Description-Based Object Association for High-Definition Maps
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The manual association of objects in the real world with objects in high-definition maps is costly and inefficient, leading to low association efficiency.
Innovation Solution
An object association method that extracts first and second description information from real data and high-definition map data, respectively, determines association probabilities based on these descriptions, and uses these probabilities to automatically associate objects, thereby improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual association method is used to associate objects in real world with objects in high-definition maps, then association accuracy can be maintained, but association efficiency deteriorates and operation costs increase
Solution Approach 1:
The system automatically extracts description information from both real-world data and high-definition map data, performs matching based on extracted features, and determines associations without human intervention. The algorithm self-services the entire association process by autonomously comparing description information and calculating association probabilities, eliminating the need for manual operation while maintaining high efficiency
Solution Approach 2:
The patent replaces the mechanical manual association process with an automated information processing system. Instead of human operators manually matching objects, the system uses computational methods to extract description information, compare features, calculate association probabilities, and determine associations automatically, substituting mechanical human labor with automated computational mechanisms
2Productivity
If automated association method is implemented, then association efficiency is improved, but association accuracy may deteriorate
Solution Approach 1:
The system calculates association probabilities based on extracted description information and uses this probabilistic feedback to determine the final association. The feedback mechanism allows the system to evaluate the strength of associations and make accurate determinations automatically, ensuring that high efficiency does not compromise accuracy
Solution Approach 2:
The patent transforms the association problem into a parameter-based comparison by extracting description information and calculating association probabilities. By changing the approach from subjective manual judgment to objective parameter comparison, the system achieves both high efficiency and high accuracy in automated associations
Data Source
AI summary
The present disclosure provides an object association method and apparatus, and an electronic device, which relate to the technical field of maps. A specific implementation solution is: when performing object association, extracting first description information of each of a plurality of first objects from real data, and extracting second description information of each of a plurality of second objects from high-definition map data; and determining, according to the first description information and the second description information, association probabilities between the first objects and the second objects; then determining, according to the association probabilities between the first objects and the second objects, an association result of the first objects and the second objects, thus realizing automatic associations between objects in real world and objects in a high-definition map, and improving an association efficiency of objects.