Helicopter human factors research

Helicopter flight is among the most demanding of all human-machine integrations. The inherent manual control complexities of rotorcraft are made even more challenging by the small margin for error created in certain operations, such as nap-of-the-Earth (NOE) flight, by the proximity of the terrain. Accident data recount numerous examples of unintended conflict between helicopters and terrain and attest to the perceptual and control difficulties associated with low altitude flight tasks. Ames Research Center, in cooperation with the U.S. Army Aeroflightdynamics Directorate, has initiated an ambitious research program aimed at increasing safety margins for both civilian and military rotorcraft operations. The program is broad, fundamental, and focused on the development of scientific understandings and technological countermeasures. Research being conducted in several areas is reviewed: workload assessment, prediction, and measure validation; development of advanced displays and effective pilot/automation interfaces; identification of visual cues necessary for low-level, low-visibility flight and modeling of visual flight-path control; and pilot training

Perception enhancement system for automotive steering

Laboratory-based experiments were conducted to evaluate the effect of the frequency and scale of transient vibration events on the human detection of road surface type by means of steering wheel vibration. The study used steering wheel tangential direction acceleration time histories which had been measured in a mid-sized European automobile that was driven over three different types of road surface. The steering acceleration stimuli were manipulated by means of the mildly non-stationary mission synthesis (MNMS) algorithm in order to produce test stimuli which were selectively modified in terms of the number, and size, of transient vibration events they contained. Fifteen test participants were exposed to both unmanipulated and manipulated steering wheel rotational vibration stimuli, and were asked to indicate, by either “yes or no”, whether the test stimuli was from a target road surface which was displayed on a board. The findings suggested that transient vibration events play a key role in the human detection of road surface type in driving situations. Improvements of up to 20 percentage points in the rate of correct detection were achieved by means of selective manipulation of the steering vibration stimuli. The results also suggested, however, that no single setting of the MNMS algorithm proved optimal for all three road surface types that were investigated

Effect of transient event frequency content and scale on the human detection of road surface type

This paper describes two laboratory-based experiments which evaluate the effect of transient event frequency content and scale on the human detection of road surface type by means of steering wheel vibration. This study used steering wheel tangential direction acceleration time histories which had been measured in a mid-sized European automobile that was driven over two different types of road surface. The steering acceleration stimuli were manipulated by means of the mildly non-stationary mission synthesis (MNMS) algorithm in order to produce test stimuli which were selectively modified in terms of the number, and size, of transient vibration events they contained. Fifteen test participants were exposed to both unmanipulated and manipulated steering wheel rotational stimuli by means of a steering wheel vibration simulator. For each road surface type a total of 45 vibration test stimuli were presented to each participant. Each participant was asked to state, by means of a simple "yes" or "no" answer, whether each individual stimuli was from a road surface which was being presented in front of the simulator as a picture on a large board. Using Signal Detection Theory as the analytical framework the results were summarized by means of the detectability index d' and by means of receiver operating curve (ROC) points. Improvements of up to 20 percentage points in the rate of correct detection were achieved by means of selective manipulation of the steering vibration stimuli. The results suggested that no single setting of the MNMS algorithm proved optimal for both two road surface types that were investigated

A voyage to Mars: A challenge to collaboration between man and machines

A speech addressing the design of man machine systems for exploration of space beyond Earth orbit from the human factors perspective is presented. Concerns relative to the design of automated and intelligent systems for the NASA Space Exploration Initiative (SEI) missions are largely based on experiences with integrating humans and comparable systems in aviation. The history, present status, and future prospect, of human factors in machine design are discussed in relation to a manned voyage to Mars. Three different cases for design philosophy are presented. The use of simulation is discussed. Recommendations for required research are given

PRESENCE: A human-inspired architecture for speech-based human-machine interaction

Recent years have seen steady improvements in the quality and performance of speech-based human-machine interaction driven by a significant convergence in the methods and techniques employed. However, the quantity of training data required to improve state-of-the-art systems seems to be growing exponentially and performance appears to be asymptotic to a level that may be inadequate for many real-world applications. This suggests that there may be a fundamental flaw in the underlying architecture of contemporary systems, as well as a failure to capitalize on the combinatorial properties of human spoken language. This paper addresses these issues and presents a novel architecture for speech-based human-machine interaction inspired by recent findings in the neurobiology of living systems. Called PRESENCE-"PREdictive SENsorimotor Control and Emulation" - this new architecture blurs the distinction between the core components of a traditional spoken language dialogue system and instead focuses on a recursive hierarchical feedback control structure. Cooperative and communicative behavior emerges as a by-product of an architecture that is founded on a model of interaction in which the system has in mind the needs and intentions of a user and a user has in mind the needs and intentions of the system