Gabriel Font (2021) Simulation of a TaxiBot Operation for First Person Training
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The document presents a simulation project for taxibot operations designed to enhance first-person training in aerospace systems. It details the development process, objectives, technical specifications, and evaluation methods used, highlighting successful validation with user feedback. Future research directions include expanding the simulation to various platforms and enhancing training content and user roles.
Gabriel Font (2021) Simulation of a TaxiBot Operation for First Person Training
- 1. SIMULATION OF A TAXIBOT OPERATION FOR FIRST PERSON TRAINING Double Bachelor’s Degree in Aerospace Systems Engineering and Telecommunications Systems September 2021 AUTHOR: GABRIEL SEBASTIÁN FONT ROJAS DIRECTORS: JORDI PONS PRATS JAVIER MORA SERRANO 1
- 2. SIMULATION OF A TAXIBOT OPERATION FOR FIRST PERSON TRAINING GABRIEL SEBASTIÁN FONT ROJAS 2 INTRODUCTION Source: https://ensia.com/ Aircraft Emissions in Shanghai Pudong International Airport Source: https://www.researchgate.net/publication/339047513
- 3. SIMULATION OF A TAXIBOT OPERATION FOR FIRST PERSON TRAINING GABRIEL SEBASTIÁN FONT ROJAS 3 INTRODUCTION 2009 IAI and Lufthansa start development of the TaxiBot. 2014 EASA Certification for use with the Boeing- 737. 2015 The TaxiBot joins the Lufthansa fleet at Frankfurt Airport. 2019 Air India started regular use at Indhira Gandhi International. Video source: https://www.youtube.com/watch?v=MPf7fX1Rnhs
- 4. SIMULATION OF A TAXIBOT OPERATION FOR FIRST PERSON TRAINING GABRIEL SEBASTIÁN FONT ROJAS 4 OBJECTIVES Design and develop a simulator of TaxiBot operations for first person training with the aim of evaluating and improving the human factors. Is it feasible to create a simulator? What is the scope that can be reached? What are the important aspects to simulate?
- 5. SIMULATION OF A TAXIBOT OPERATION FOR FIRST PERSON TRAINING GABRIEL SEBASTIÁN FONT ROJAS 5 STATE OF THE ART Examples Tecknotrove: Tecknosim Pushback Simulator 2017 (https://www.youtube.com/watch?v=-TzDYp65zo4) KLM VR Training (https://www.youtube.com/watch?v=C6EiRQjvZjo) Microsoft Flight Simulator (https://www.youtube.com/watch?v=fLQgAN79YqE)
- 6. SIMULATION OF A TAXIBOT OPERATION FOR FIRST PERSON TRAINING GABRIEL SEBASTIÁN FONT ROJAS 6 EXPERIENCE DESIGN Experience and Difficulty What to Simulate? Challenge and Learning Content Gathering Specifications Specific Case Criteria TaxiBot Aircraft Airport Location Procedure Events 1 2 3
- 7. SIMULATION OF A TAXIBOT OPERATION FOR FIRST PERSON TRAINING GABRIEL SEBASTIÁN FONT ROJAS 7 EXPERIENCE DESIGN VEHICLE SPECIFICATIONS Taxibot Specifications: • Net weight: 27 t • Tractive power: 8 t • Driving speed (max. load): 42 km/h • 11 x 3.5 m Boeing-787 Specifications: • Takeoff weight: 180 t • Nose turning radius: 32 m
- 8. SIMULATION OF A TAXIBOT OPERATION FOR FIRST PERSON TRAINING GABRIEL SEBASTIÁN FONT ROJAS 8 EXPERIENCE DESIGN ENVIRONMENT RECREATION Manises, Valencia - 8.539.403 PAX in 2019 - Class E - Unusual taxiway arrangement
- 9. SIMULATION OF A TAXIBOT OPERATION FOR FIRST PERSON TRAINING GABRIEL SEBASTIÁN FONT ROJAS 9 EXPERIENCE DESIGN TAXI PROCEDURE “TAXI TO AND HOLD SHORT OF RWY 12 VIA GATE C N H8”
- 10. SIMULATION OF A TAXIBOT OPERATION FOR FIRST PERSON TRAINING GABRIEL SEBASTIÁN FONT ROJAS 10 EXPERIENCE DESIGN EVALUATION TOOL Solutions to Evaluate the User Performing The Experience AUTOMATIC REAL-TIME SUPERVISOR
- 11. SIMULATION OF A TAXIBOT OPERATION FOR FIRST PERSON TRAINING GABRIEL SEBASTIÁN FONT ROJAS 11 UNITY IMPLEMENTATION TOOLS SketchUp Google Earth Adobe Photoshop Unity 3D MODELING TEXTURES AND UI ENGINE
- 12. SIMULATION OF A TAXIBOT OPERATION FOR FIRST PERSON TRAINING GABRIEL SEBASTIÁN FONT ROJAS 12 UNITY IMPLEMENTATION ASSETS AVAILABLE 3D MODELS ADAPTING GEOMETRY IMPORTING INTO UNITY TEXTURES AND LIGHT
- 13. SIMULATION OF A TAXIBOT OPERATION FOR FIRST PERSON TRAINING GABRIEL SEBASTIÁN FONT ROJAS 13 UNITY IMPLEMENTATION PHYSICS SIMULATION PHYSX LIBRARY SCRIPTS GAME OBJECT
- 14. SIMULATION OF A TAXIBOT OPERATION FOR FIRST PERSON TRAINING GABRIEL SEBASTIÁN FONT ROJAS 14 UNITY IMPLEMENTATION EVENTS 1. Fire Fighting Vehicle 2. Leading Aircraft AVAILABLE 3D MODELS IMPORTING WAYPOINTS SCRIPT TRIGGER ZONES
- 15. SIMULATION OF A TAXIBOT OPERATION FOR FIRST PERSON TRAINING GABRIEL SEBASTIÁN FONT ROJAS 15 UNITY IMPLEMENTATION AUTOMATIC EVALUATION TRIGGERS ON COLLISION MESSAGES MODEL RELEVANT ZONES SCORE
- 16. SIMULATION OF A TAXIBOT OPERATION FOR FIRST PERSON TRAINING GABRIEL SEBASTIÁN FONT ROJAS 16 UNITY IMPLEMENTATION NETWORKING
- 17. SIMULATION OF A TAXIBOT OPERATION FOR FIRST PERSON TRAINING GABRIEL SEBASTIÁN FONT ROJAS 17 UNITY IMPLEMENTATION NETWORKING Code: https://github.com/brihernandez/MouseFlight
- 18. SIMULATION OF A TAXIBOT OPERATION FOR FIRST PERSON TRAINING GABRIEL SEBASTIÁN FONT ROJAS 18 RESULT • Single developer. • Approximately 400 hours. • Design requirements met and some additional implementations: Tutorial. Steering wheel and pedals. Sound.
- 19. SIMULATION OF A TAXIBOT OPERATION FOR FIRST PERSON TRAINING GABRIEL SEBASTIÁN FONT ROJAS 19 RESULT https://www.youtube.com/watch?v=qGyz6eGMNC8
- 20. SIMULATION OF A TAXIBOT OPERATION FOR FIRST PERSON TRAINING GABRIEL SEBASTIÁN FONT ROJAS 20 VALIDATION Validation Session • 16 Users • Live supervision & assistance. • Awareness: 3.125/5 average • Engagement: 93.8% Commercial Pilot • No additional help. • Well recreated vehicle dynamics. • Turning is different.
- 21. SIMULATION OF A TAXIBOT OPERATION FOR FIRST PERSON TRAINING GABRIEL SEBASTIÁN FONT ROJAS 21 CONCLUSIONS A TaxiBot simulator was created and a similar project can be replicated in less than one month. It is the first to feature it. High visual fidelity in recreated environment. State of networking in Unity. Organic approach to development is preferable.
- 22. SIMULATION OF A TAXIBOT OPERATION FOR FIRST PERSON TRAINING GABRIEL SEBASTIÁN FONT ROJAS 22 FUTURE LINES OF RESEARCH Porting the experience to different devices like VR or smartphones. More events and conditions for training content. Different user roles create new possibilities. Expand data gathering, gamification, and quantify user learning.