Flight Lesson Authoring With Dual-Simulator Step Validation
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Solution Overview
Problem
High fidelity aircraft simulators are costly and difficult to manufacture, and existing training methods require them for tasks that do not necessitate high fidelity, such as pre-flight operations, which are inefficient and costly.
Innovation Solution
A system utilizing a flight simulator and a separate plane simulator, with a workflow engine to translate events and provide accurate training lessons using graphic user interfaces, allowing training on off-the-shelf flight simulators with lower fidelity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If high fidelity aircraft simulators are used for all training tasks, then training accuracy is improved, but cost and device complexity increase significantly
Solution Approach 1:
The training system is divided into two separate components: a flight simulator for visual presentation and interaction, and a plane simulator for accurate aircraft model computation. This segmentation allows each component to be optimized independently, reducing overall system complexity while maintaining training accuracy.
Solution Approach 2:
A workflow engine is introduced as an intermediary component that translates events from the flight simulator into inputs for the plane simulator and processes outputs back to the flight simulator. This mediator enables the two simulators to work together effectively, allowing lower fidelity visual simulation combined with accurate model-based computation.
2Reliability
If high fidelity aircraft simulators are used for pre-flight operations training, then training realism is improved, but cost increases significantly
Solution Approach 1:
Different levels of simulation fidelity are applied to different aspects of the training system. The flight simulator provides visual and interface realism for pre-flight operations, while the plane simulator provides accurate aircraft model computation. This local quality differentiation allows cost-effective training without sacrificing realism where it matters most.
Solution Approach 2:
The system uses a separate plane simulator model that can be independently developed and maintained, allowing the flight simulator to be updated or replaced without affecting the core aircraft model accuracy. This copying approach enables cost-effective iterations and updates to the training system.
3Measurement precision
If trainers are present to determine training completion, then assessment accuracy is improved, but operational efficiency decreases
Solution Approach 1:
The workflow engine automatically evaluates trainee performance by monitoring events from the flight simulator and comparing them against expected outcomes from the plane simulator. This automated feedback mechanism provides objective assessment without requiring constant trainer intervention, improving operational efficiency while maintaining assessment accuracy through systematic evaluation criteria.
Solution Approach 2:
The training system includes automated evaluation capabilities that allow it to assess its own performance without external intervention. The workflow engine self-evaluates whether training objectives have been met by analyzing simulator data, reducing the need for manual trainer assessment and improving operational efficiency.
Data Source
AI summary
The present disclosure provides generating, using a flight simulator, graphic user interfaces (GUIs) simulating a cockpit of an aircraft; receiving, using the flight simulator, user input that affects an operation of the aircraft; receiving events from the flight simulator that affect the operation of the aircraft; translating the events into inputs for a plane simulator comprising a model of the aircraft; receiving outputs from the plane simulator generated in response to the inputs; and determining whether, based on at least one of the events and the outputs from the plane simulator, a step in a training lesson was performed correctly.