Quantum is set to showcase its latest storage innovations for autonomous vehicle development at the Consumer Electronics Show (CES) 2020 in Las Vegas. The company will demonstrate its R-Series removable, in-vehicle storage and workflow systems which form a new end-to-end solution that enables high-speed data capture, fast upload, automated tiering for analysis, and shared storage for mobile environments.
Quantum has teamed with Elektrobit to conduct a first-of-its-kind in-vehicle autonomous research data capture and management demonstration at CES.
The team will drive a test vehicle cross-country from San Jose to Las Vegas, collecting real-world video and raw sensor data along the way using Elektrobit’s EB Assist Test Lab combined with Quantum’s R-Series removable storage to capture data in the vehicle, and Xcellis Workflow Director appliances powered by StorNext to ingest and direct files to the Elektrobit EB Assist Test Lab cloud-based validation tool, all on site.
With this approach, engineers gain the ability to capture, ingest, and manage large amounts of data in a manner that is flexible and cost-effective for a hybrid cloud-based solution.
EB Assist Test Lab provides engineers with a tool to manage petabytes of driving-scene data generated in real and simulated test drives. The EB Assist Test Lab enables engineers to annotate data and define its level of critical importance as it’s being captured.
EB Assist ADTF (Automotive Data and Time-Triggered Framework) is a tool for development, validation, visualization and test of driver assistance and automated driving features that includes the latest technology. Users can deliver advanced driver assistance systems (ADAS) and highly automated driving (HAD) features to customers with EB Assist ADTF.
EB Assist ADTF combines a development environment with an interactive work environment. Developers can use the graphical user interface and existing modules to create new configurations without writing a single line of code. They can use drag-and-drop to define the data-flow between software components and execute this immediately to see the effects.
Faster development of driver assistance and automated driving software modules is facilitated by the libraries and toolboxes for various functionalities, which can be easily integrated into the framework. EB Assist ADTF is designed to be used in the lab as well as in test cars.
EB Assist ADTF describes a binary standard. The functional interfaces and data formats are open to developers. The framework is available for Microsoft Windows and Linux operating systems.
Using a touchscreen interface, a driver tags user-defined events, such as roadway signs, pedestrians, hazards, wildlife, or other impediments, as they’re encountered. Automated tagging is also available. These events are tagged with metadata that flags them for prioritized analysis.
Test data is captured on the ruggedized Quantum R-Series in-vehicle data storage system, along with the corresponding metadata. Once the Quantum R-Series magazine is removed from the test vehicle and placed into the StorNext solution in the test facility data center, the data is ingested. StorNext recognizes the metadata on the R-Series device and captures the data prioritization. StorNext then directs the data to the appropriate storage tier as defined by the customer.
High-priority data may be directed to an on-premise high-performance tier utilized for Hardware in the Loop (HIL) testing, while other data may be directed to a secondary tier, such as object storage, tape or S3 cloud for cloud-based analytics and long-term backup and retention.
This data workflow solution is highly efficient and cost-effective because data is identified and moved to the appropriate storage tier upon capture and ingest. This helps prevent customers from spending time and valuable resources on managing low-priority data on high-performance, higher cost tiers.
“Delivering confidence in vehicle safety and design begins with capturing real-world test data, and ADAS and autonomous vehicle development generates a staggering volume of data,” said Graham Cousens, ADAS/autonomous vehicle solutions practice leader, Quantum. “Autonomous research also has unique workflow requirements, from capturing, processing, analyzing the data, and storing and retaining it. By demonstrating this workflow at CES we aim to show how this complexity can be intelligently managed, even in the chaos of Las Vegas.”