Autonomous Vehicle Control Authority Adjustment
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Solution Overview
Problem
Autonomous vehicles face challenges in dynamically adjusting their control authority in response to changing operating conditions, such as sensor data quality, operator responsiveness, and environmental factors, which can impact safety and efficiency.
Innovation Solution
A vehicle control system that adjusts the level of autonomous control authority based on real-time data from various sensors and external sources, using a controller that determines a vehicle control authority modification parameter to modify the level of autonomous control, allowing for dynamic responses to changing conditions, including alerting operators when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the autonomous vehicle operates with a fixed level of control authority, then the system is simple to manage, but it cannot adapt to changing operating conditions such as sensor data quality, operator responsiveness, and environmental factors
Solution Approach 1:
The patent implements dynamic adjustment of control authority by transitioning from a fixed control level to a variable control level that adapts in real-time. The controller continuously monitors operating conditions (sensor quality, operator responsiveness, environmental factors) and dynamically modifies the autonomous vehicle's control authority accordingly, allowing the system to be both adaptive and manageable through automated decision-making algorithms.
Solution Approach 2:
The system changes the control authority parameter based on monitored operating conditions. By adjusting the control authority parameter dynamically rather than keeping it fixed, the system achieves adaptability to varying conditions such as sensor data quality degradation, operator responsiveness variations, and environmental factors while maintaining systematic control through parameter-based regulation.
2Productivity
If the vehicle maintains high autonomous control authority, then operational efficiency is improved, but safety may be compromised when operating conditions deteriorate
Solution Approach 1:
The patent implements a feedback mechanism where the controller continuously monitors operating conditions including sensor data quality, operator responsiveness, and environmental factors. Based on this feedback, the system automatically adjusts control authority to maintain safety while preserving operational efficiency. When conditions deteriorate, the feedback loop triggers reduced autonomous control and increased operator involvement, ensuring safety without permanently sacrificing efficiency.
Solution Approach 2:
The system dynamically balances productivity and safety by adjusting control authority in real-time based on monitored conditions. High autonomous control authority is maintained during favorable conditions for operational efficiency, while automatic reduction occurs when conditions deteriorate to preserve safety, achieving both goals through dynamic adaptation rather than fixed settings.
3Reliability
If the vehicle requires constant operator monitoring and intervention, then safety is improved, but fuel consumption increases and operational efficiency decreases
Solution Approach 1:
The system optimizes the operator monitoring parameter based on operating conditions. Instead of requiring constant operator monitoring, the system dynamically adjusts the monitoring level parameter according to sensor quality, environmental factors, and route characteristics. This parameter-based approach ensures adequate safety monitoring while reducing unnecessary operator engagement that would increase fuel consumption and decrease operational efficiency.
Solution Approach 2:
The patent implements dynamic adjustment of operator involvement levels rather than constant monitoring. The system transitions between different monitoring intensities based on real-time conditions, maintaining high safety standards when needed while reducing operator engagement during favorable conditions to minimize fuel consumption and maximize operational efficiency.
4Measurement precision
If the vehicle uses multiple sensors and data sources for decision-making, then measurement precision is improved, but the complexity of processing and integrating this data increases
Solution Approach 1:
The patent implements a universal data processing approach where a single controller handles multiple sensor types and data sources. The controller is designed with multi-functional capabilities to process radar, LIDAR, camera, and other sensor data through unified algorithms, achieving high measurement precision while avoiding the complexity of separate processing systems for each sensor type.
Solution Approach 2:
The system merges multiple data processing functions into a single integrated controller. By combining sensor data acquisition, processing, integration, and decision-making functions in one unified system rather than separate modules, the patent achieves high measurement precision from multiple sensors while reducing overall system complexity through functional integration.
Data Source
AI summary
Apparatuses, methods, and systems adjust the level of control authority of one or more autonomous vehicles in order to respond to changes in one or more operating conditions associated with the vehicle, operator, environment, route, and other conditions.