Map Data Validation via Challenge Questions
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Solution Overview
Problem
Existing map validation methods for autonomous vehicles are inadequate in ensuring the accuracy and reliability of map data, particularly in identifying subtle errors and ensuring that critical attributes are correctly set and verified, which can impact the safety of driving decisions.
Innovation Solution
A method and system that utilize challenge questions associated with image information to validate map data, where operators review and answer questions based on retrieved images, with answers used to validate attributes and potentially correct or update the map data, and compare results for accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional map validation methods are used, then the validation process is simple, but the accuracy and reliability of map data validation is insufficient
Solution Approach 1:
The validation process is segmented into multiple challenge questions, each targeting specific map attributes (e.g., traffic light detection, lane connection, stop sign identification). This divides the complex validation task into manageable, focused questions that operators answer individually, improving overall validation accuracy while maintaining operational feasibility.
Solution Approach 2:
Challenge questions serve as an intermediary mechanism between the map data and the validation operator. Instead of directly validating complex map attributes, the system uses structured questions as intermediaries that guide operators' attention to critical features, thereby improving validation reliability without overwhelming the operator with system complexity.
2Reliability
If comprehensive map attributes are validated, then the map quality improves, but the validation time and operational complexity increase
Solution Approach 1:
Different challenge questions focus on different local aspects of map data quality (traffic lights, lanes, stop signs, intersections). Each question targets specific critical attributes rather than attempting uniform validation of all map features, thereby improving overall map reliability while reducing the time required for comprehensive validation.
Solution Approach 2:
The system prepares and presents challenge questions in advance with associated image data, allowing operators to efficiently validate multiple attributes systematically. The predetermined structure of challenge questions enables operators to quickly assess critical map features without spending excessive time on each validation task.
3Adaptability or versatility
If multiple challenge questions are used to validate different attributes, then the validation coverage improves, but the interface complexity and operator workload increase
Solution Approach 1:
The challenge question interface serves multiple functions: it displays map images, presents validation questions, collects operator responses, and tracks validation progress all within a single unified interface. This multi-functional design improves validation coverage across different map attributes while maintaining ease of operation through a consistent, standardized interaction model.
Data Source
AI summary
Aspects of the disclosure relate to validating map data using challenge questions. For instance, an attributes to be validated may be identified from the map data. At least one challenge question may be selected from a plurality of predetermined challenge questions based on the attribute. An image may be retrieved based on image information associated with the at least one challenge question. The image and the at least one challenge question may be provided for display. In response to the providing, operator input identifying an answer to the at least one challenge question may be received. This answer may be then used to validate the attribute.