1 Interactive Vehicle Level Human Perfomance Modeling Presented by Mr. Tim Lee DCS Corporation 1330 Braddock Place Alexandria, VA Phone: X 203 Fax:

2 Introduction TARDEC Embedded Simulation Team and the Joint Virtual Battlespace (JVB) Program conducted a collaborative effort to develop a technique to implement interactive human performance models for the crew of simulated vehicles on a virtual battlefield, aka Vehicle Level Human Performance Model (VLHPM) Initial development and integration based on TARDEC Vetronics Technology Testbed (VTT) Vehicle model Vehicle Model Sensors Actuators Automation System Architecture Joint Virtual Battlespace Battlefield Friendlies Enemies Human Performance Model Operators MM Interfaces Decision Aides Vehicle Level Human Performance Model JVB FOM HPM ICD

3 Introduction (continued) VLHPM utilized ARL Human Research & Engineering Directorate’s Improved Performance Research Integration Tool (IMPRINT) by Micro Analysis & Design – Design event driven models (not scripted static models) – Utilize prioritized goals concept TARDEC expanded the effort to model operators of Command Vehicle (CV) and Armed Robotic Vehicle (ARV) in FCS LSI’s Unmanned Combat Demo Unmanned Combat Demo – Utilizing Crew integration & Automation Testbed (CAT) vehicle assets –Evaluate maturity of key robotics technologies, CV / ARV concept Two CV operators; Two (or more) ARV operators –Experiment with different operator to robotic asset ratios to determine optimum

4 Introduction (cont.) CAT vehicle limitations for UCD –Two man CAT crew –Experiments limited to two ARV operators; no simultaneous CV operations Augmentation with constructive operator model –Four constructive operators, Two CV operators, two ARV operators, feasible –Low cost additions and modifications of crew, crewstation model –Low cost experimentation (vs with real HW, operator) –Mutual refinement and validation with real system

5 CV/ARV VLHPM Overview CV/ARV Operator HPM CV Dpty CV Cdr ARV Operator 1 ARV Operator 2 IMPRINT 6.0 Runtime Vehicle I/F CV/ARV Vehicle Model Route/ Tactics Planner New Stuff ARV Operator 3 ARV Operator n Optional Stuff Modified from VTT Model COM WSTAWG OE JVB C3 Grid Surrogate Simulation Control ESS state/mode control, CGF control AAR, data log control CAT Vehicle Sensor simulation Sensor motion, visualization, automation (ATR simulation, auto tracking) CAT Vehicle Mobility Simulation Automotive simulation, auto-drive Navigation sim Communications Simulation JVMF message generation, reception CAT vehicle Weapon simulation Weapon motion, control, round Flyout Visualizer Crewstation Interface DIS / HLA Interface UGV Simulation UGV/ARV mobility, tele-op, RSTA, OCSW, Javelin simulations Internal OTB Embedded Simulation System Disabled when interfaced to external SAF Control Status External SAF Environment DIS / JVB / RPR Operational Commands Video (for monitoring) Execution Time Control

6 CV/ARV Vehicle Model Extensive modifications and additions to baseline model of VTT Embedded Simulation System (ESS) –Automation intensive CAT architecture –Multiple UGV simulation Stryker variant for CV –Wheeled vehicle mobility Concept 5.5 ton wheeled ARVs with configurable payload –Weapon simulation based on Cougar turret (OCSW, Javeline) –Simulation of RSTA sensor, Target tracking sensor –Semi-autonomous mobility Example screen shot of vehicles. Not from actual experiments

7 CV/ARV Human Performance Model IMPRINT Goal oriented task network paradigm –Goals can be prioritized –Execution of tasks (task networks) to achieve a goal can be interrupted by execution of tasks of a higher priority goal Behavior models designed for real-time interaction, not static analysis –Operators are never loaded more than 100% –Reactions to external stimuli represented as mutually exclusive prioritized goals –Continuous main mission tasks that monitor for external stimuli Awareness and Interaction via MMI –Assume plausible level of automation –Processing of audio visual input aggregated as a task load factor for each task –Operations that require sight are approximated with, assisted by, or replaced by automation that provide digital data (route / tactics planner, Automated Target Recognition, Automated Target Tracking).

8 CV/ARV Human Performance Model: ARV Operator Monitor ARV Monitor Internal Communications 2 View RSTA Target Goal -View Target -Add Target to Queue -Tell Cdr “Targets” 4 Engage Threat Goal -Confirm Targets -Engage Targets -Clear Targets -Tell CDR “Engagement Complete” 3 Route to Defilade Goal -Enter ARV plan -Send ARV plan ARV ATR Alarm 6 View RSTASCAN Goal -View Image - Send Resume Msg 1 Teleop ARV Goal - Teleop ARV back 20m -Update ARV Route -Send Resume Msg 7 Report In Defilade Goal -Tell CDR “In Defilade” ARV RSTA SCAN ARV Stuck Alarm “Engage” & ARV Targets>0 5 Plan to Objective Goal - Develop ARV Plan -Send ARV Plan “ Plan to Objective” “Defilade” ARV In Defilade Report ARV Operator Mission and Goal Breakdown

9 CV/ARV Human Performance Model: CV Commander Monitor External Communications Monitor Surveillance Systems Monitor Internal Communications Monitor Self Protection Systems 1 Process C2 Message Goal -Enter CV Route -Tell ARV “Plan to Obj” -Set Fire Perm.= Free -Tell DPTY “Drive Route” 5 View Threat Goal -Confirm Targets -Report Type=SPOT 4 Engage Threat Goal -Set Fire Perm.= Free -Confirm Targets -Engage Targets -Report Type=SIT 7 Send C2 Report Goal -Enter C2 Report -Send C2 Report C2 Alarm (Unit March) CV ATR Alarm & !FREE CV ATR Alarm & FREE “At Destination” Detonation & CV Targets>1 2 Seek Defilade Goal -Update CV Route -Say “Defilade” 6 Resume Mission Goal -Update CV Route -Tell ARV “Plan to Objective” -Report Type=SIT “Targets & ARV Targets>1 “Engagement Complete” 3 Unit Engage Goal Say “Engage” ARV Targets>1&Free &”In Defilade1” &”In Defilade2” & “At Destination” OR ARV Targets=1 & FREE CV Commander Mission and Goal Breakdown

10 CV/ARV Human Performance Model: CV Deputy/Driver 1 Drive Route Goal - Steer to Waypoint -Accelerate/Brake to Waypoint -Say “At Destination” Monitor Internal Communications “Drive Route” CV Driver Mission and Goal Breakdown

11 CV/ARV Human Performance Model Example Task Network: Driving Task network

12 CV/ARV Human Performance Model: Automation Both “manual” and autonomous control of mobility designed to follow a route generated by a route / tactics planner –Considers terrain elevations –Considers terrain type –Manual control model adjusts actuator values in real time to keep vehicle on route –Autonomous control model issues a “plan” that contains the route and RSTA scan commands to the vehicle model Target detection by RSTA Automatic Target Recognition Target engagement with Automatic Target Tracking

13 CV/ARV Human Performance Model: Automation Pictorial representation of example terrain type data and generated routes Elevation data is not shown Open Terrain Roads Non-traversable area Routes for two ARVs And CV

14 CV/ARV Human Performance Model: User Interface Real time display of Visual Auditory, Cognitive, Psychomotor (VACP) loading on each operator Real time indication of vehicle position navigation data All interfaces and data logging of IMPRINT 6.0

15 Experiments Unmanned Combat Demo –One CV, two ARVs –Initial integration demo of maneuvers Capstone Demo –One CV, one ARV –Limited participation due to risk mitigation Virtual Distributed Lab for Modeling & Simulation (VDLMS) First Application –One CV, one ARV –Modified vehicle model, and HPM for participation as a Forward Observer / Laser Designator of “Netfires” concept evaluation Maneuver in recon mission; Spot report or call for fire (for Precision Attack Missile) Perform laser designation –Participated in majority of recorded runs simultaneously with CAT crewstations

16 Lessons Learned Real-time interactive simulation of complex behaviors of combat vehicle operator(s) is feasible –With goal oriented task model of IMPRINT –With a high fidelity vehicle model that has a rich, portable data interface –With sensor automation such as ATR, ATT that minimizes the need to convert and process visual information Enhancements to IMPRINT can simplify dynamic HPM development, such as: –Nested IF or While constructs –Temporary variables in macros –Improved External Model Call facility –Inter-operability with cognitive models (SOAR, ACT-R) Improvement of command data protocol / interface is needed –JVB C3 grid interactions afforded limited flexibility –Direct manual command injection via a “C3 Grid surrogate” was implemented for non-JVB experiments –Additional manual input of decision thresholds for target engagement were added for First App

17 Future Plans Enhancement of C3 interactions, processing, decision making –Higher echelon platform(s) or organization –Improvement of C3 interaction protocols, data sets Run-time manual command input Simulation C2 interface: JVB, Netfires, MATREX Modeling of or integration with other automation or simulation tools –On board decision aids –Higher fidelity component or functionality models of VDLMS (other HLA federates) –Integrated Unit Simulation System (IUSS) of SBCCOM –Cognitive simulation tools (ACT-R, SOAR)

18 Future Plans Higher fidelity route / tactics planner –Higher fidelity environment data –More rigorous algorithms Controlled data collection and analysis –Manned crewstations & HPM executing same operation (achieved at First App, but not enough correlated data) –Compare HPM “predicted” performance with actual –Adjust HPM Continued support of simulation analysis objectives of FCS SDD –Enhancements based on all the above –CAT HPM developments in parallel with crewstation enhancements / modifications –Unmanned Combat Demo II