Vehicle Maneuver Grading Using Generated Training Parameters
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Solution Overview
Problem
Existing vehicle simulation training systems lack standardized and accurate tools for instructors to assess and improve their grading of vehicle maneuvers, leading to subjective and inconsistent evaluations.
Innovation Solution
A computer software system that generates vehicle parameters using machine learning or rule-based models to provide objective feedback, compares subjective instructor grades with objective criteria, and offers graphical displays and simulations to enhance assessment accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If instructors perform visual subjective observations and interpret log files to evaluate trainee performance, then the evaluation process is simple and quick, but the evaluation becomes subjective and inconsistent between different instructors
Solution Approach 1:
The patent introduces an intermediary system consisting of a processor and software that acts as a mediator between the subjective instructor evaluation and the objective log file data. This intermediary automatically generates vehicle parameters from simulation data and presents them to instructors, eliminating direct subjective interpretation of raw logs while maintaining instructor involvement in the evaluation process.
Solution Approach 2:
The patent replaces the mechanical process of manual log file interpretation and subjective visual observation with an automated computational system. The processor automatically generates vehicle parameters from simulation data, substituting the manual analytical process with an automated algorithmic approach that provides consistent, objective measurements while reducing instructor workload.
2Productivity
If instructors rely on their own training and experience to grade maneuvers, then the grading process is fast and requires minimal tools, but the grading consistency and standardization across different instructors deteriorates
Solution Approach 1:
The patent implements a feedback mechanism where the system automatically generates vehicle parameters from simulation data and presents them to instructors for verification and final grading. This feedback loop allows instructors to quickly review objective data rather than manually analyzing logs, maintaining grading speed while improving consistency through standardized parameter generation and presentation.
Solution Approach 2:
The patent transforms raw simulation log data into standardized vehicle parameters through automated processing. By changing the form of the data from unstructured logs to structured, standardized parameters, the system enables consistent evaluation across different instructors while maintaining efficient grading throughput.
3Measurement precision
If detailed vehicle parameters are generated and displayed to instructors for maneuver assessment, then the objectivity and accuracy of evaluation improves, but the time and computational resources required for parameter generation and display increases
Solution Approach 1:
The patent performs preliminary action by automatically generating vehicle parameters from simulation data in advance of the grading process. The system processes simulation logs and creates standardized parameter sets before presenting them to instructors, eliminating the time-consuming manual analysis step while providing comprehensive assessment data when needed.
Solution Approach 2:
The patent creates simplified copies of the complex simulation data in the form of standardized vehicle parameters. Instead of presenting instructors with raw, complex log files requiring detailed analysis, the system generates streamlined parameter representations that capture essential maneuver characteristics, reducing assessment time while maintaining accuracy.
Data Source
AI summary
There is described a method and a system for training a user to score a vehicle maneuver: vehicle parameters are generated, using one of a machine learning model and a rule-based model, based on a target grade and a vehicle maneuver, the target grade being indicative of a given performance level of a pilot performing the vehicle maneuver, the vehicle parameters representing parameters of the vehicle during the vehicle maneuver, the vehicle parameters enabling evaluating a performance of the pilot during the vehicle maneuver. The vehicle parameters are provided for display providing the vehicle parameters for display, a subjective grade indicative of an estimated performance level of the pilot during the vehicle maneuver is received, and the target grade is provided for display to the user on the display device, thereby allowing the user to compare the subjective grade to the target grade.