Automation Technology and Human Performance: Current Research and Trends

By Mark W. Scerbo | Go to book overview

The Global Implicit Measurement of Situation Awareness: Implications for Design and Adaptive Interface Technologies

Bart J. Brickman, Lawrence J. Hettinger, and Dean K. Stautberg

Logicon Technical Services, Inc.

Dayton, Ohio

Michael W. Haas and Michael A. Vidulich

Human Effectiveness Directorate

Air Force Research Laboratory

Wright-Patterson Air Force Base, Ohio

Robert L. Shaw

F.C.I. Associates

Beavercreek, Ohio


INTRODUCTION

The purpose of this paper is to describe the initial results of a novel approach to develop a reliable, objective methodology to assess crewmember Situation Awareness (SA) during simulated air-to-air combat missions. The Global Implicit Measurement (GIM) technique was developed at the US Air Force Research Laboratory's Synthesized Immersion Research Environment (SIRE) facility at Wright-Patterson Air Force Base, Ohio as part of a program of research devoted to developing virtually-augmented, multisensory, adaptive crewstation technologies for use in future tactical aircraft.

The GIM was designed to incorporate the strengths of traditional implicit measurement techniques (e.g., non-intrusive, performance-based, objective, precisely measurable) while limiting the weaknesses typically associated with implicit measures and other methods such as memory probe techniques (e.g., intrusiveness, reliance on imperfect memory, few observations, limited scope and generalizability) (see Brickman, et al. 1995 for a description of GIM).

In order to ensure that it benefits from a high level of operational validity, the first step in the GIM procedure is to provide a high level of specificity to the nature of pilot tasks involved in air combat. To this end, a detailed task analysis of the general characteristics of a typical mission is conducted in association with subject matter experts (USAF fighter pilots). The results of the task analysis provide a detailed description of the mission parsed into mission phases. The tasks associated with each phase are further segmented according to three major sub-headings: aviation, navigation, and communication. Specific mission tasks are then listed under each subheading to reflect the changing goals and sub-goals of the pilot throughout the mission. During an Air Base Defense mission, for example, a transition from a CAP phase to an intercept phase represents a radical change in the pilot's immediate goals, while the overall goal of bomber interception and return to safe air space remains. The task analysis is used to create a highly detailed set of rules of engagement, similar in nature to rules of engagement encountered by fighter pilots in an operational context. The rules derived from the task analysis place constraints on both mission performance parameters as well as the engagement of hostile targets. Each of the "rules" of engagement is treated as an individual implicit probe and assessed at the frame rate of the simulation.

As an example, the rules of engagement specify a radar mode for each mission segment (i.e., "track while scan" as opposed to "single target track"). If the pilot configures the radar correctly for that portion of the mission, the resulting score on that implicit metric would reflect adequate SA (i.e., a numerical value

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