Multi-Sensor Fusion Confidence Calculation for Autonomous Vehicle Positioning
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Solution Overview
Problem
Autonomous driving systems face challenges in achieving high-precision positioning due to accumulation errors in Inertial Measurement Units (IMUs) and inaccuracies in confidence measurement values, leading to safety risks during navigation.
Innovation Solution
A method for obtaining confidence of a measurement value based on multi-sensor fusion, which involves determining initial and subsequent measurement positions, acquiring distance information using inertial and wheel speedometer data, and calculating confidence levels to enhance positioning accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If Inertial Measurement Units (IMUs) are used for positioning, then continuous high-frequency positioning results can be obtained, but accumulation error increases with long-time operation
Solution Approach 1:
The patent implements a feedback mechanism by calculating the confidence value of measurement values and using it to adjust the positioning results. The system continuously monitors the reliability of IMU data through confidence calculation based on multiple measurement values, and feeds this information back to correct positioning drift, thereby resolving the accumulation error problem while maintaining high-frequency positioning.
Solution Approach 2:
The patent performs preliminary calculation of confidence values for measurement values before they are used in positioning. By pre-assessing the reliability of IMU data through confidence calculation using historical measurement values and their variances, the system prepares correction factors in advance to counteract accumulation errors before they significantly degrade positioning accuracy.
2Measurement precision
If confidence of measurement value is inaccurate, then positioning system cannot accurately predict vehicle state, but increasing measurement value collection increases system complexity
Solution Approach 1:
The patent implements a self-service mechanism where the positioning system automatically calculates confidence values using its own collected measurement data. The system uses its internal IMU measurement values and their historical statistics to compute confidence levels without requiring external validation systems, thereby improving confidence accuracy while avoiding additional system complexity.
Solution Approach 2:
The patent changes the parameter representation by introducing a confidence value parameter that quantifies measurement reliability. Instead of increasing the number of sensors or measurement channels, the system transforms existing measurement data into a confidence parameter through statistical calculation, achieving improved confidence accuracy without increasing hardware complexity.
Data Source
AI summary
The present disclosure provides a method for obtaining confidence of a measurement value based on multi-sensor fusion and an autonomous vehicle, which includes that: a first measurement value position of a positioning component on a target vehicle is determined at a first moment, and a second measurement value position of the positioning component is determined at a second moment, where the first moment is earlier than the second moment; first distance information is acquired according to the first measurement value position and the second measurement value position; inertial measurement information and wheel speedometer information of the target vehicle from the first moment to the second moment are determined; second distance information is acquired based on the inertial measurement information and the wheel speedometer information; and confidence of a target measurement value corresponding to the second moment is acquired according to the first distance information and the second distance information.