Performance degradation due to interruptions is a critical issue, particularly when people are supervising highly autonomous systems in time and safety critical environments. Previous research in the development of automated support to help supervisory control operators resume task activities after an interruption has had limited success. This paper describes two new interruption recovery approaches that attempt to mitigate the disadvantages of previous approaches. In particular, this paper describes the design and initial investigation of a prototype assistive interface developed to support interruption recovery for supervisory control of multiple unmanned aerial vehicles (UAVs). These two 'replay'-type interruption recovery approaches enable increased user-control of the event discovery process and provide event 'bookmarks' to highlight emergent system events. The findings from this initial study provide several recommendations for the future design of interruption assistance tools for human supervisory control tasks.

(212 words OK)Objective: To explore how a single master alarm system affects drivers' responses when compared to multiple, distinct warnings. Background: Advanced driver warning systems are intended to improve safety, yet inappropriate integration may increase the complexity of driving, especially in high workload situations. This study investigated the effects of auditory alarm scheme, reliability, and collision event-type on driver performance. Method: A 2x2x4 mixed factorial design investigated the impact of two alarm schemes (master vs. individual) and two levels of alarm reliability (high and low) on distracted drivers' performance across four collision event-types (frontal collision warnings, left and right lane departure warnings, and followvehicle fast approach). Results: Participants' reaction times and accuracy rates were significantly affected by the type of collision event and alarm reliability. The use of individual alarms, rather than a single master alarm, did not significantly affect driving performance in terms of reaction time or response accuracy. Conclusion: Even though a master alarm is a relatively uninformative warning, it produced statistically no different reaction times or accuracy results when compared to information-rich auditory icons, some of which were spatially located. In addition, unreliable alarms negatively impacted driver performance, regardless of event type or alarm scheme.Application: These results have important implications for the development and implementation of multiple driver warning systems.

Performance degradation due to interruptions is a critical issue, particularly when people are supervising highly autonomous systems in time and safety critical environments. Previous research in the development of automated support to help supervisory control operators resume task activities after an interruption has had limited success. This paper describes two new interruption recovery approaches that attempt to mitigate the disadvantages of previous approaches. In particular, this paper describes the design and initial investigation of a prototype assistive interface developed to support interruption recovery for supervisory control of multiple unmanned aerial vehicles (UAVs). These two 'replay'-type interruption recovery approaches enable increased user-control of the event discovery process and provide event 'bookmarks' to highlight emergent system events. The findings from this initial study provide several recommendations for the future design of interruption assistance tools for human supervisory control tasks.

Appropriate user interface tools providing delay feedback information can help modify user expectations and delay tolerance. These tools are especially valuable when delay conditions exceed a few seconds or when task constraints and system demands are high. Interface designs for HCNI tasks should consider assistant-style presentations of delay feedback, information freshness, and network characteristics. Assistants should also gather awareness of user time constraints.

This paper focuses on user's delay perception and tolerance in a simulated computer supported cooperative work (a special case of HCI) environment, as well as the non-technological factors affecting user's delay tolerance. Five factors (gender, Type-A personality, task-type, difficulty level and time delay) were investigated by a mixed 2 (male vs. female, between-group) X 2 (object search vs. budget calculation, within-group) X 2 (hard vs. easy, within-group) factorial experimental design. Type-A personality and time delay were nested in gender and treatment respectively. Results showed that users could estimate 2–6 second delay accurately, but would underestimate shorter delays (<2 seconds) and overestimate longer delays (>6 seconds). MANOVA analysis indicated that task-type, difficulty level and time delay were major factors affecting user's delay tolerance. We also found some important interaction effects between independent variables. The findings suggest that users can adjust their delay tolerance based on the context information such as task-type and difficulty level.