Inertial Measurement Unit Accuracy Evaluation Using Vanishing Line Geometry
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Solution Overview
Problem
Autonomous driving vehicles face accuracy challenges with inertial measurement units due to multipath effects and non-line-of-sight propagation errors, particularly in urban areas, which require complex and costly calibration methods.
Innovation Solution
An inertial measurement unit evaluating method and system that uses dual cameras to capture images, calculate vanishing lines, determine image parameters, and compare them with unit parameters to assess the accuracy of the inertial measurement unit, reducing computational load and cost.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional calibration methods are used to improve inertial measurement unit accuracy, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces complex mathematical filtering and calibration procedures with a geometric vision-based method. By using camera images to detect lane lines and calculate vanishing points, the system substitutes computational mechanics with optical geometry, achieving accurate IMU evaluation without complex calibration algorithms or additional hardware
Solution Approach 2:
The patent creates a virtual model of the road geometry by capturing images and extracting lane line features. This virtual representation of the road layout is then used to calculate vanishing points and compare with IMU data, eliminating the need for physical calibration equipment while maintaining measurement accuracy
2Measurement precision
If complex calibration methods are used to reduce inertial measurement unit errors, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent performs calibration data collection during normal vehicle operation rather than requiring separate calibration sessions. The system continuously captures images and IMU data during regular driving, using these pre-collected data for vanishing point calculation and comparison, thereby eliminating dedicated calibration time while maintaining accuracy
Solution Approach 2:
The patent transforms the calibration process from a discrete, time-consuming procedure into a continuous operation that occurs during normal vehicle use. By continuously capturing images and sensor data during regular driving, the system performs calibration functions without interrupting vehicle operation or requiring additional time investment
3Measurement precision
If high precision inertial measurement units are used to reduce drift error, then measurement precision is improved, but cost increases
Solution Approach 1:
The patent replaces expensive high-precision IMU hardware with a low-cost vision-based evaluation system. By using standard cameras and processing open-source algorithms, the system achieves accurate IMU performance assessment without requiring costly specialized sensors or calibration equipment
Solution Approach 2:
The patent makes the vision system multi-functional by using it for both autonomous driving navigation and IMU accuracy evaluation. The same camera and image processing pipeline serve dual purposes, eliminating the need for separate expensive calibration hardware and reducing overall system cost
Data Source
AI summary
An inertial measurement unit evaluating method is for evaluating an accuracy of an inertial measurement unit included in an autonomous driving vehicle. The inertial measurement unit evaluating method includes an image capturing step, a vanishing line calculating step, an image parameter determining step, a unit parameter obtaining step and a parameter comparing step. The left image includes a first left lane line, a first right lane line and a first vanishing point, and the right image includes a second left lane line, a second right lane line and a second vanishing point. The vanishing line calculating step includes calculating to generate a vanishing line equation of a vanishing line, which is a line connecting the first vanishing point and the second vanishing point. The parameter comparing step includes comparing the image parameter set and the unit parameter set to generate a comparison result.