Visual Attention Allocation Between Robotic Arm and Environmental Process Control: Validating the STOM Task Switching Model

Fifty six participants time shared a spacecraft environmental control system task with a realistic space robotic arm control task in either a manual or highly automated version. The former could suffer minor failures, whose diagnosis and repair were supported by a decision aid. At the end of the experiment this decision aid unexpectedly failed. We measured visual attention allocation and switching between the two tasks, in each of the eight conditions formed by manual-automated arm X expected-unexpected failure X monitoring- failure management. We also used our multi-attribute task switching model, based on task attributes of priority interest, difficulty and salience that were self-rated by participants, to predict allocation. An un-weighted model based on attributes of difficulty, interest and salience accounted for 96 percent of the task allocation variance across the 8 different conditions. Task difficulty served as an attractor, with more difficult tasks increasing the tendency to stay on task

Exploring the Effects of Task Priority on Attention Allocation and Trust Towards Imperfect Automation: A Flight Simulator Study

The present study examined the effect of task priority and task load on attention allocation and automation trust in a multitasking flight simulator platform. Previous research demonstrated that, participants made less fixations and reported lower levels of trust towards the automation in the secondary monitoring under higher load on the primary tracking task (e.g., Karpinsky et al., 2018). The results suggested that participants perceived behaviors of the automated system less accurately due to less attention allocated to monitoring of the system, leading to decreased trust towards it. One potential explanation of the effect is that participants might have prioritized the tracking task due to the elevated task load over monitoring of the automation. The current study employed a 2 x 2 mixed design with task difficulty (low vs. high difficulty) and task priority (equal vs. tracking priority). Participants performed the central tracking task, the system monitoring task, and the fuel management task where the system monitoring was assisted by an imperfect automated system. Participants were instructed to either prioritize the central tracking task over the other two tasks or maximize performance for all tasks. Additionally, participants received feedback on their tracking performance reflecting an anchor of their baseline performance. The data indicated that participants rated lower performance-based trust in a multitasking environment when all tasks were equally prioritized, supporting the notion that task priority modulates the effect of task load

The Effect of Differing Degrees of Automation and Reliability on Simulated Luggage Screening Performance

The present work examined the effects of two types of decision support systems in a simulated luggage screening task: An input aid and an output aid. An input aid supports an operator’s information gathering. An output aid supports decision making and action selection. A Time-Accuracy Function (TAF) analysis was applied to isolate processing time from performance asymptote, which conventional performance measures such as sensitivity and response time do not distinguish one from the other. Sixty participants performed a luggage screening task unaided (manual condition), with the assistance of an input aid (spatial aid), and with the assistance of an output aid (decision aid) across different stimulus exposure durations of 250 ms, 500 ms, 1000 ms, 2000 ms, or 3000 ms. Participants were asked to judge the presence of a knife in each of the bags and either “stop” the bag or “pass” the bag. Reliability of the automated aids was 90% in Experiment 1 and 60% in Experiment 2. Experiment 1 showed that sensitivity increased with the assistance of both the input and the output aids as the stimulus exposure duration increased. The performance improvement was greater for the input aid than the output aid condition. Though processing times did not differ across the conditions, asymptotic performance level was higher when participants had the assistance of the input aid compared to the unaided condition. Experiment 2 and cross-experimental analysis demonstrated that the unreliable aids eliminated the benefit of the reliable aids. TAF analysis further showed that, although asymptotic performance can differ, processing times can remain constant regardless of DOA. The results imply that the input aid elevates asymptotic performance without influencing processing times, perhaps allowing operators to crosscheck their decisions within the restricted area of the search field identified by the aid. The present findings are inconsistent with the lumberjack hypothesis (Onnasch et al., 2013) and future research directions are provided

Dynamic virtual reality user interface for teleoperation of heterogeneous robot teams

This research investigates the possibility to improve current teleoperation control for heterogeneous robot teams using modern Human-Computer Interaction (HCI) techniques such as Virtual Reality. It proposes a dynamic teleoperation Virtual Reality User Interface (VRUI) framework to improve the current approach to teleoperating heterogeneous robot teams