Sensor Data Sorting Verification for Autonomous Vehicle Integrity

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Solution Overview

Problem

Automated driving vehicles face challenges in processing and sorting sensor signals and signal packets in a way that ensures data integrity, accuracy, and adherence to specified parameters, which is crucial for reliable autonomous operations.

Innovation Solution

An apparatus comprising sensors and a computing system with processing circuits that generate and sort data elements based on spatial and temporal parameters, verify the sorting process to ensure data integrity, and update a particle filter for autonomous vehicle operations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If data elements are sorted according to specified parameters, then data organization and processing efficiency are improved, but data integrity may be compromised due to potential errors in sorting operations

Engineering Contradiction:

Improveprocessing efficiencyVSAvoiddata integrity

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system performs preliminary actions by generating invariant parameters (such as hash values, sums, or counts) of the original data elements before sorting operations. These invariant parameters serve as reference values that enable subsequent verification of sorting correctness, ensuring data integrity is maintained throughout the processing pipeline.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements feedback mechanisms by comparing invariant parameters calculated before sorting with those calculated after sorting. This feedback loop verifies whether the sorting operation preserved data integrity, allowing the system to detect and correct potential sorting errors automatically.

Inventive Principle:

Principle #23Feedback

2Reliability

If verification operations are performed on sorted data elements, then data integrity is ensured, but processing time and computational resources increase

Engineering Contradiction:

Improvedata integrityVSAvoidprocessing time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system transforms data elements into invariant parameters (such as hash values, sums, or counts) that capture essential properties of the data set. These invariant parameters serve as compact representations that enable efficient verification without requiring element-by-element comparison, thus reducing processing time while maintaining data integrity checks.

Inventive Principle:

Principle #35Parameter changes

3Measurement precision

If invariant parameters are used to verify sorting correctness, then verification accuracy is improved, but computational complexity increases

Engineering Contradiction:

Improveverification accuracyVSAvoidcomputational complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system extracts essential properties of data elements by computing invariant parameters (such as hash values, sums, or counts) that capture the core characteristics needed for verification. This extraction process simplifies the verification task by focusing on key properties rather than analyzing entire data sets, thereby improving verification accuracy without excessive computational overhead.

Inventive Principle:

Principle #2Taking out (Extraction)

Data Source

PatentUS20240192919A1Systems, devices and/or processes for verification of data sorting operations

Publication Date: 2024.06.13 MERCEDES BENZ GROUP AG

AI summary

Subject matter disclosed herein may relate to systems, devices, and/or processes for verification of data sorting operations, such as for those that occur in automated driving vehicles.