Autonomous Vehicle Control System Adaptability
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Solution Overview
Problem
Current autonomous vehicle control systems lack the ability to effectively select and execute operational plans based on real-time situational awareness data and mission control inputs, leading to inefficiencies in navigation and control, especially in dynamic and unpredictable tactical missions.
Innovation Solution
An autonomous vehicle control system that includes an operational plan controller, a decision-making algorithm, and an execution engine, which utilize situational awareness data from on-board sensors and mission control data to select and execute operational plans, ensuring optimal behavioral characteristics and intent decisions for navigation and control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If autonomous vehicle control systems use predetermined operational plans with fixed behavioral characteristics, then the system structure remains simple and manageable, but the system cannot adapt effectively to dynamic and unpredictable tactical missions
Solution Approach 1:
The patent implements dynamics by making the operational plan selection process adaptive rather than static. The decision-making algorithm continuously evaluates current situational awareness data and mission control data to dynamically select from multiple operational plans, allowing the system to adapt its behavior characteristics in real-time based on changing mission requirements and environmental conditions.
Solution Approach 2:
The patent applies segmentation by dividing the control system into distinct functional modules: an operational plan controller that maintains multiple operational plans, a decision-making algorithm that selects plans, and an execution engine that implements selected plans. This modular architecture manages complexity by organizing the adaptive control system into separatable, manageable components with defined interfaces.
2Productivity
If the system processes real-time situational awareness data and mission control data through a decision-making algorithm, then navigation and control efficiency improves, but computational requirements and processing time increase
Solution Approach 1:
The patent applies preliminary action by pre-defining multiple operational plans with predetermined behavioral characteristics before mission execution. The decision-making algorithm only needs to select from these pre-prepared plans based on current data, rather than generating behavior sequences in real-time, significantly reducing computational requirements and decision processing time while maintaining high navigation efficiency.
3Extent of automation
If the execution engine provides control outputs to operational components based on selected operational plans, then autonomous navigation and control are achieved, but system reliability decreases without human oversight
Solution Approach 1:
The patent implements feedback by continuously monitoring situational awareness data from sensors and mission control data, using this information to inform the decision-making algorithm's selection of operational plans. This closed-loop feedback mechanism ensures the autonomous system responds appropriately to changing conditions, maintaining reliability through data-driven decision-making while achieving full automation without requiring constant human oversight.
Data Source
AI summary
One example includes an autonomous vehicle control system. The system includes an operational plan controller to maintain operational plans that each correspond to a predetermined set of behavioral characteristics of an associated autonomous vehicle based on situational awareness data provided from on-board sensors of the autonomous vehicle and mission control data provided from a user interface. The system also includes a decision-making algorithm to select one of the operational plans for operational behavior of the autonomous vehicle based on the situational awareness data and the mission control data at a given time and to provide an intent decision based on the situational awareness data and the selected one of the operational plans. The system further includes an execution engine to provide control outputs to operational components of the autonomous vehicle for navigation and control based on the selected one of the operational plans and in response to the intent decision.