Adaptive Coordinate Encoding for Lower In-Vehicle Data Volume
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Solution Overview
Problem
Existing methods for minimizing data transmission in in-vehicle networks are inefficient, leading to increased communication load and storage costs due to fixed file formats and lack of adaptive optimization.
Innovation Solution
A minimization method that optimizes data storage by determining whether data is stored as an absolute or relative value based on its change from the previous coordinate, using a controller to identify the optimal relative value length for each coordinate, allowing for flexible storage formats that reduce file size without compromising data integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fixed file formats are used for data storage, then data integrity is maintained, but communication load and storage costs increase
Solution Approach 1:
The patent applies dynamics by making the file format adaptive rather than fixed. The system dynamically determines whether to store data as absolute values or relative values based on the degree of change from previous coordinates, allowing the storage format to flexibly adapt to different data characteristics and minimize communication volume while maintaining data integrity
Solution Approach 2:
The patent changes the parameter of data representation from fixed to variable. By introducing a change determination mechanism that compares current coordinate values with previous ones, the system transforms the storage parameter (absolute vs. relative values) based on detected changes, thereby reducing overall data volume without sacrificing reliability
2Quantity of substance
If adaptive optimization is implemented, then file size is reduced, but processing complexity increases
Solution Approach 1:
The patent segments the data processing into distinct stages: change detection, threshold comparison, and conditional storage. By dividing the optimization process into these manageable segments, the system achieves adaptive file size reduction while keeping each processing step simple and computationally efficient
Solution Approach 2:
The system performs self-service optimization by automatically detecting data changes and determining the appropriate storage format without requiring external intervention. The controller autonomously compares coordinates, determines changes, and selects between absolute and relative value storage, reducing file size through self-directed processing
3Quantity of substance
If relative values are used for storage, then communication load is reduced, but data interpretation complexity increases
Solution Approach 1:
The patent incorporates feedback mechanisms where the system tracks which coordinates have changed and uses this information to determine storage format. The change detection feedback loop ensures that relative values are only used when appropriate, and the system maintains awareness of the coordinate history needed for accurate data interpretation
Solution Approach 2:
The patent changes the interpretation parameter dynamically based on storage format. When relative values are stored, the system adjusts its interpretation process to account for the relative nature of the data, using the stored change information to correctly reconstruct absolute values when needed, thereby managing interpretation complexity
Data Source
AI summary
A minimization method for minimizing the size of a file is provided, the minimization method including preparing an absolute value length that is equal to or larger than the largest data length among the data lengths of the data of a plurally of coordinates, and a plurality of relative value lengths equal to or less than the absolute value length, and identifying a relative value length causing minimization of the size among a plurality of relative value lengths.