Autonomous Vehicle Data Lake on AWS

The single source of truth for storing, cataloging, and searching Autonomous Vehicle data.

Align all phases of development, from ingest through annotation, model development, simulation, testing, and validation.
Tie all engineering teams together around a flexible and scalable data flywheel that not only aligns all phases of development, but also allows these workloads to be interdependent and iterative with each stage, enriching metadata and storing it back.
Building TuSimple's Level 4 Autonomous Driving Truck Using AWS (3:21)

Benefits

De-risk cost of development

Use instant pay-as-you-go scale to give every engineer access to the same power as the largest autonomous vehicle (AV) development teams.

Scalable, flexible data pipeline

Reliably handle ingesting, transforming, labeling, and cataloging billions of miles of real and simulated drive miles. Add pipelines as needed with no performance concerns.

Increase developer efficacy

Empower developers from multiple groups to find, search, and analyze drive data.

Gain knowledge

Gain knowledge from AWS worldwide automotive Technical Field Community experts.

Autonomous Driving Data Lake

Build an MDF4/Rosbag-based data ingestion and processing pipeline for Autonomous Driving and Advanced Driver Assistance Systems (ADAS).

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AWS services in this solution

Amazon DynamoDB is a fully managed, serverless, key-value NoSQL database designed to run high-performance applications at any scale.
Amazon Managed Workflows for Apache Airflow (MWAA) is a managed orchestration service for Apache Airflow that makes it easier to set up and operate end-to-end data pipelines in the cloud at scale.
Amazon SageMaker Ground Truth is a fully managed data labeling service that makes it easy to build highly accurate training datasets for machine learning.

Customer stories

Learn how AWS customers use highly scalable storage, deep learning, and edge computing capabilities to power ADAS and Autonomous Driving development and deployment.

BMW-group

Paving the Way Toward Automated Driving with BMW Group

See how BMW Group collects 1 billion+ kilometers of anonymized perception data from its worldwide connected fleet of customer vehicles to develop safe and performant automated driving systems.

Watch the video »
Paving the way toward automated driving with BMW Group
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All Things Automotive: Data Lakes with BMW

Explore the BMW Cloud Data Hub, and how BMW and AWS have teamed up to accelerate data-driven innovation enterprise-wide.

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Momenta Accelerates Autonomous Driving Technology with AWS

Momenta quickly built a prototype with AWS IoT services for the mass production of autonomous driving solutions and verified the feasibility of the design in only two weeks.

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Resources

AV Data Lake reference architecture
Blog

Building an Autonomous Driving and ADAS Data Lake on AWS

This blog post explains how to build an Autonomous Driving Data Lake using this Reference Architecture.

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Automated scene detection pipeline
Blog

Building an Automated Scene Detection Pipeline for Autonomous Driving – ADAS Workflow

This blog describes how many OEMs face the challenge of ingesting, transforming, labeling, and cataloging massive amounts of data to develop automated driving systems.

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Autonomous driving and ADAS workloads reference architecture
Blog

Deploying Autonomous Driving and ADAS Workloads at Scale with Amazon Managed Workflows for Apache Airflow

This blog defines a workflow that processes ROS bag files on Amazon S3, and extracts individual PNGs from a video stream using AWS Fargate on Amazon Elastic Container Service (Amazon ECS).

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Automated image processing and model training
Blog

Building an Automated Image Processing and Model Training Pipeline

This blog describes how to extract images at large scale from ROS bag files and label a subset of them with Amazon SageMaker Ground Truth.

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Get started

Leading automotive and mobility companies are innovating faster by leveraging the AWS Autonomous Vehicle Data Lake solution. Contact our experts and start your journey today.
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