Accelerate autonomous vehicle development with purpose-built AWS and partner services and solutions
Benefits
Autonomous Mobility use cases and solutions
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Data Management, Processing & Analytics
These solutions give companies a flexible and scalable data flywheel, in which categorized data continues to feed workloads that become increasingly iterative with each stage, optimizing model development, simulation, testing, and validation.
Model & Algorithm Development
Build powerful solutions to facilitate critical self-driving functions, including lane-keeping assist, adaptive cruise control, and automated emergency braking, accelerating their time to market.
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Autonomous Driving Data Lake
Build an MDF4/Rosbag-based data ingestion and processing pipeline for Autonomous Driving and Advanced Driver Assistance Systems (ADAS).
Weights and Biases for AWS
Weights & Biases is the leading developer-first MLOps platform to build better models faster. Weights & Biases lets ML teams track experiments, understand model and dataset dependencies, visualize and understand their datasets, and collaborate and share findings.
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Customer stories
Learn how leading automotive companies are transforming their businesses with AWS Autonomous Mobility solutions.
Transforming Autonomous Trucking with a Data Lake Built on Amazon S3
Learn about key insights from Torc Robotics after migrating to a modern data lake in the cloud with Amazon S3.
Mobileye: Navigating the winding road toward driverless mobility
Autonomous vehicles (AVs) are becoming a reality, as evidenced by the variety of advanced driver assistance systems (ADAS) and growing number of AV test programs on the road. Mobileye, a global leader in the development of technologies for ADAS and autonomous driving solutions, has been an integral part of this technology revolution.
Lyft Increases Simulation Capacity, Lowers Costs Using Amazon EC2 Spot Instances
Lyft increased simulation capacity and lowered costs using Amazon EC2 spot instances to improve performance and safety of its self-driving system.
Toyota Research Institute accelerates safe automated driving with deep learning at a global scale on AWS
Toyota Research Institute uses Amazon EC2 P3 instances to efficiently handle and process the huge amount of data it collects, helping accelerate development of its automated driving systems.
Momenta Accelerates Autonomous Driving Technology with AWS
Momenta uses AWS storage and IoT solutions to collect and process hundreds of petabytes of data from on-board sensors of its autonomous vehicles.
WeRide Speeds Autonomous Driving Machine Learning Model Training from Weeks to 12 Hours on AWS
WeRide sped its autonomous driving machine learning model training from weeks to 12 hours on AWS.
Building TuSimple's Level 4 Autonomous Driving Truck Using AWS
TuSimple has simulated billions of miles driving and developed its autonomous driving platform that uses sophisticated deep learning algorithms on AWS.
Innovate with key industry partners
Engage with a global community of AWS Partners who have demonstrated technical expertise and customer success in building solutions on AWS.
Resources
Check out AWS Automotive blog posts, videos, podcasts, and other resources to learn more and stay up to date on the latest developments.
Autonomous Development Ebook
Autonomous vehicles hold the promise of a safe, efficient, and accessible future that will minimize the dependency on—and eventually eliminate—the need for a human driver. Read this ebook to learn how Toyota Research, Lyft, Momenta, and TuSimple accelerate their autonomous driving system development by building on AWS.
Building an automated scene detection pipeline for Autonomous Driving – ADAS Workflow
This Field Notes blog post in 2020 explains how to build an Autonomous Driving Data Lake using this Reference Architecture.
How Autonomous Trucking Became the Unlikely Hero of Autonomous Vehicle Development
Class 8 commercial trucks, the tractor trailers you pass every day on the highway, typically log astronomical mileages on long routes with relatively predictable conditions. That’s an ideal environment for developing and proving self-driving technology.
Run any high-fidelity simulation in AWS RoboMaker with GPU and container support
To support high fidelity simulation, AWS RoboMaker now supports GPU-based simulation jobs designed for compute intensive workflows, such has high-fidelity simulation.
Deploy and Visualize ROS Bag Data on AWS using rviz and Webviz for Autonomous Driving
This blog post describes three solutions on how to deploy and visualize ROS bag data on AWS by using two popular visualization tools.
Label Videos with Amazon SageMaker Ground Truth
As models become more sophisticated, AWS customers are increasingly applying machine learning prediction to video content. Autonomous driving is perhaps the most well-known use case, as safety demands that road conditions and moving objects be correctly detected and tracked in real time.
Label 3D Point Clouds with Amazon SageMaker Ground Truth
Using the built-in graphical user interface (GUI) and its shortcuts for navigation and labeling, workers can quickly and accurately apply labels, boxes and categories to 3D objects (“car,” “pedestrian,” and so on).
Capgemini Driving Automation System Validation
Helps OEMs rapidly adopt the underlying architecture and technologies of autonomous driving.
DXC and AWS Robotic Drive Cloud
Provides the tools, services, and base backend platform on AWS to accelerate the build of autonomous driving functions and software by enriching AWS services optimized for autonomous driving-specific workloads.
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