Autonomous Driving Data Queries for Fault-Tolerant SQL Storage
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Solution Overview
Problem
Current data storage systems for automated driving (DSSAD) face challenges in efficiently storing and retrieving autonomous driving data, particularly due to partial hardware errors in non-volatile memories, which can lead to data loss and retrieval issues.
Innovation Solution
A device comprising a controller that receives a key and a query string from an autonomous driving controller, determines the authority level, modifies the query string based on the authority level, and executes the modified query string to record and retrieve autonomous driving data in a structured query language (SQL) database.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is stored in non-volatile memory with pre-matched storage addresses, then data storage organization is improved, but data recovery and retrieval become difficult when hardware errors occur
Solution Approach 1:
The patent creates a logical copy of the data storage structure through a database system that mirrors the physical non-volatile memory organization. When hardware errors occur, the logical database copy allows data to be retrieved and reconstructed without directly accessing the damaged physical addresses, thus maintaining both storage efficiency and recovery capability.
Solution Approach 2:
The patent introduces a database management system as an intermediary layer between the autonomous driving controller and the non-volatile memory. This intermediary handles data retrieval requests by translating logical queries into physical address access, enabling data recovery even when physical addresses are damaged by hardware errors.
2Adaptability or versatility
If autonomous driving data is stored without structured management, then storage flexibility is maintained, but data retrieval and integrity verification become inefficient
Solution Approach 1:
The patent segments autonomous driving data into distinct categories (sensor data, control data, event data) and stores them in separate database tables with specific schemas. This segmentation maintains storage flexibility for different data types while enabling efficient targeted retrieval operations, improving productivity without sacrificing adaptability.
Solution Approach 2:
The patent creates a universal database management system that handles multiple data types and retrieval scenarios through a single structured interface. This multi-functional system supports various query patterns and data access methods while maintaining consistent efficiency across different retrieval operations.
3Stability of the object's composition
If data storage addresses are predetermined in non-volatile memory, then data organization is improved, but data integrity is compromised when partial hardware errors occur
Solution Approach 1:
The patent implements error detection and correction mechanisms in advance within the database management system. Checksum validation, data redundancy, and error handling protocols are prepared beforehand to cushion against the impact of hardware errors, preserving data integrity even when physical storage addresses become corrupted.
Data Source
AI summary
Disclosed are a device for managing autonomous driving data and a method thereof. The device includes a controller that receives a key and a query string from an autonomous driving controller of a vehicle, determines an authority level corresponding to the key, modifies the query string based on the authority level, and executes the modified query string, and a database that stores the autonomous driving data according to an execution of the query string.