Michael G. Shafto

Effects of target luminance and cue validity on the latency of visual detection

Hughes (1984) has reported that the magnitude of the cue-validity effect in luminance detection is unaffected by target luminance. In three experiments, we explored the possible basis of this counterintuitive finding. The experiments focused on the design of the Hughes study, in which target luminance was treated as a between-blocks variable. Our results reveal that when target luminance is varied randomly within trial blocks, the cue-validity effect grows with declining target luminance. The difference between our findings and those of Hughes is interpreted in terms of cue-utilization strategies, which may adapt to target luminance when luminance remains invariant within trial blocks. Several alternative conceptions of the nature and locus of the cuevalidity effect in luminance detection are considered in light of these results.

FORMAL ASPECTS OF PROCEDURES: THE PROBLEM OF SEQUENTIAL CORRECTNESS

A formal, model-based approach is proposed for the development and evaluation of the sequences of actions specified in procedures. The approach employs methodologies developed within the discipline of discrete-event and hybrid systems control. We demonstrate the proposed approach through an evaluation of a procedure for handling an irregular engine-start on board a modern commercial aircraft.

MODE USAGE IN AUTOMATED COCKPITS: SOME INITIAL OBSERVATIONS

Abstract Mode confusion is increasingly becoming a significant contributor to accidents and incidents involving highly automated airliners; in the last seven years there have been four airline accidents in which mode problems were present. This paper attempts to provide some initial observations about modes and how pilots use them. The authors define the terms “mode“,“mode transitions“,“mode configurations“, and propose a framework for describing and classifying modes. Preliminary results from a field study that documented mode usage in “Glass Cockpit” aircraft are presented. The data were collected during 30 flights onboard Boeing 757/767 type aircraft. Summary of the data depicts the paths that pilots use in transitioning from one mode to another. Analysis of the data suggest that these mode transitions are influenced by changes in aircraft altitude as well as by two factors in the operational environment: the type of air traffic control facility supervising the flight, and the type of instruction (clearance) issued.

Aviation safety: modeling and analyzing complex interactions between humans and automated systems

The on-going transformation from the current US Air Traffic System (ATS) to the Next Generation Air Traffic System (NextGen) will force the introduction of new automated systems and most likely will cause automation to migrate from ground to air. This will yield new function allocations between humans and automation and therefore change the roles and responsibilities in the ATS. Yet, safety in NextGen is required to be at least as good as in the current system. We therefore need techniques to evaluate the safety of the interactions between humans and automation. We think that current human factor studies and simulation-based techniques will fall short in front of the ATS complexity, and that we need to add more automated techniques to simulations, such as model checking, which offers exhaustive coverage of the non-deterministic behaviors in nominal and off-nominal scenarios. In this work, we present a verification approach based both on simulations and on model checking for evaluating the roles and responsibilities of humans and automation. Models are created using Brahms (a multi-agent framework) and we show that the traditional Brahms simulations can be integrated with automated exploration techniques based on model checking, thus offering a complete exploration of the behavioral space of the scenario. Our formal analysis supports the notion of beliefs and probabilities to reason about human behavior. We demonstrate the technique with the Überlingen accident since it exemplifies authority problems when receiving conflicting advices from human and automated systems.

Human vs. Autonomous Control of UAV Surveillance

We describe an approach to evaluating algorithmic and human performance in directing UAV-based surveillance. Its key elements are a decision-theoretic framework for measuring the utility of a surveillance schedule and an evaluation testbed consisting of 243 scenarios covering a well-defined space of possible missions. We apply this approach to two example UAV-based surveillance methods, an algorithm called 2-opt and a human-directed approach, then compare them to identify general strengths and weaknesses of each method.

Human-centered computing at NASA

That statement also accurately and succinctly describes NASA’s working definition of HCC. In the last issue of Intelligent Systems, Robert Hoffman and his colleagues presented a framework encompassing the various approaches that constitute the world of HCC.1 This special issue examines the particular region NASA is exploring within this vast world— the working definition of HCC shaped by NASA’s mission requirements,2 available resources, and existing investments.

Canonical Correlation Analysis of Data on Human-Automation Interaction

Canonical correlation analysis is a type of multivariate linear statistical analysis, first described by Hotelling (1935), which is used in a wide range of disciplines to analyze the relationships between multiple independent and multiple dependent variables. We argue that canonical correlation analysis is the method of choice for use with many kinds of datasets encountered in human factors research, including field-study data, part-task and full-mission simulation data, and flight-recorder data. Although canonical correlation analysis is documented in standard textbooks and is available in many statistical computing packages, there are some technical and interpretive problems which prevent its routine use by human factors practitioners. These include problems of computation, interpretation, statistical significance, and treatment of discrete variables. In this paper we discuss these problems and suggest solutions to them. We illustrate the problems and their solutions based on our experience in using canonical correlation in the analysis of a field study of crew-automation interaction in commercial aviation.

Information Organization in the Airline Cockpit Lessons From Flight 236

We describe the all-engine-out landing of Air Transat Flight 236 in the Azores Islands (August 24, 2001) and use certain aspects of that accident to motivate a conceptual framework for the organization and display of information in complex human-interactive systems. Four hours into the flight, the aircraft experienced unusual oil indications. Two hours later, a fuel system failure led to a full-blown emergency that was not evident to the crew until it was too late. Although all relevant data to avoid the emergency were available to the aircraft computer systems, the design choices made about what to display and how to display it kept the pilots “in the dark.” The framework proposed here consists of six levels, beginning from the extraction of data from physical signals, abstracting from raw data to form visual representations on the user interface, and finally integrating high-level elements and information structures. We illustrate how the framework can be used to analyze some of the shortcomings in current display design, and we discuss some principles of information organization and formal analysis of task logic that might help to improve design. Finally, we sketch a design for a helicopter engine display based on these principles.

Employing Simulation to Evaluate Designs: The APEX Approach

Computer simulation could be used to reduce the cost of designing human-machine systems, just as it is currently used in the design process for inanimate systems such as electronic circuits. However, past efforts have met with limited success due to difficulties modeling the human components of these systems. We have constructed a software framework and methodology for modeling human performance, APEX, that addresses several of these difficulties. This paper describes a methodology for using APEX to evaluate designs in complex, dynamic task environments; we then illustrate this process using an example from the domain of air traffic control.

Contributions to IT: A View from Ames Research Center

Learn how NASA Ames Research Center has been contributing to IT over the decades and about its recent contributions in supercomputing, modeling, and simulation; next-generation air-traffic management; intelligent systems; and complex data analysis.