Autonomous Vehicle Control Blending Across Steering, Throttle, and Braking
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Solution Overview
Problem
Existing autonomous vehicle systems offer only binary, mutually exclusive autonomous driving modes or operator control, lacking the ability to seamlessly blend levels of control across different control inputs, which limits the flexibility and safety of vehicle operation.
Innovation Solution
The implementation of a system that receives sensor data to determine a degree of autonomous control for each control input, allowing for a range of autonomous control from full operator control to full autonomous control across multiple control inputs, such as steering, throttling, and braking, using redundant power and data fabrics and AI accelerators to ensure reliable and efficient operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If binary autonomous driving modes are used, then system complexity is reduced, but adaptability and control flexibility are limited
Solution Approach 1:
The patent segments the autonomous control system into multiple independent control inputs (steering, acceleration, braking) with individual autonomy levels for each. This allows the system to provide fine-grained control flexibility without requiring complete reconfiguration of the entire control architecture, thus improving adaptability while managing complexity through modular segmentation.
Solution Approach 2:
The system dynamically adjusts the degree of autonomous control for each control input based on real-time conditions, operator preferences, and situational context. This dynamic adjustment mechanism enables the system to adapt to varying driving scenarios without requiring a completely complex static architecture, resolving the contradiction between flexibility and complexity.
2Ease of operation
If full autonomous control is applied to all control inputs, then operator workload is reduced, but operator control and safety are diminished
Solution Approach 1:
The patent implements local quality by allowing different degrees of autonomous control for different control inputs based on specific driving conditions and operator needs. For example, autonomous control may be applied to acceleration while the operator maintains control of steering, providing tailored control distribution that reduces workload where appropriate while preserving operator control where safety requires it.
Solution Approach 2:
The system applies partial autonomous control to specific control inputs rather than implementing full autonomous control across all inputs. This partial action approach allows the system to reduce operator workload on non-critical functions while maintaining operator control over safety-critical functions, thus improving ease of operation without compromising reliability.
3Measurement precision
If partial autonomous control is implemented for each control input, then control precision and safety are improved, but device complexity increases
Solution Approach 1:
The patent divides the control system into separate control inputs (steering, acceleration, braking) with independent autonomy level settings for each. This segmentation allows the system to implement precise control adjustments for each function without requiring complex cross-functional coordination, thus improving control precision while managing system complexity through modular independence.
Data Source
AI summary
Blended operator and autonomous control in an autonomous vehicle, including: receiving sensor data from a plurality of sensors of an autonomous vehicle; determining, based on the sensor data, a degree of autonomous control for each control input of a plurality of control inputs; and applying the degree of autonomous control for each control input of the plurality of control inputs.