Vehicle Target Confidence Scoring via Sensor Weighting
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Solution Overview
Problem
Current perception technologies for vehicles lack robust and reliable object detection, particularly in varying light conditions and environmental impacts, as they do not adequately account for sensor intrinsic characteristics and environmental factors.
Innovation Solution
A method to assign a confidence score to detected targets based on intrinsic sensor characteristics and environmental conditions, including type, field of action, atmospheric conditions, and target properties, using weighting coefficients to update the confidence score over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple sensors are used to detect targets, then the quantity of detection information increases, but the complexity of processing and integrating this information increases
Solution Approach 1:
The patent segments the sensor system into multiple independent detection modules, each responsible for specific sensor types (camera, radar, lidar). Each module processes its sensor data independently through detection, weighting, and confidence scoring, then integrates results at a higher level. This segmentation reduces overall processing complexity while maintaining comprehensive multi-sensor detection capability.
2Productivity
If sensor data is processed without considering environmental factors, then the processing speed increases, but the reliability of target detection decreases
Solution Approach 1:
The patent performs preliminary actions by pre-defining environmental condition categories (good, moderate, poor lighting, weather conditions) and pre-establishing weighting coefficients for different sensor types under these conditions. During real-time processing, the system only needs to identify the current environmental category and apply the corresponding pre-computed weights, avoiding complex real-time environmental analysis while maintaining high detection reliability.
3Measurement precision
If confidence scores are updated continuously, then the accuracy of target recognition improves, but the computational load increases
Solution Approach 1:
The patent implements dynamic confidence scoring where the weighting coefficients are adjusted based on real-time environmental conditions and sensor performance. The system dynamically modifies the importance of different sensors and detection results according to current conditions (e.g., reducing camera reliability in poor lighting), allowing continuous accuracy improvement while adapting computational requirements to actual operational needs rather than using fixed high computational load.
Data Source
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AI summary
The invention relates to a method for determining a confidence score for a target, comprising the following steps: - a detection step in which a sensor (21, 22) detects a target to be tailed (3) and a computer (4) initializes a confidence score for said target to be tailed (3); - an acquisition step in which an active sensor (2) acquires data in order to detect targets (3,10) in the surroundings; - a weighting step in which the computer (4) assigns a weighting coefficient to the target to be tailed (3) on the basis of the detection or lack of detection by the active sensor (2) of the target to be tailed (3), weighted on the basis of features (50) of the active sensor (2) and of the surroundings (21) of the vehicle (1); - a scoring step in which the computer (4) updates the confidence score for the target to be tailed (3).