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Time estimation is a fundamental behavioral characteristic used by all humans when completing task sequences in the real world. Properly characterizing the manner that humans engage in time-critical tasks, as well as the interaction among these tasks, is necessary when developing reliable computational models of human performance to be used to simulate real-world human-system performance. The current paper introduces the notion of estimating time available, time required, and time onset to complete behaviors within real environmental contexts. It also summarizes relevant research on over- and under-estimating of time, and outlines critical factors - workload and windows of opportunity - that impact estimates of time. The paper culminates in the development of a new domain- and platform-independent conceptual model, dubbed TEMPORA, the Time Estimation Model for Predicting Onset, Required and Available time.

The Man-machine Integration Design and Analysis System (MIDAS) is an integrated human performance modeling software tool that is based on mechanisms that underlie and cause human behavior. A PC-Windows version of MIDAS has been created that integrates the anthropometric character “Jack™”1 with MIDAS’ validated perceptual and attention mechanisms. MIDAS now models multiple simulated humans engaging in goal-related behaviors. New capabilities include the ability to predict situations in which errors and/or performance decrements are likely due to a variety of factors including concurrent workload and performance influencing factors (PIFs). This paper describes a new model that predicts the effects of microgravity on a mission specialist’s performance, and its first application to simulating the task of conducting a Life Sciences experiment in space according to a sequential or parallel schedule of performance.

A new method, combining virtual environment simulation technologies with unique human performance modeling software is being used to design, test and evaluate procedures for future biology experiments aboard the International Space Station (ISS). The Man Machine Integration Design and Analysis System (MIDAS) simulates human performance through seven underlying architectural components. The models interact producing results such as astronaut work load and experiment success rates given environmental inputs and timing constraints. Graphical models of biology research equipment and samples are provided by the Virtual Glovebox (VGX), a state-of-the-art simulation system mimicking the real Space Station systems. Human-in-the-loop experiment simulation using the VGX also enables validation of human-environment interactions predicted by MIDAS.

The Requirements and Technical Concepts for Aviation, Inc. (RTCA) has recently proposed a new concept known as “free flight” for guiding the separation of aircraft in the National Airspace System (NAS). “Free flight” in the United States is a Federal Aviation Administration (FAA) strategic goal for system capacity and for Air Traffic Services to improve accessibility, flexibility, and predictability in the national airspace in order to reduce flight times, crew resources, maintenance, and fuel costs. The scenarios in the current experiment were used to explore the farthest out parameters of “free flight” anticipated by RTCA in the year 2025.

The Federal Aviation Administration (FAA) has established the strategic goal for System Capacity and Air Traffic Services to improve accessibility, flexibility and predictability in the aviation community in order to reduce flight times, crew resources, maintenance, and fuel costs. Free flight is a system concept that addresses this goal. However, the potential for certain human performance costs arise, such as a increases in flight crew workload, or decreases in flight crew errors as predicted by Supervisory Control Theory. An evaluation of system costs associated with transitioning to Free Flight using two First Principles modeling approach, the Man-Machine Integration Design and Analysis System (MIDAS) and the Integrated Performance Modeling Environment (IPME) will be performed. IPME is expected to show differential human performance effects in cockpit and air traffic control system performance over those predicted by Air MIDAS over 50 Monte Carlo simulation runs.