Vehicle Sensor Mapping for Task-Specific Coverage Gaps
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Solution Overview
Problem
Vehicle systems equipped with sensors face challenges in determining whether their sensor configurations are sufficient and optimal for various tasks, especially in unanticipated conditions or when additional tasks are assigned, leading to potential inefficiencies and safety concerns.
Innovation Solution
A software application is developed to create target and capability specification maps that indicate the required and achievable sensor parameter values for different regions around a vehicle, allowing for the identification of disparities and adjustments to ensure optimal sensor data collection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor configurations are fixed for specific tasks, then task performance is optimized, but adaptability to unanticipated conditions or additional tasks deteriorates
Solution Approach 1:
The system dynamically adjusts sensor configurations based on task requirements and environmental conditions. Sensors can be repositioned, reoriented, or have their scanning parameters modified in real-time to adapt to different tasks and unanticipated conditions, resolving the contradiction between fixed optimization and adaptability.
Solution Approach 2:
The system changes sensor operating parameters (such as scanning frequency, resolution, field of view, or sensor positions) based on the specific task and environmental conditions. This allows the same sensor to provide optimal data quality for different tasks without requiring fixed configurations, thereby achieving both precision and adaptability.
2Measurement precision
If sensors are repositioned to optimize task performance, then measurement capability is improved, but system complexity increases
Solution Approach 1:
The system employs universal sensor mounting mechanisms and control architectures that can accommodate multiple sensors and task types. The same repositioning infrastructure serves multiple purposes (different tasks, different sensors, different environmental conditions), reducing the overall complexity despite the added repositioning capability.
Solution Approach 2:
The system includes automated control that manages sensor repositioning based on task requirements and environmental feedback. The automated decision-making and control reduce the need for complex manual positioning systems, as the system self-adjusts sensor configurations without requiring complex external intervention.
3Measurement precision
If sensor configurations are customized for each task, then task-specific performance is improved, but ease of operation deteriorates
Solution Approach 1:
The system automatically determines and configures appropriate sensor settings based on the assigned task and environmental conditions. The automated configuration management eliminates the need for manual customization, maintaining ease of operation while achieving task-specific optimization through self-adjusting sensor parameters.
Solution Approach 2:
The system uses feedback from environmental sensors and task performance data to automatically adjust sensor configurations. This closed-loop control allows the system to maintain optimal task-specific performance without requiring manual intervention, thereby preserving ease of operation while achieving customization.
Data Source
AI summary
A method includes determining a target specification map that is associated with a task and that indicates, for each respective region of a plurality of regions around a vehicle equipped with a sensor, a target value of a parameter of the sensor. The method also includes determining a capability specification map that indicates, for each respective region, an attained value of the parameter that the sensor is configured to provide. The method additionally includes comparing the capability specification map to the target specification map to determine, for each respective region, a disparity between the target value and the attained value. The method further includes, based on the comparing, identifying one or more of: a first subset of the plurality of regions where the target value exceeds the attained value or a second subset of the plurality of regions where the attained value meets or exceeds the target value.