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Autonomous Mobility

Accelerate advanced driver assistance and autonomous driving feature development with purpose-built AWS and partner services and solutions

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Powering the continued advancement of autonomous mobility

Developing and deploying Advanced Driver-Assistance Systems (ADAS) features and autonomous vehicle (AV) systems requires a development platform with highly scalable compute, storage, networking, as well analytics and deep learning frameworks. An end-to-end platform includes capabilities that allow for data collection, ingestion, storage, data management and processing, labeling and anonymization, map development, model and algorithm development, simulation, verification and validation, and workspace management functions (inclusive of MLOps and DevOps). To scale and accelerate development, leading automotive and mobility customers turn to AWS to power autonomous their development platforms for our breadth and depth of managed services, purpose-built solutions, experience, and partner community to deliver the architecture and technology required to scale and accelerate new feature development.

Benefits

Scalable infrastructure

AWS solves petabyte-scale data processing, storage, and management needs by delivering thousands of cores of compute for development and validation.

Simplified data management

Deliver new features faster by increasing data management efficiency throughout the development platform tool chain.

Tool chain compatibility

AWS provides the managed infrastructure layer needed to connect datalakes and complex tool chains together.

Accelerated time to market

Building on AWS increases agility, streamlines validation, and reduces development time.

Autonomous Mobility use cases and solutions

Data ingest & pre-processing

Access petabytes of data faster using services that accelerate data ingestion, then process the data to ensure only high quality and relevant data is stored and easily searchable for edge case scenarios

Data labeling & anonymization

Accelerate labeling and annotation while reducing operational errors to achieve high-quality data sets

Data management, processing, & analytics

Deliver new features faster by increasing data management efficiency throughout the development platform tool chain

Model development & training

Develop AI algorithms and run machine learning workloads up to 5x faster, while increasing collaboration among globally distributed teams

AM Software Development

Develop and test in a common, cloud native environment with accessibility to industry standard tool chains

Simulation & Verification

Virtually test billions of miles to improve autonomous mobility feature performance, achieving KPIs in days versus months

Learn more about featured solutions

Autonomous Driving Data Framework (ADDF)

Scale and accelerate ADAS and autonomous driving development using the data processing pipelines, visualization mechanisms, analytics interfaces, and a scene search interface.

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Scene Intelligence with Rosbag on AWS

Scene Intelligence with Rosbag is an AWS Solution that walks you through the steps to extract sensor data and apply object detection using custom business logic.

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Get started with select AWS services

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Amazon Direct Connect

The AWS Direct Connect cloud service is the shortest path to your AWS resources. While in transit, your network traffic remains on the AWS global network and never touches the public internet.

Amazon Simple Storage Service (Amazon S3)

Object storage with industry-leading scalability, availability, and security for you to store and retrieve any amount of data from anywhere.

Amazon Elastic Compute Cloud (Amazon EC2)

Amazon Elastic Compute Cloud (Amazon EC2) is a web service that provides secure, resizable compute capacity in the cloud.

AWS Batch

AWS Batch enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS.

Amazon SageMaker

Amazon SageMaker helps data scientists and developers to prepare, build, train, and deploy high-quality machine learning (ML) models quickly by bringing together a broad set of capabilities purpose-built for ML.

Amazon EMR

Amazon EMR is the industry-leading cloud big data solution for petabyte-scale data processing, interactive analytics, and machine learning using open-source frameworks such as Apache Spark, Apache Hive, and Presto.

AWS CodeBuild

AWS CodeBuild is a fully managed continuous integration service that compiles source code, runs tests, and produces software packages that are ready to deploy.

AWS CodePipeline

AWS CodePipeline is a fully managed continuous delivery service that helps you automate your release pipelines for fast and reliable application and infrastructure updates.

Customer stories

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.

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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.

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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.

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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.

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See all automotive customer stories

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.

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Developing a highly automated driving platform in the cloud

Learn how BMW built its next-generation highly automated driving development platform in the cloud, leveraging vast amounts of data and AWS services to accelerate scenario labeling and scale reprocessing to deliver new capabilities, faster.

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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.

See all automotive customer stories »

DXC Technology

DXC Robotic Drive on AWS

KPIT

KPIT SIL Platform

Capgemini

Driving Automation and Systems Validation (DASV)

Lyve Mobile

Lyve Mobile Data Transfer Services

dSPACE

Simphera

Equinix

Equinix Interconnection

Ottometric

Ottometric Platform

Weights & Biases

Weights & Biases MLops Platform

TIER IV

Web.Auto

Featured Resource

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.

Download the ebook

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Resources

See all resources »

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).

Related resource

Capgemini Driving Automation System Validation

Helps OEMs rapidly adopt the underlying architecture and technologies of autonomous driving.

Related resource

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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Automotive companies of all types and sizes—from global automakers to startups—rely on AWS. Contact our experts and start your own journey to the cloud today.

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