Map Data Validation by Per-Target Sensor Collation
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Solution Overview
Problem
Existing map data delivery systems cannot perform quality assurance on a per-feature or per-lane basis, limiting the effectiveness of map data validation and updates.
Innovation Solution
A map data delivery system that collates target information from onboard sensors with map data on a per-target basis, determining quality and validity of map data for provisional and actual delivery, allowing for per-feature or per-lane validation and updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If map data quality assurance is performed on a per-feature or per-lane basis, then the effectiveness of map data validation and updates is improved, but the device complexity increases
Solution Approach 1:
The patent segments map data into discrete target objects (features, lanes, intersections) and performs quality assurance on each segment independently. The collation unit divides the map data into multiple target objects, and the quality determination unit evaluates each segment separately, enabling granular validation without requiring complete reprocessing of entire map datasets.
Solution Approach 2:
The patent implements local quality assessment by determining quality metrics for specific target objects (individual features or lanes) rather than uniformly across the entire map. This allows different quality standards and validation methods to be applied to different map segments based on their specific characteristics and importance.
2Measurement precision
If per-target collation is performed between map data and sensor data, then the measurement precision of map data quality is improved, but the loss of time increases
Solution Approach 1:
The patent segments the quality assurance process into independent target object evaluations. Instead of processing entire map datasets sequentially, the system divides map data into multiple target objects and processes them in parallel or independently, reducing overall processing time while maintaining precision for each target.
Solution Approach 2:
The patent performs preliminary collation of target information from multiple sources (map data, probe data, sensor data) before conducting detailed quality determination. This preliminary organization of data structures and pre-processing of target object information reduces the computational burden during the actual quality assessment phase.
3Reliability
If comprehensive quality determination is performed on all map data, then the reliability of map data is improved, but the productivity of map data delivery is reduced
Solution Approach 1:
The patent applies local quality determination by assessing only specific target objects that require validation rather than performing comprehensive checks on all map data. The system can selectively determine quality for individual features, lanes, or intersections based on their importance, changing frequency, or error probability, thereby maintaining reliability for critical elements while improving overall delivery productivity.
Solution Approach 2:
The patent implements partial quality determination by performing collation and quality assessment on a subset of target objects rather than exhaustive processing of all map data. This selective approach focuses computational resources on critical map elements while accepting that less critical elements may undergo lighter validation, balancing reliability and productivity.
Data Source
AI summary
A map data delivery system in which map data is delivered from a map data delivery apparatus to an onboard apparatus is provided. The map data delivery system collates target information of a target object included in the map data and target information of a target object acquired by an autonomous sensor mounted in a vehicle on a per-target basis. The map data delivery system determines quality of the map data based on the collation result regarding the target information. The map data delivery system determines validity of the map data based on the determination result regarding the quality of the map data. The map data delivery system permits validity of the map data in response to the map data being determined to be valid.