John W. Keller

Left. No, Right! Development of the Frame of Reference Transformation Tool (FORT):

A computational model was developed to predict the spatial-cognitive difficulties imposed when the operator must transform information along up to 6 degrees of freedom between a display (viewed at different orientations), and either a cognitive understanding or a compensatory control. The model applies to pilots, robotics operators, navigators or surgeons using endoscopic procedures. Penalties (in workload, errors or time) in the frame of reference transformation (FORT) are based on psychological findings in spatial cognition, such as mental rotation, depth compression, population stereotypes and verbally mediated strategies. We present the graphical user interface for exercising the model; then show how we have applied it to an astronaut space-shuttle, Hubble rendezvous sequence. Finally we validate the model against two existing data sets, one for cognition and one for control. The model could be used as the basis for both a design analysis tool and a real-time operator aiding system.

Human Factors in High-Altitude Mountaineering

We describe the human performance and cognitive challenges of high altitude mountaineering. The physical (environmental) and internal (health) stresses are first described, followed by the motivational factors that lead people to climb. The statistics of mountaineering accidents in the Himalayas and Alaska are then described. We then present a detailed discussion of the role of decision-making biases in mountaineering mishaps. We conclude by discussing interpersonal factors, adaptation, and training issues.

A Pilot Spatial Orientation Aiding System

Spatial disorientation (SD) is a normal human response to accelerations in flight. Its cost to the US military is over

Assessing Dynamic Value for Safety Gear During a Rock Climbing Task

300 million per year, with comparable costs to US civil aviation. Due to significantly increased research over the past decade, some progress is being made in helping pilots avoid SD’s adverse consequences (i.e., mishaps, incidents, or accidents). We used a multi-sensory model-based approach to intelligently trigger SD countermeasures. Results for two simulated and one actual SD event were very promising, and indicate that the next research step should include verifying and validating our models, and evaluating our spatial orientation aiding system (SOAS) via pilot-in-the-loop simulations and flight tests. SOAS evaluates the aircraft motions, pilot workload, aircraft state, and world state to determine if the pilot is probably suffering from SD, and, if so, SOAS applies a range of countermeasures to assist the pilot in recognizing the SD and recovering. Countermeasures include visual cues, audio cues, audio recovery commands, tactile cues, and olfactory cues, as well as the more extreme measures of auto-recovery and auto-ejection (to save the pilots life, only if all other countermeasures have failed).

Task Switching in Rock Climbing: Validation of a Computational Model for Different Skill Levels

Value is a component of the SEEV model of attention combined with measures of salience, effort, and expectancy to characterize areas of interest in a visual workspace. In the current project, an assessment of dynamic value was created by prompting rock climbers to assess their post-hoc priority for placing safety gear at various points during a climb when the risk of injury from a fall varied. Analyses determined that, for expert and non-expert rock climbers, gear placement priority rose as time since the most recent gear placement increased, after controlling for climbing speed. Prediction of the attentional value of a target via dynamic estimates may be applied in other highly dynamic environments.

N-SEEV in SOAS Predicting Time to Notice for Multi-Modal Cockpit Alerting Events

Thirty-two rock climbers, all self-identifying as capable of lead climbing (place protective gear in the rock, to mitigate the risks of falling), climbed an outdoor route while placing what they believed was the necessary amount of protection. Cameras recorded the percentage of time they spent climbing upward (productivity) relative to placing protection (safety). We then applied STOM (strategic task overload model) to predict percent time-on-task, using the differences in their ratings of task interest, task priority, and task difficulty as predictors. The model significantly predicted time on task for the participants categorized as experts, but not for those categorized as non-experts. Time on the climbing (versus protection) task for the expert group, but not the non-expert group, was also predicted by a derived measure inferred to assess risk tolerance in climbing.

Cognitive Task Analysis of Commercial Jet Aircraft Pilots during Instrument Approaches for Baseline and Synthetic Vision Displays

This paper presents the current work to extend the N-SEEV model of visual attention to both the auditory and tactile modalities in support a cockpit adaptive automation system for pilot spatial disorientation. Cockpit countermeasure systems use visual, auditory and tactile modalities to communicate problems to the pilot. The SOAS spatial orientation aiding system uses all three modalities to support a disoriented pilot. The system initiates increasingly intrusive countermeasure as it determines that the probability and severity of a detected disorientation is increasing. N-SEEV has been included within SOAS to support the change to countermeasure levels based on the prediction of the pilot noticing countermeasure onset. Previous versions of N-SEEV could predict a time-to-notice for the onset of a visual cockpit countermeasure. In this work, N-SEEV is extended to include noticing predictions for both the auditory and tactile modes.