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ame-based Experiential Learning for Road Vehicle Dynamics Education - Kevin Hulme, Senior Research Associate, University

The project’s theoretical underpinnings are based on situated learning where new educational material is presented in an authentic context, and social interaction and group collaboration are required for learning to occur. Through a learner-centered approach, students use a physics-based simulation and large-scale visualization presented in a gaming-inspired format to discover the impact that design decisions have on a dynamic system.

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ame-based Experiential Learning for Road Vehicle Dynamics Education - Kevin Hulme, Senior Research Associate, University

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  1. Game-based Experiential Learning for Road Vehicle Dynamics Education

  2. Modeling & Simulation (M&S) - History/Origins in Training Earliest Vehicle Simulation Trainer •The LINK Trainer (1929)

  3. •aka “The Blue Box” •Train pilots to fly by instruments

  4. Modeling & Simulation (M&S) - History/Origins in Training

  5. Motion-based Simulation – A Brief History

  6. 6-DOF Motion-cueing MSL’s SimRING Simulator –Leverages a 6-DOF Moog full motion simulator –Utilizes 360 degree display screen –1080p HD Image Generation

  7. –Stereo sound system, haptic controls onboard

  8. Rotation

  9. M&S Building Blocks

  10. Motion & Force Cueing

  11. M&S Building Blocks

  12. Motion & Force Cueing

  13. The MSL Driving Simulator -- Development Framework

  14. Motion rendering (O)

  15. Simulator Construction – Software Components 1. Input Device Management

  16. Simulator Construction – Software Components DirectX/DirectInput – collect command input(s) from the driver for 2. Analysis Engine downstream processing – this data

  17. Simulator Construction – Software Components serves as input to our dynamics model, 3. Output – Graphics Engine which then commands the motion platform 4. Output – Sound Management 5. Output – Motion Base API Action mapping – allows assignment of specific actions to the buttons and axes of the input devices; handles force-feedback (e.g., calculated steering wheel torque; wheel-centering)

  18. Simulator Construction – Software Components y’(t) = f(t, y(t)), where: y(to) = yo Solved (rapidly) using simple/effective 1st/2nd order numerical methods, as necessary (e.g., Euler’s Method, Runge-Kutta) yn+1 = yn + h*f(tn , yn) (for all vehicle states) Milliken & Milliken, 1995

  19. Simulator Construction – Software Components Models allow us to adjust key vehicle parameters (e.g., vehicle 1. Input Device Management center-of-gravity, cornering

  20. Simulator Construction – Software Components stiffness at each tire) to enable 2. Analysis Engine driver interactivity “on the fly” 3. Output – Graphics Engine 4. Output – Sound Management 5. Output – Motion Base API Analyze vehicle stability with different vehicle settings (e.g., oversteer vs. understeer; front-wheel vs. rear-wheel drive)

  21. Simulator Construction – Software Components

  22. Simulator Construction – Software Components

  23. Simulator Construction – Software Components Texture Mapping

  24. Simulator Construction – Software Components Driving events tied directly to vehicle dynamics model:

  25. Simulator Construction – Software Components • • • Vehicle ignition, vehicle shutdown Engine idle (~speed, Fx) Squealing tires (~tire slip angles)

  26. Simulator Construction – Software Components

  27. Education and Training Implementation of Physics-based Modeling as an active learning tool for experiential learning and engaging young- driver training and education

  28. MSL – Experiential Learning (RVD)

  29. “The Moose Test” experiment Motion Simulator game-based (off-road) experiential learning exercises: The Moose Test evasive maneuver (ISO 3888-2) of a suddenly appearing obstacle More safely performed within a simulator than in an actual field test, particularly with novice drivers Goal: correlate simulator performance – upon an actual vehicle test maneuver - with relevant self-report metrics

  30. Hulme & Estes, 2018

  31. “The Moose Test” experiment

  32. Game-based Simulation for Vulnerable Driving Populations

  33. Laboratory Assessment of Behaviors in Occupational Roles (LABOR)

  34. A greater likelihood of being unemployed within workplace settings Perform analysis to quantify

  35. LABOR

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