers to apply to the analyses of complex new designs. This paper offers a summary of this new human performance model, together with justifications for some of its main components, and indicates plans for its subsequent verification and validation.

A Review of Computer-Based Human Behavior Representations and Their Relation to Military Simulations

“…According to Tyler et al (1998), the most recent revision of the MIDAS architecture is divided into five high-level components:…”

“…One of the principal purposes of the MIDAS rearchitecture was to align the human operator model more closely with typical models of human information processing (Tyler et al, 1998). According to Hart et al (2001), the human operator model comprises six components: sensory input, memory, decision-making, attention, SA, and output behavior.…”

Optimizing Biology Research Tasks in Space Using Human Performance Modeling and Virtual Reality Simulation Systems Here on Earth

“…Static models are theoretical representations and commonly use behavioral information gathering techniques [15], cognitive task analysis [16][17][18], and work domain analysis techniques [19] to predict operator-environment interactions. Static models also include models of operator characteristics such as visual, cognitive, attentional, situation awareness, or static workload models [20][21][22][23]. Some static models also maintain human motion and posture simulation/prediction models [24].…”

Evaluation and Application of MIDAS v2.0

“…The relationships among these components are illustrated in Figure 3. (19), they will be summarized only briefly, with the exception of the decision-making model. SENSORY INPUT -The operator obtains visual information about objects in the world from their symbolic representation (i.e., attributes that are attached to the objects) along with information about the objects' surroundings such as ambient lighting.…”