Road Surface Matrix Barcodes for Precise Vehicle Localization
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Solution Overview
Problem
Current driving assistance systems with SLAM face challenges in achieving high-definition, semantically-defined maps for autonomous vehicles, as they require precise location identification and dynamic updates to navigate complex traffic scenarios effectively.
Innovation Solution
A visual localization support system using matrix barcodes on road surfaces that provide high-definition coordinates, including latitude, longitude, and altitude, and 3D affine transformations, allowing cameras in autonomous vehicles to accurately identify locations and navigate through precise positioning and lane detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If SLAM algorithms are used for autonomous navigation, then the system can operate without pre-mapped environments, but achieving high-definition map accuracy (centimeter-level precision) becomes extremely difficult and computationally intensive
Solution Approach 1:
The patent introduces matrix barcodes as intermediary markers placed on road surfaces at known geographic coordinates. These barcodes serve as mediators between the natural environment and the autonomous vehicle's navigation system, providing direct, high-precision location references that eliminate the need for complex SLAM-based map construction while maintaining centimeter-level accuracy.
Solution Approach 2:
The system pre-places matrix barcodes with encoded geographic coordinates (latitude, longitude, altitude) and affine transformation parameters at specific locations on road surfaces before autonomous vehicles arrive. This preliminary action creates a pre-established reference framework that vehicles can directly utilize, avoiding the need for real-time environmental mapping and complex computational processing during navigation.
2Measurement precision
If matrix barcodes are placed on road surfaces to provide high-definition coordinates, then location identification accuracy improves to within 1 meter deviation, but the complexity of deploying and maintaining the infrastructure increases
Solution Approach 1:
The patent uses matrix barcodes that can be replicated and deployed across multiple locations using standardized printing and application processes. Each barcode contains encoded geographic coordinates and affine transformation parameters, allowing for consistent, high-precision positioning references to be created and deployed across extensive road networks using relatively simple, scalable infrastructure processes.
3Measurement precision
If affine transformation parameters are encoded in barcodes to correct perspective distortion, then navigation accuracy through intersections and road paths improves, but the data processing requirements and computational load increase
Solution Approach 1:
The affine transformation parameters (scaling, rotation, translation) are pre-calculated and encoded within the matrix barcodes during the infrastructure deployment phase. When autonomous vehicles capture images of these barcodes, the pre-encoded parameters enable direct geometric correction of perspective distortion through straightforward image processing operations, avoiding the need for complex real-time calculations and reducing computational energy consumption during navigation.
Data Source
AI summary
A visual localization support system is provided. The visual localization support system includes one or more guidance indicators place on a road surface of a roadway, wherein the one or more guidance indicators each include a matrix barcode that uniquely identifies a location by latitude, longitude, and altitude, and describes an affine shape of the guidance indicator.