Track Selection for Balanced Environment Reconstruction Coverage
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Solution Overview
Problem
Existing map generation systems face inefficiencies due to varying amounts of sensor data for different roads, leading to computational burdens and inaccuracies, particularly in areas with few data tracks.
Innovation Solution
A track selection algorithm that segments and clusters sensor data using grid-based segmentation and clustering, merges similar tracks, and selects a subset of tracks based on orientation and altitude, ensuring a balanced track density for accurate map generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple passes or tracks of data are captured for each section of roadway to ensure accuracy, then measurement precision is improved, but device complexity and computational overhead increase
Solution Approach 1:
The patent extracts only the necessary subset of tracks from the complete set of captured data. By identifying and selecting a minimal number of tracks that provide sufficient coverage and accuracy, the system removes redundant data processing while maintaining measurement precision for map generation.
Solution Approach 2:
The patent applies partial action by processing only a selected portion of the available track data rather than all captured tracks. The track selection algorithm determines an optimal subset that provides adequate coverage, avoiding the excessive computational burden of processing every single track while still achieving required accuracy levels.
2Measurement precision
If all captured tracks of data are processed for map generation, then measurement precision is improved, but productivity decreases due to computational inefficiencies
Solution Approach 1:
The system extracts a representative subset of tracks from the complete dataset, removing unnecessary data processing steps. This extraction maintains the essential information needed for accurate map generation while significantly reducing computational workload and improving processing productivity.
Solution Approach 2:
The track selection algorithm performs preliminary filtering and selection of tracks before the main map generation process. By pre-identifying and selecting the most valuable tracks in advance, the system prepares an optimized dataset that accelerates subsequent processing while ensuring sufficient accuracy for map creation.
3Manufacturing precision
If track data is captured uniformly across all roadways, then manufacturing precision is improved, but loss of substance increases due to excessive data in high-traffic areas
Solution Approach 1:
The patent applies local quality by adapting the track selection strategy to local conditions of each roadway section. In high-traffic areas with abundant tracks, the algorithm selects only the necessary number of tracks, while in low-traffic areas, it ensures sufficient coverage is captured. This localized approach maintains uniform data quality across all regions while reducing overall data volume.
Solution Approach 2:
The system dynamically changes the track selection parameters based on local data density. By adjusting the number and distribution of selected tracks according to the specific characteristics of each roadway section, the patent optimizes the balance between data uniformity and volume reduction, eliminating excess data in high-traffic areas while maintaining adequate coverage.
Data Source
AI summary
Approaches presented herein provide for the selection of tracks of data to be used to generate, or update, a digital representation or reconstruction of a physical environment. Tracks of data may be obtained that correspond to roads or other features of a region, but there may be more tracks of data obtained for certain features than is needed, and few tracks obtained for other features. A selection process can cluster track segments into buckets, and attempt to select tracks so that the number of tracks for each bucket is above a minimum track threshold and below a maximum track threshold. An interactive selection process can be used, where selection of a track causes that track to be selected for all associated buckets that have not yet reached the maximum track threshold. Once at least a minimum number of tracks have been selected for each bucket, the tracks can be registered and provided for generation of the digital representation.