Designing Data Fusion Displays for Situation Awareness: Phase 1 Results

1. Designing Data Fusion Displays for Situation Awareness: Phase 1 Results Phillip L. Morgan, Samuel M. Waldron, John Patrick & Dylan M. Jones 5*A Research Excellence RAE (2001) Fundedby UK MOD DIF DTC Project 4.9: Aim The battlefield is typically a highly dynamic environment and the proliferation of information sources, both onboard (radar, infra-red etc.) and off-board (e.g., data link), has meant that operators find themselves “swamped with data and starved of information”. In short, operators have poor SA, where SA broadly refers to the operators’ understanding of the environment.Whilst data fusion seeks to improve operators’ performance by reducing their workload, we have to ensure that fused data supports directly the operators’ cognitive processes during task performance. It is not inevitable that fusion technologies will achieve this. Therefore, Project 4.9 seeks to investigate the relationship between fused displays and SA in order to provide feedback to developers concerning the effective and efficient design of fused displays. In most experiments we also monitored eye movements using Tobii 1750 Eye Trackers to measure strategy One consequence of data fusion is that operators often have to ‘drill-down’ into fused data to reveal more information which requires time and both physical and mental effort… Investigating the Information Access Cost (IAC) Aim: To investigate the effects of different levels of IAC on memory, strategy and willingness to drill-down. Low IAC is known to encourage interaction-intensive strategies whereas high IAC leads to more memory-intensive strategies (Fu & Gray, 2004) Task: Similar to a military resource allocation task, in the Blocks World Task (BWT) participants copy a target window (TW) by selecting from a palette of different coloured blocks and moving them into a workspace window (WW) IAC Conditions: High (mask on all windows and delay on uncovering TW), Medium (same as High with no delay), Low (no masks) Information Fusion Testbed (IFT) Aim: To assess location estimates using a simulated flight with fused and unfused data Task: Pilots flew a series of Suppression of Enemy Air Defence (SEAD) missions and when prompted estimated the positions of fixed locations Fusion Conditions: Fused (from two aircraft), Fused Drill-Down (option to reveal more information about data), Unfused (raw sensor data) Workload Manipulation: Pilots had to estimate 1 or 3 locations TW WW PALETTE Low IAC Condition High IAC Condition • Main Findings • Generally, more blocks correctly recalled in High IAC although faster to complete in Low IAC • TW unmasked more with Medium IAC vs. High IAC (Expt. 1) • TW examined longer in High vs. Medium IAC (Expt. 2) • No effect of instructing participants that time to completion and number of moves were not important (Expt. 2) • Snapshot from the Fused Drill-Down Condition • Main Findings Experiment 1 (in collaboration with QinetiQ): To evaluate fusion technologies being used within the IFT in its development at QinetiQ • 6 RAF pilots (minimum 10 yrs flying experience) The extent to which individuals rely on a display as an external memory source reduces as the cost associated with accessing information increases Recommendation Introducing a small cost in accessing information can encourage more task-relevant processing, as demonstrated in the ability to remember more critical information, consequently improving SA Figure 1 Figure 2 Investigating IAC and Planning Within More Complex Problem Solving Tasks • During Trial: Fused Drill-Down more accurate than Fused and Unfused and more accurate in Fused low workload conditions (Fig. 1) • Recall: Fused Drill-Down better than Fused, but Fused not better than Unfused (Fig. 2) Experiment 2: Replicated results from Experiment 1 using 42 University students Experiment 3 (N = 80):Manipulated onscreen availability of fused data to test possible improvements in attention or in task-relevant processing • Permanently (10 sec) vs. temporarily available (2 sec in every 10 sec) • During Trial & Recall: More accurate when information temporarily available Aim: To assess the extent to which problem solving search strategies would be sensitive to changes in IAC and how this might affect planning behaviour Task: Move coloured blocks into empty spaces (one-at-a-time) in vertical or horizontal directions within a workspace window (WW) to match the configuration of a target window (TW) IAC Conditions: Same as above Fused condition takes operator out of ‘SA loop’ and causes memory decay Including a drill-down facility or presenting critical information temporarily rather than permanently encourages more interaction with the interface increasing task-relevant processing and improving SA Recommendations ‘Too much’ or ‘too little’ fusion can result in poor SA. Including a facility to drill-down into fused data or presenting fused datatemporarily rather than permanently are ways to improve SA • Main Findings: • Generally, replicated main BWT results (more blocks correctly recalled with High IAC & faster completion with Low IAC) • Imposing a higher cost of implementing actions (the Implementation Cost, IC) through having to enter a string of commands (e.g., move_up/down/left/right) = fewer remembered moves (Expt. 1) • An IAC only on TW to make problem solving easier abolished the effect of IAC on number of moves-to-completion, although led to more initial planning with High IAC and more concurrent planning with Low IAC (Expt. 2) • Further replicated effects of IAC with a more complex planning task (8-puzzle) & provided additional qualitative evidence from verbal protocols for the precedence of initial and concurrent planning with different levels of IAC (Expt. 3) • Provided initial evidence for improved long term learning of task-relevant information due to higher IACs (Expt. 4) Main Dissemination Duggan, G. B., Banbury, S., Howes, A., Patrick, J., & Waldron, S. M. (2004). Too much, too little or just right: designing data fusion for Situation Awareness. Proceedings of the Human Factors and Ergonomics Society 48th Annual Meeting, New Orleans, USA, 528-533. Santa Monica, CA: Human Factors and Ergonomics Society. Patrick, J., & James, N. (2004). A task-oriented perspective of Situation Awareness. In Banbury S. and Tremblay, S. (Eds). A Cognitive Approach to Situation Awareness: Theory, Measures and Application. (p. 61-81) Ashgate. Howes, A., Duggan, G. B., Patrick, J., Waldron, S. M., & Banbury, S. (2004). Designing data fusion for Situation Awareness. Coping with Complexity Workshop, Bath University. Waldron, S. M., Duggan, G. B., Patrick, J., Banbury, S., & Howes, A. (2005). Information fusion for Situation Awareness in the cockpit. Proceedings of the Human Factors and Ergonomics Society 49th Annual Meeting, Orlando, USA. Santa Monica, CA: Human Factors and Ergonomics Society. Waldron, S. M., Duggan, G. B., Patrick, J., Howes, A., & Banbury, S. (2005). The cost of information access: implications for retrospective memory. Speaking of Science Cardiff University Interdisciplinary Conference. Morgan, P. L., Waldron, S. M., Patrick, J., & Jones, D. M. (2005). Designing data fusion displays for situation awareness. Poster presented at the Data Information Fusion Defence Technology Centre (DIF-DTC) Annual Conference. Shrivenham, Swindon. Waldron, S. M., Duggan, G. B., Patrick, J., Banbury, S., & Howes, A. (2005). Adaptive information fusion for situation awareness in the cockpit. Human Factors and Ergonomics Society 49th Annual Meeting: Special ‘Neo-Wickenseon’ Section. Orlando, FL. Waldron, S. M., Patrick, J., Duggan, G. B., & Howes, A., (2006). Problem solving with information access costs in mind. Annual BPS Conference. Cardiff, Wales. Waldron, S. M., Patrick, J., Duggan, G. B., & Howes, A. (2006). Planning with information access costs in mind. Proceedings of the Cognitive Science Society 28th Annual Meeting, Vancouver, BC. Effects of IAC from BWT largely replicated in more complex problem solving tasks with novel evidence for different planning strategies with different levels of IAC and improved learning with high IAC Recommendations Exploit IAC in complex problem solving tasks to promote different planning strategies & use high IACs to improve better memory and learning