Vehicle Constraint-Aware Partial Control for Predicted State Breaches
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Solution Overview
Problem
Drivers often unknowingly exceed a vehicle's operational or contextual constraints, leading to potential catastrophes due to lack of awareness of the vehicle's limits and environmental conditions.
Innovation Solution
A vehicle system that uses sensors to gather operational and contextual information, predicts future states, and adjusts controls to prevent breaches of operational constraints, allowing for partial control to avoid accidents while maintaining driver input as primary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system implements partial control to prevent vehicle catastrophes, then safety and reliability are improved, but device complexity increases due to multiple sensors and control mechanisms
Solution Approach 1:
The system performs preliminary prediction of future vehicle states and identifies potential constraint breaches before they occur. By predicting operational parameters and detecting envelope violations in advance, the system can prepare corrective actions proactively, preventing catastrophes before they happen rather than reacting after failure occurs.
Solution Approach 2:
The system continuously monitors current vehicle state through sensors, compares it against predicted future states and operational constraints, and provides feedback control by adjusting vehicle operations when potential violations are detected. This closed-loop feedback mechanism ensures safety while maintaining manageable complexity through intelligent control algorithms.
2Manufacturing precision
If the system monitors and corrects driver input in real-time, then operational precision and safety are improved, but information processing requirements and system complexity increase
Solution Approach 1:
The system applies partial control by only intervening when predicted operational parameters approach constraint boundaries. Rather than continuously correcting all driver inputs, the system selectively applies corrections only when necessary to prevent envelope violations, reducing unnecessary processing while maintaining precision where needed.
Solution Approach 2:
The system dynamically adjusts control parameters based on predicted vehicle states and operational constraints. By changing control parameters adaptively according to real-time conditions and predicted future states, the system achieves high precision control without requiring excessive processing complexity, as parameters are adjusted only when constraint violations are anticipated.
Data Source
AI summary
Systems and methods of a vehicle for partially controlling operation of a vehicle based on operational constraints of the vehicle and/or contextual constraints of the vehicle are disclosed. Exemplary implementations may: generate output signals conveying operational information regarding the vehicle; generate output signals conveying contextual information regarding the vehicle; determine, based on the output signals, the operational information; determine, based on the output signals, the contextual information; determine, based on the operational information and/or the contextual information, a current vehicle state of the vehicle; determine, based on the current vehicle state of the vehicle, a future vehicle state; determine, based on the operational information, predicted boundaries of the operational information; determine, based on the operational information and contextual information, trajectory threshold values of trajectory metric; and control the vehicle partially, based on the future vehicle states determined, the predicted boundaries, and the trajectory threshold values.