Effects of Touch, Voice, and Multimodal Input, and Task Load on Multiple-UAV Monitoring Performance During Simulated Manned-Unmanned Teaming in a Military Helicopter.

OBJECTIVE: We evaluated three interface input methods for a simulated manned-unmanned teaming (MUM-T) supervisory control system designed for Air Mission Commanders (AMCs) in Black Hawk helicopters. BACKGROUND: A key component of the U.S. Army's vision for unmanned aerial vehicles (UAVs) is to integrate UAVs into manned missions, called MUM-T (Department of Defense, 2010). One application of MUM-T is to provide the AMC of a team of Black Hawk helicopters control of multiple UAVs, offering advanced reconnaissance and real-time intelligence of flight routes and landing zones. METHOD: Participants supervised a (simulated) team of two helicopters and three UAVs while traveling toward a landing zone to deploy ground troops. Participants classified aerial photographs collected by UAVs, monitored instrument warnings, and responded to radio communications. We manipulated interface input modality (touch, voice, multimodal) and task load (number of photographs). RESULTS: Compared with voice, touch and multimodal control resulted in better performance on all tasks and resulted in lower subjective workload and greater subjective situation awareness, ps < .05. Participants with higher spatial ability classified more aerial photographs ( r = .75) and exhibited shorter response times to instrument warnings ( r = -.58) than participants with lower spatial ability. CONCLUSION: Touchscreen and multimodal control were superior to voice control in a supervisory control task that involved monitoring visual displays and communicating on radio channels. APPLICATION: Although voice control is often considered a more natural and less physically demanding input method, caution is needed when designing visual displays for users sharing common communication channels.

Effects of Adjacent Vehicles on Judgments of a Lead Car During Car Following.

OBJECTIVE: Two experiments were conducted to determine whether detection of the onset of a lead car's deceleration and judgments of its time to contact (TTC) were affected by the presence of vehicles in lanes adjacent to the lead car. BACKGROUND: In a previous study, TTC judgments of an approaching object by a stationary observer were influenced by an adjacent task-irrelevant approaching object. The implication is that vehicles in lanes adjacent to a lead car could influence a driver's ability to detect the lead car's deceleration and to make judgments of its TTC. METHOD: Displays simulated car-following scenes in which two vehicles in adjacent lanes were either present or absent. Participants were instructed to respond as soon as the lead car decelerated (Experiment 1) or when they thought their car would hit the decelerating lead car (Experiment 2). RESULTS: The presence of adjacent vehicles did not affect response time to detect deceleration of a lead car but did affect the signal detection theory measure of sensitivity d' and the number of missed deceleration events. Judgments of the lead car's TTC were shorter when adjacent vehicles were present and decelerated early than when adjacent vehicles were absent. CONCLUSION: The presence of vehicles in nearby lanes can affect a driver's ability to detect a lead car's deceleration and to make subsequent judgments of its TTC. APPLICATION: Results suggest that nearby traffic can affect a driver's ability to accurately judge a lead car's motion in situations that pose risk for rear-end collisions.

Effects of oncoming vehicle size on overtaking judgments.

During overtaking maneuvers on two-way highways drivers must temporarily cross into the opposite lane of traffic, and may face oncoming vehicles. To judge when it is safe to overtake, drivers must estimate the time-to-contact (TTC) of the oncoming vehicle. Information about an oncoming vehicle's TTC is available in the optical expansion pattern, but it is below threshold during high-speed overtaking maneuvers, which require a large passing distance. Consequently, we hypothesized that drivers would rely on perceived distance and velocity, and that their overtaking judgments would be influenced by oncoming vehicle size. A driving simulator was used to examine whether overtaking judgments are influenced by the size of an oncoming vehicle, and by whether a driver actively conducts the overtaking maneuver or passively judges whether it is safe to overtake. Oncoming motorcycles resulted in more accepted gaps and false alarms than larger cars or trucks. Results were due to vehicle size independently of vehicle type, and reflected shifts in response bias rather than sensitivity. Drivers may misjudge the distances of motorcycles due to their relatively small sizes, contributing to accidents due to right-of-way violations. Results have implications for traffic safety and the potential role of driver-assistance technologies.