Vehicle Driving Data Filtering for Cross-Border Storage Compliance
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Solution Overview
Problem
Existing vehicle control systems face challenges in managing and storing driving data efficiently across different countries with varying storage regulations, requiring cumbersome processes to delete or modify data when crossing borders.
Innovation Solution
A vehicle control device and method that adaptively delete or filter driving data based on storage expiration dates and location, using reference data to manage data storage and ensure compliance with regional regulations, including encryption and directory organization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If driving data is stored continuously to ensure data availability for autonomous driving analysis, then data completeness is improved, but storage space is consumed and data management complexity increases
Solution Approach 1:
The system performs preliminary classification of driving data into multiple categories (sensor data, control data, event data, map data) before storage, and pre-allocates storage spaces for different data types. This preliminary organization enables efficient space management while ensuring all necessary data is captured for autonomous driving analysis.
Solution Approach 2:
The storage system is segmented into multiple independent storage spaces, each dedicated to specific data categories. This segmentation allows the system to manage storage capacity for each data type separately, preventing any single category from consuming all available space while ensuring data completeness within each category.
2Reliability
If all driving data is retained without filtering to maintain data integrity for regulatory compliance, then data integrity is improved, but data processing time increases
Solution Approach 1:
The system performs preliminary filtering and classification of driving data at the time of acquisition, organizing data into categorized storage spaces based on type, time, and relevance. This preliminary action ensures data integrity is maintained through systematic organization while reducing processing time during retrieval and analysis operations.
3Adaptability or versatility
If driving data is organized by multiple classification criteria to meet diverse regulatory requirements across different countries, then regulatory compliance is improved, but system complexity increases
Solution Approach 1:
The storage system is divided into multiple independent storage spaces, each dedicated to specific data categories (sensor data, control data, event data, map data). This segmentation allows the system to independently manage and organize data according to different regulatory requirements without creating complex cross-referential structures, thereby maintaining regulatory compliance while controlling system complexity.
Solution Approach 2:
The system adds a time-based dimension to data organization by storing data in chronological order within each category. This temporal organization provides an additional layer of structure that helps meet regulatory requirements for data retention periods and historical analysis without requiring complex multi-dimensional classification systems.
4Adaptability or versatility
If driving data is deleted based on storage expiration dates to comply with regional regulations when crossing borders, then regulatory compliance is improved, but data availability decreases
Solution Approach 1:
The system segments data into multiple categories with different retention policies. When crossing borders or encountering regulatory changes, the system can selectively manage deletion across different data categories based on their specific expiration dates and regulatory requirements, thereby maintaining compliance while preserving data availability for categories that remain valid.
Solution Approach 2:
The system applies partial deletion actions rather than complete data removal. When regulatory compliance requires data deletion, the system selectively deletes only the portions of data that exceed expiration dates or violate regional regulations, while retaining other data that remains compliant and valuable for autonomous driving analysis.
Data Source
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AI summary
A vehicle control device may delete at least a portion of driving data stored in the memory using the reference data when a trigger signal is identified, acquire real-time driving data of a host vehicle using the sensor device, identify a characteristic of the real-time driving data using the reference data, filter the real-time driving data based on the identified characteristic, and store the filtered real-time driving data in a directory included in the memory, the directory corresponding to the characteristic.