Command Post of the Future Limited Objective Experiment

Command Post of the Future Limited Objective Experiment - One (LOE-1) Some Results William Wright Principal Investigator DARPA CPOF Visual Insights Inc. By Permission Ward Page CPOF Program Manager DARPA Richard Hayes President Evidence Based Research www. ebrinc. com 1

Acknowledgement Most of the presentation materials here were provided by Ward Page and Dick Hayes. 2

Overview • • • Command Post of the Future Limited Objective Experiments Scenario Space Data Collection Significant Findings Summary 3

Command Post of Today (What the services are developing) Forward TAC 4 th Infantry Division Ft. Hood, TX Main TOC Division Advanced Warfighting Experiment Planning Cell 4

Command Post of Today Current Limitations • Characteristics – – – 60+ Workstations, 100+ people People are flooded by individual data streams Disjointed data systems; fragmented pictures of the battlefield No portrayal of uncertainties, inconsistencies or unknowns Requires too many people, too much communication • Consequences – – Disjointed systems can cause negative situational awareness Increased time to comprehend significance on information Incomplete, inaccurate understanding of the battlefield Delayed decisions while waiting for more data, understanding Mismatch between available data and Commander’s cognitive model. 5

Command Post of the Future Operational Impact • Increased Operational Tempo – Faster recognition and better understanding of significant battlefield changes – Faster and more complete exploration of available courses of action – More rapid and more accurate dissemination of commands • Smaller, More Mobile Command Structures – Fewer staff members – Smaller support trail & reduced deployment requirements – More mobile, distributed command organizations • Increased Span of Control 6

Command Post of the Future • Command Post of the Future (CPOF) is a DARPA program that aims to: • Increase Speed and Quality of Command Decisions – Faster recognition and better understanding of changing battlefield situation – Faster and more complete exploration of available courses of action • Provide More Effective Dissemination of Commands – COA capture for dissemination of commander’s intent – Status and capability feedback from deployed operators • Enable Smaller, More Mobile and Agile Command Structures – More mobile, distributed command element – Smaller support tail & reduced deployment requirements The goal of CPOF is to shorten the commander’s decision cycle to stay ahead of the adversary’s ability to react. 7

“We Own The Last 18 Inches” Visualization and Human. Computer Interaction 18” From Other Programs: Analysis Tools and Planning Aids; Information Management; Networking and Comms CPOF Will Create Design Rules Enabling a New Interface Metaphor for C 2 After Next 8

Command Post of the Future Tailored Visualizations • Immediate Understanding – Match user’s cognitive model – Data => Information => Knowledge – Intuitive visual presentations • Abstract as well as geospatial • Temporal as well as static • Decision-Centered – Information tailored to decisions – Show decision-relevant details – Highlight relevant changes, anomalies, exceptions – Uncover battlespace patterns – Portray uncertainties • Tailored to User – Current echelon, task & situation – User’s functional role – User’s background & preferences 9

CPOF Experiments Users • CPOF Aces (8 -15) • Battle Lab Students (40) Asymmetric • Threat (IW or BIO) • Chem/Bio attack • Info warfare attack Guerrilla • Dispersed guerilla force • Threatened urban attack HADR • Urban disaster Peace Keeping • Stability • Imminent attack Sustained Engagement • Opportunity to attack • Multiple avenues of attack • Random forces Pedigree Completeness Accuracy Consistency Perishability Control Condition Decision Performance Situation Awareness x CPOF Technology Noise Time E Stu xper Trial de ts nts Time Conditions Known Situation Matrix Core Hypotheses Improve Decision Speed & Quality • H 1: Improve Situation Awareness • H 2: Improve COA Generation • H 3: Improve COA Selection • H 4: Improve COA Communication S M L C 1 C 2 T 1 T 2 T 3 Trial Conditions 10

Limited Objective Experiment - 1 (LOE -1) Hypothesis: • Tailored visualizations will improve Situation Awareness MOE: • Correctness of Situation Awareness comprehension • Quality of Pattern Recognition • Greater Entity Retention 11

LOE-1 Scenario Space Less Complex Force-on-Force Insurgency More Complex Situation 10 Situation 13 Situation 4 Situation 5 12

F on F Treatment B Blobs, 3 D 13

Legend Bn - enemy Co - enemy Pt - enemy F on F Treatment A Color Coded Bn - friend Co - friend Pt - friend 14

Haiti Sit 4 B - 5 Critical Events Insurgency Treatment B 15 Time-Space-Event View

Insurgent activity in Haiti by category and region Civil Preparatory Military • Significant preparatory activity in Port-au-Prince • Military activity only in the North • Dormant South Insurgency Treatment A Drill Down 16

Insurgent activity in Haiti by week and category 14 12 Number of incidents 10 8 Civil Preparatory Military 6 4 2 0 C-140 C-133 C-126 C-119 C-112 C-105 C-98 C-91 C-84 C-77 C-70 C-63 C-56 C-49 C-42 C-35 C-28 C-21 C-14 C-7 Current Week • Increase in preparatory activity (last 9 weeks) • Decrease in civil activity • Low level military activity 17

Preparatory incidents by week and type 14 Recruiting 12 Propaganda 8 Leadership 6 Arms shipment 4 2 0 Preparatory type Number of incidents 10 Logistics C-140 C-133 C-126 C-119 C-112 C-105 C-98 C-91 C-84 C-77 C-70 C-63 C-56 C-49 C-42 C-35 C-28 C-21 C-14 C-7 Current Week • Very active recruiting • Increasing propaganda and logistics • Leadership activity throughout the period 18

Significant Findings • Visualization technologies generated better Situation Awareness – CPOF strongest in complex situations – CPOF strongest in force-on-force situations – CPOF strongest in understanding adversary’s situation • Different Strengths Emerged from Alternative CPOF technologies – Treatment B strongest where force ratio is important in force-onforce scenarios – Treatment A strongest in overall sketch scores in insurgency situations – Treatment A strongest in overall Situation Awareness scores in insurgency situations 19

Significant Findings (cont. ) • Time Issues and Others – Some changes due to control scores getting worse rather than CPOF scores greatly improving – Time appeared to help in case where visualization technique introduced new concept – Longer viewing time did not always result in higher scores 20

CPOF Technologies Significantly Outperform Control in Overall Scores Unprompted Prompted 33. 86 x 25. 80 17. 77 s 22. 30 N=157 21. 41 23. 40 CPOF Technologies Control p=. 058 23. 89 N=157 25. 62 p=. 007 Interpretation • CPOF Technologies generated: – Better situation awareness (higher mean or x) – CPOF Technologies performance improves for prompted 21

CPOF Technologies Significantly Outperform Control in Complex Situations Prompted Unprompted 19. 96 x 17. 24 5. 10 s 3. 95 6. 28 N=78 18. 53 CPOF Technologies Control p=. 000 8. 85 18. 28 N=78 p=. 000 Interpretation • CPOF Technologies generated: – Better situation awareness (higher mean or x) in complex situations 22

CPOF Technologies Significantly Outperformed Control in Force-on-force Situations Unprompted Prompted 29. 69 x 18. 55 16. 73 10. 10 s 11. 87 16. 95 N=78 CPOF Technologies Control p=. 020 19. 37 N=78 21. 51 p=. 019 Interpretation • CPOF Technologies generated: – Significantly better situation awareness than Control for both prompted and unprompted in Force-on-Force situations 23

CPOF Treatments Vs. Control for Enemy Representation in Insurgency Treatment A Vs. Control Treatment B Vs. Control 35. 13 33. 13 22. 25 Treatment A/B 17. 58 18. 20 Control 17. 58 21. 55 Interpretation • Treatments A and B significantly outperformed control in representing enemy force information 24

Treatment B outperforms Treatment A in Overall Situation Awareness in Situation 13 Unprompted Prompted 29. 66 x 22. 93 12. 21 s 15. 93 15. 00 N=29 p=. 073 12. 71 Treatment A Treatment B 14. 85 N=29 12. 06 p=. 002 Interpretation • Treatment A used icon visualization scheme (color coded) that subjects stated was confusing. 25

Differences between Treatments A & B in Insurgency Situations Overall Sketch Score 72. 20 64. 87 x Prompted Situational Awareness 45. 48 30. 83 s 17. 13 16. 21 N=59 p=. 07 Treatment A Treatment B 30. 93 24. 88 N= 59 p=. 05 Interpretation • In Insurgency Situations: • Treatment A outperforms Treatment B in overall sketch score • Treatment A significantly outperforms Treatment B in prompted overall Situational Awareness 26

More Time is Not Always Better (Percent of instances where time did not help, when significant differences between times were found) 39% 23% 20% 8% Situation 10 Situation 4 Situation 13 Situation 5 Interpretation • In less complex situations, more reversals in performance between times were found (subjects performed worse when given 5 minutes when compared with 3 minutes) with force on force, situation 10, 27 containing the highest percentage of instances.

More Time Helped Only in More Complex Situations 28

Situation 4 29

Situation 5 30

Situation 10 31

Situation 13 32

Summary • CPOF technologies appear to make a difference • CPOF experimental approach captures the strengths and weaknesses • CPOF technologies appear to improve subjects’ overall Situation Awareness when compared to traditional methods • CPOF experimental approach captures strengths and weaknesses of each treatment 33