ARFF Vehicle Simulators provides airport firefighting crews with the opportunity to gain experience in using ARFF vehicle controls. These customizable, open-ended scenarios allow users to command and control basic vehicle operation and positioning skills comfortably.

Using the SENSE-R VR ARFF simulator, responders can build the same operational skills, plus the necessary insight and emergency-response skills needed at a fraction of the cost of live training; and without any environmental side effects. It is an economical solution for any size airport.

Aircraft Rescue Fire Fighting (ARFF)
Aircraft Rescue Fire Fighting (ARFF)


Operation Skills:

  • Position and operate vehicles
  • extinguish fires,
  • contain and control spillage
  • mitigate damage
  • mobilize resources,
  • work as a team,
  • command and control

Aircraft Rescue Fire Fighting (ARFF) Training
Aircraft Rescue Fire Fighting (ARFF) Training

Orientation Skills:

  • Drive on the Airport Operations Area (AOA) in any weather condition
  • Recognize signs and markings
  • Observe speed limits, right of way
  • Radio communications,
  • Deal with air traffic movement

Accurate simulation of fires, smoke, spills, weather, and extinguishing agents including water, foam, and dry chemical.


  • Train staff while on duty
  • Save on fuel, agent, & vehicle costs
  • Installed and portable systems (with generic or specific vehicle controls) are available and can be connected to existing networks for team training


Scenario Generator for Instructor defined scenarios and injects for many training possibilities and Observation and Scoring System for trainee record keeping.


  • No risk to lives & property
  • No live burns, chemical release, or pollution


Aircraft Rescue Fire Fighting (ARFF)
Aircraft Rescue Fire Fighting (ARFF)

The applied physics-based simulation makes the fires, smoke and hazardous materials behave as they do in real life. Plus, the crews and bystanders act realistically due to the embedded artificial intelligence software. Scenarios can hyper-realistically replicate the unpredictability of high-stress emergency situations.

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