Panel Vector
Interactive A320 cockpit trainer with scenario-driven hotspot decision workflows.
A320 Incident Replay
A320 Incident Replay
Simulator Exercise A
Scenario 1
Technical foundation
This trainer is built by decomposing the A320 cockpit into composite scene regions, named control panels, and individual control hotspots that can be queried during a scenario run.
The FlyByWire A320 flight deck material is used here as an open simulation-oriented reference for cockpit structure, panel naming, and systems context, rather than as a direct airline SOP reproduction.
- Composite cockpit scenes provide fast spatial orientation before the learner drills into a smaller panel.
- Panel JSON files define image dimensions, panel identity, and hotspot geometry for control-level interaction.
- Scenario logic adds timing pressure, error handling, hints, and debrief review.
- Debrief mode reveals expected panel path, required controls, and missed actions after the blind run ends.
Reference sources
- FlyByWire A320 Flight Deck Overview — interactive cockpit overview with clickable panel exploration.
- FlyByWire A320neo Pilot Briefing — systems-oriented A32NX overview for simulation use.
- FlyByWire A32NX Pilot’s Corner — guide hub covering beginner and advanced A320neo material.
- FlyByWire Documentation Home — documentation portal for the open-source A32NX ecosystem.
Why this method is efficient
Faster than passive reading
Checklist-only study teaches labels, but this interface forces spatial recall, panel discrimination, and control recognition under time pressure.
Faster than video review
Video shows what someone else did; this trainer requires the learner to search, decide, commit, and recover.
Scalable deliberate practice
A structured cockpit trainer can deliver repeatable targeted practice, step-level error capture, and immediate debrief without instructor scheduling limits.
Weak-zone isolation
Because the cockpit is divided into panel regions and then control hotspots, learners can isolate weak areas quickly instead of repeating full procedures every time.
Future roadmap
- Adaptive scenario engine: difficulty changes dynamically based on hesitation, wrong-panel frequency, repeat errors, and hint usage.
- Semantic debrief intelligence: failures are clustered by cockpit region, system family, and decision pattern instead of only reporting wrong clicks.
- Voice and crew interaction: add challenge-response, callout recognition, and cross-check prompting.
- Telemetry and analytics: capture hover, click, hint, and timing data for heat maps, replay, confusion analysis, and longitudinal competency tracking.
- Immersive cockpit modes: extend toward panoramic navigation, head-tracked inspection, and spatialized abnormal-event cues.
- Procedure graph logic: replace fixed step chains with graph-based action logic containing valid, invalid, recoverable, and alternate branches.