Google Cloud for autonomous vehicles and ADAS

Accelerate the development and commercialization of autonomous vehicle (AV) and advanced driver assistance system (ADAS) solutions on scalable, open, and cost-efficient cloud infrastructure.

Solutions

Autonomous vehicles and ADAS solutions

Explore solutions for developing, deploying, and managing autonomous vehicle and ADAS applications at scale.

Drive infrastructure at scale for R&D

End-to-end simulation with HPC

Use Google Cloud’s high performance computing to power vehicle simulation workloads to generate, test, and validate millions of simulated miles.

Multi-cloud and hybrid software development

Create a fully managed CI/CD pipeline with open source portability on a consistent platform that works across multiple deployment environments.

Learn how Sibros makes it possible to build and launch new connected vehicle use cases from production to post-sale at scale.

Intelligent and sustainable cloud

Proactively receive automated recommendations with Active Assist to help reduce costs, increase performance, improve security, and make more sustainable decisions.

Use production-level ingestion and storage

On-road data ingestion from the edge

Create and extract petabytes of on-the-road data leveraging Pub/Sub, Dataflow, Spark, and BigQuery for high scale processing.

ETL pipelines for fleet data

Simplify the data ingest process from on-prem to the cloud and in-vehicle computation leveraging Google Cloud-managed, secure, and high-performance appliance.

See how Subaru reduces pre-processing time from days to minutes using Google Cloud and Dataflow.

Planet-scale storage

Cloud Storage has extended storage bucket locations to store data with high levels of availability and performance.

Enable AI/ML workflows for autonomous driving

Neural Architecture Search (NAS) for SiL and HiL

Vertex AI Neural Architecture Search (NAS) generates neural networks to help optimize model performance.

Read how Nuro's perception team has accelerated their AI model development with Google Cloud and Vertex AI NAS.

MLOps for deployment and operations

Empower ML and data science teams for rapid prototyping and model development using Vertex AI Notebooks and services.

Deep learning for perception/behavior AI models

See how Google Cloud can provide up to 16 A100 GPUs in a single VM, offering a total of 640 GB of GPU memory.

Take the next step

Tell us what you’re solving for. A Google Cloud expert will help you find the best solution.

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