Multi-Trip Landmark Association for Accurate Route Map Data
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Solution Overview
Problem
Existing vehicle guidance systems face challenges in accurately determining map data, particularly at node points with signaling units, which affects the reliability and convenience of automated longitudinal guidance functions.
Innovation Solution
A device and method for determining map data using multi-trip observations of landmarks, employing SLAM techniques to align and cluster observations, and considering internal geometry and similarity measures to enhance accuracy and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sets of observations from different trips are acquired to improve map data quality, then measurement precision improves, but device complexity increases due to the need for association algorithms and data processing
Solution Approach 1:
The patent introduces an intermediary association process that uses geometric relationships and similarity measures as mediators to link observations from different trips. This intermediary layer transforms raw multi-trip observations into associated landmark data, resolving the contradiction by adding a structured processing layer that improves precision while managing complexity through algorithmic organization
Solution Approach 2:
The patent applies preliminary action by pre-processing observations to extract geometric features and establish similarity measures before final association. By performing preliminary extraction of positional and geometric characteristics, the system prepares data in advance for more efficient and accurate association, improving map data quality while structuring the complexity in manageable stages
2Reliability
If similarity measures are used to associate observations from different trips, then reliability of landmark identification improves, but computational requirements increase
Solution Approach 1:
The patent applies partial action by implementing similarity measures that evaluate only critical geometric features and selective observation pairs rather than exhaustive comparisons. This partial evaluation approach achieves sufficient reliability for landmark association while significantly reducing computational energy requirements by focusing on the most discriminating features
Solution Approach 2:
The patent changes parameters by transforming raw observation data into standardized geometric parameters and similarity metrics. This parameter transformation enables more efficient computational processing while maintaining high reliability, as the transformed parameters are optimized for comparison and association operations, reducing the energy cost of reliable landmark identification
3Manufacturing precision
If SLAM methods are employed to optimize associations, then manufacturing precision of map data improves, but device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the SLAM optimization process into distinct functional modules: observation association, geometric constraint formulation, and optimization execution. This segmentation of the complex SLAM system into manageable components improves map data accuracy through systematic processing while reducing overall device complexity by organizing functions into independent, reusable modules
Data Source
AI summary
A device for determining map data with respect to a route portion, configured to acquire a first set of first observations during a first trip along the route portion and a second set of second observations during a second trip along the route portion, determine values of a measure of similarity for different possible observation pairs each consisting of one first observation and one second observation, determine, on the basis of the values of the measure of similarity for different possible observation pairs, an overall association with one or more one-to-one associations between, in each case, one first observation from the first set and one second observation from the second set. The device is also configured to determine the map data with respect to the route portion on the basis of the overall association.