Vehicle Impact Reaction Control With ML Trajectory Prediction

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Solution Overview

Problem

Existing automated systems for vehicle control, such as aircraft, face challenges in providing reliable and efficient impact avoidance maneuvers, particularly in situations where traditional numerical integration methods are slow and resource-intensive, and lack adaptability to varying operational conditions.

Innovation Solution

An apparatus management system with an impact reaction system that includes an intervention control unit and an operator notification unit, utilizing machine learning models to assess commands for controlling vehicle functions and predict optimal maneuvers to avoid impacts, such as missiles, by simulating behavior and selecting appropriate control models based on current conditions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional numerical integration methods are used for calculating flight paths and predicting missile trajectories, then measurement precision is improved, but productivity deteriorates due to low calculation speed and high resource consumption

Engineering Contradiction:
Improvetrajectory prediction accuracyVSAvoidcalculation speed
Core Design Contradiction:
Measurement precisionVSProductivity

Solution Approach 1:

The patent replaces traditional numerical integration methods (mechanical calculation systems) with deep learning-based neural networks. The system uses offline training with pre-calculated trajectory data to create a trained neural network that performs online prediction, substituting iterative numerical computations with a trained model that provides both high accuracy and real-time performance.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent implements offline training phase where the neural network is pre-trained using pre-calculated missile trajectory data before actual operation. This preliminary action allows the system to store learned patterns in the neural network weights, enabling fast online predictions without performing heavy numerical integration during critical real-time operations.

Inventive Principle:
Principle #10Preliminary action

2Reliability

If automated impact avoidance systems are implemented, then reliability is improved, but device complexity increases due to multiple control models and notification systems

Engineering Contradiction:
Improveimpact avoidance reliabilityVSAvoidsystem structure complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent divides the automated system into distinct functional modules: impact detection unit, control model selection unit, multiple control models (first and second control models), and operator notification unit. Each module performs a specific function, making the complex system more manageable and maintainable while ensuring reliable operation through specialized components.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent selects between different control models based on changing operational parameters and conditions. The control model selection unit determines which control model to activate by evaluating current system state parameters, allowing the system to adapt to varying conditions and maintain reliability across different operational scenarios.

Inventive Principle:
Principle #35Parameter changes

3Adaptability or versatility

If multiple control models are used for different operational conditions, then adaptability is improved, but device complexity increases

Engineering Contradiction:
Improveoperational condition adaptabilityVSAvoidcontrol model management complexity
Core Design Contradiction:
Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent creates a universal control model selection mechanism that manages multiple specialized control models. The control model selection unit serves as a universal interface that evaluates current conditions and routes to the appropriate control model, allowing the system to handle diverse operational conditions through a single management architecture rather than requiring separate dedicated systems for each condition.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Data Source

PatentEP4492183A1Apparatus management system for controlling at least one function of an apparatus
Publication Date: 2025.01.15 AIRBUS DEFENCE & SPACE GMBH
  • EP4492183A1 patent drawingFigure 1
  • EP4492183A1 patent drawingFigure 2~3
  • EP4492183A1 patent drawingFigure 4~5

AI summary

An apparatus management system (10), in particular a vehicle management system, for controlling at least one function of an apparatus (1), such as a vehicle, operated by an operator (2) and exposed to a potential impact (3) approaching the apparatus (1), as well as a corresponding apparatus (1) and a system training device (200) are provided, the apparatus management system (10) comprising: an impact reaction system (11), configured for generating a command for controlling the at least one function of the apparatus (1); wherein the impact reaction system (11) comprises: an intervention control unit (100); and an operator notification unit (55); wherein the intervention control unit (100) comprises at least one control model configured for assessing at least one command for controlling the at least one function of the apparatus (1) to perform an intervention in order to avoid the impact (3); wherein the operator notification unit (55) is configured to issue at least one notification to the operator (2) regarding the at least one command; and wherein the intervention control unit (100) is configured to output the at least one command for controlling the at least one function of the apparatus (1) subsequent to issuance of the notification.