Lane-Level Positioning Using Map and Vision Probability Fusion
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Solution Overview
Problem
Existing lane-level positioning technologies suffer from low accuracy.
Innovation Solution
A method that combines map road information, visual perception road information, and positioning information to determine a target lane by calculating topological recursion, perception observation, and positioning probabilities, enabling more accurate lane-level positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional lane-level positioning methods are used, then the system is simple, but the positioning accuracy is low
Solution Approach 1:
The patent combines multiple data sources including map road information, visual perception road information, and positioning information into a unified lane-level positioning system. By merging these diverse data types and processing them through a consistent framework, the system achieves high positioning accuracy without requiring completely separate processing systems for each data source.
Solution Approach 2:
The positioning system is designed to handle multiple types of input data (map-based, visual perception-based, and general positioning information) through a universal processing framework. This multi-functional approach allows the same system to accommodate different data sources and processing methods, improving accuracy while maintaining system coherence.
2Measurement precision
If multiple data sources are integrated, then positioning accuracy improves, but data processing complexity increases
Solution Approach 1:
The patent segments the data processing into distinct modules: map road information processing, visual perception road information processing, and positioning information processing. Each module handles specific data types independently before integrating results, which reduces overall processing complexity while maintaining comprehensive accuracy through multi-source integration.
Solution Approach 2:
The system introduces intermediate processing layers that reconcile different data formats and perspectives. These intermediary processing steps bridge the gap between diverse data sources, transforming them into a unified representation that can be consistently processed without requiring direct complex interactions between all data sources.
Data Source
AI summary
A lane-level positioning method and apparatus, a device, a vehicle, and a medium are provided. The method includes: obtaining map road information and visual perception road information of surroundings of a vehicle based on positioning information of the vehicle; determining a plurality of candidate lanes based on the positioning information; determining a topological recursion probability of the vehicle being in each of the candidate lanes by utilizing the map road information; determining a perception observation probability of the vehicle being in each of the candidate lanes by utilizing the visual perception road information; determining a positioning probability of the vehicle being in each of the candidate lanes by utilizing the positioning information; determining a target lane the vehicle is in from the plurality of candidate lanes based on the topological recursion probability, the perception observation probability, and the positioning probability of the vehicle being in each of the candidate lanes.