Autonomous Vehicle Test Data Pipeline for Distributed Research Access
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Solution Overview
Problem
Autonomous vehicles generate large amounts of data during testing, making it difficult and costly to transmit and impractical to store in cloud-based storage for researcher access, especially due to the complexity of interactions in human environments and the need for expedited data availability for testing and verification of machine learning techniques.
Innovation Solution
A system and method for distributing and analyzing autonomous vehicle test data through a pipeline that uploads driving session data from a drive site to network attached storage, then to cloud-based storage, and further distributes it to research sites for processing, enabling researchers to receive and contribute processing power for tasks such as indexing and machine learning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If test data is stored in cloud-based storage for researcher access, then data availability is improved, but transmission cost and complexity increase significantly
Solution Approach 1:
The patent segments the data management system into multiple distributed storage locations including local storage at drive sites, network-attached storage, and cloud-based storage. This segmentation allows researchers to access data from multiple nearby locations rather than requiring centralized cloud access, reducing transmission complexity while maintaining data accessibility.
Solution Approach 2:
The patent introduces a spatial dimension to data storage by distributing data across multiple geographic locations (drive sites, research sites, cloud). This multi-dimensional storage architecture allows researchers to access data from the nearest available location, reducing transmission distances and complexity while maintaining global accessibility.
2Loss of information
If all test data is transmitted to cloud storage, then complete data availability is achieved, but transmission time and cost increase
Solution Approach 1:
The patent implements preliminary data processing and filtering at the drive site before transmission. Data is pre-processed, validated, and organized locally, so that only necessary and relevant data needs to be transmitted to cloud storage or distributed to research sites. This preliminary action reduces the volume of data requiring transmission while ensuring data completeness for research purposes.
3Productivity
If data is distributed to multiple research sites, then research productivity increases, but data management complexity increases
Solution Approach 1:
The patent creates a universal data distribution system that can serve multiple research sites simultaneously from a single centralized management point. The system provides multi-functional capabilities including data storage, processing, distribution, and monitoring that work across all research sites, reducing the complexity of managing multiple separate data systems while enabling parallel research productivity.
4Loss of energy
If data is stored locally at drive site only, then transmission cost is reduced, but researcher access efficiency decreases
Solution Approach 1:
The patent introduces network-attached storage and cloud-based storage as intermediary layers between local drive site storage and researcher access points. These intermediaries cache and distribute data to multiple locations, reducing the need for repeated long-distance transmissions while enabling fast local access for researchers. The intermediary system optimizes the balance between transmission energy and access time.
Data Source
AI summary
A method for autonomous vehicle test data distribution and analysis is described. The method includes uploading driving session data from a computer of a drive site to a network attached storage of the drive site. The method also includes uploading the driving session data from the network attached storage of the drive site to a cloud-based storage location. The method further includes distributing the driving session data from the cloud-based storage location and a work unit to at least one research site separate from the drive site. The method also includes processing, by the at least one research site, the driving session data according to an analysis/processing task associated with the work unit.