Map Reliability Computation for Driving Assistance
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Solution Overview
Problem
Current navigation systems face challenges in maintaining consistent positioning accuracy across different regions, leading to varying reliability of driving assistance applications, as existing map data updates are costly and may not meet the specific accuracy requirements of different applications like brake control and air-conditioner control.
Innovation Solution
A driving assistance system that computes a map reliability degree based on positioning accuracy, time-based change, and information accuracy, allowing for dynamic adjustment of application execution based on the computed reliability, ensuring accurate data usage for various control functions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If map data accuracy is maintained at an identical high level in all regions, then positioning accuracy for driving assistance applications is improved, but map data maintenance costs and data storage requirements increase significantly
Solution Approach 1:
The patent applies local quality by dividing map data into different accuracy levels based on regional characteristics. Detail map data with high positioning accuracy is stored only in first regions where high-accuracy driving assistance applications are needed, while general map data with lower accuracy is used in second regions. This resolves the contradiction by providing high positioning accuracy only where necessary, reducing overall data storage requirements while maintaining application performance where required.
2Reliability
If detail map data is frequently updated to maintain reliability, then positioning accuracy is improved, but maintenance costs and update frequency requirements increase
Solution Approach 1:
The patent implements local quality in time-dependent manner by updating detail map data frequently only in first regions where high reliability is needed for driving assistance applications. In second regions, general map data is updated less frequently. This resolves the contradiction by maintaining high map data reliability where required while improving maintenance efficiency through selective updating based on regional application needs.
Solution Approach 2:
The patent applies dynamics by making the map data update frequency adaptive rather than uniform. The system dynamically adjusts update frequency based on the type of map data (detail vs. general) and the specific region (first vs. second regions). This resolves the contradiction by optimizing maintenance efficiency while ensuring reliability is maintained in regions where high-accuracy applications are deployed.
3Reliability
If uniform high accuracy map data is provided across all regions, then driving assistance application stability is improved, but data storage medium capacity requirements increase
Solution Approach 1:
The patent applies local quality by providing detail map data with high accuracy only in first regions where driving assistance applications require stable performance. In second regions, general map data with lower accuracy is sufficient. This resolves the contradiction by ensuring application stability where needed while significantly reducing the total volume of map data that must be stored across all regions.
4Productivity
If map data is updated only in specific segmental regions, then maintenance costs are reduced, but user experience deteriorates due to inconsistent accuracy across regions
Solution Approach 1:
The patent resolves this contradiction by intentionally creating different quality levels in different regions based on application requirements. Detail map data with high consistency is provided in first regions where driving assistance applications are deployed, while general map data is used in second regions. This approach maintains good user experience in regions where it matters most (where applications run) while preserving maintenance efficiency through selective updating.
Data Source
AI summary
A control circuit detects a current position of a subject vehicle on a map. Before executing a driving assistance application, the control circuit computes a map reliability degree by using a positioning accuracy coefficient, a time-based change coefficient, and an information accuracy coefficient. The positioning accuracy coefficient indicates a positioning accuracy of map data with respect to a target spot. The time-based change coefficient indicates a time-based change of the map data from the latest investigation for the target spot. The information accuracy coefficient indicates an accordance ratio of the map data relative to actual data with respect to multiple information items related to the target spot. The map data can be used for executing the driving assistance application when the product of (i) a required accuracy designated to the application and (ii) the computed map reliability degree is equal to or more than a predetermined value.