Map Update Reliability via Dynamic Data Request
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Solution Overview
Problem
Existing map data update systems for autonomous driving face challenges in reliably detecting changes in map features, leading to potential missed updates or incorrect reflections of changes, especially when the reliability of changes is medium.
Innovation Solution
An information processing device and measurement device system that calculates the reliability of feature changes based on difference information from moving bodies, requesting and analyzing measurement data to accurately determine and update map features, while minimizing unnecessary data exchange.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system requests measurement data from all moving bodies whenever a change is detected, then the reliability of map updates is improved, but the amount of unnecessary data exchange increases
Solution Approach 1:
The system changes the parameter of data request strategy based on the reliability degree of detected changes. When reliability is high, the system processes updates directly. When reliability is medium, the system requests additional measurement data from other moving bodies to verify the change. This dynamic parameter adjustment resolves the contradiction by adapting data exchange volume to the actual reliability needs of each situation.
Solution Approach 2:
The system applies different quality levels of verification to different change detections based on their reliability degrees. High reliability changes receive standard processing, while medium reliability changes receive enhanced verification through additional data requests. This local quality differentiation ensures reliable updates are confirmed without unnecessarily verifying high-confidence changes, reducing overall data exchange volume.
2Measurement precision
If the system requests measurement data from other moving bodies for medium reliability changes, then the accuracy of change detection is improved, but the system complexity increases
Solution Approach 1:
The system uses other moving bodies as intermediaries to verify medium reliability changes. Instead of implementing a complex internal verification mechanism, the system leverages the measurement data from independent third-party moving bodies to confirm or refute detected changes. This intermediary approach improves measurement precision while avoiding the need for complex self-verification systems.
Solution Approach 2:
The system implements a feedback mechanism where measurement data from other moving bodies is used to verify and confirm changes. The feedback loop allows the system to cross-validate detected changes against independent observations, improving detection accuracy without requiring complex internal verification logic. The feedback from multiple sources provides robust verification while maintaining system simplicity.
Data Source
AI summary
A server device stores on a storage unit an advanced map database which includes feature information associated with a feature. The server device receives, from vehicle mounted devices equipped with external sensors which measure features, difference information indicative of a difference between feature information and the actual feature corresponding to the feature information. In accordance with the degree of reliability which is calculated based on a plurality of the difference information, the server device sends to the vehicle mounted device a raw data request signal for requesting the transmission of raw data which is measurement data of the actual feature.