Reinventing Automotive Engineering for Software-Defined Vehicles

As software-defined vehicles (SDVs) move from a vision to reality, car manufacturers must reinvent the vehicle development process to accelerate technical development and enhance the in-vehicle driving experience.

The standard development of a new vehicle takes a hardware-driven approach. It starts with documenting all requirements, creating a concept, and sourcing the hardware components. Therefore, the development, integration, and testing of software components can only be conducted once first hardware prototypes are available. Then, validation testing begins with a test fleet on the road. This is a slow and expensive process with limited possibility for agile development and innovation.

To accelerate vehicle development, offer new functionalities at a faster pace to customers, and lower development costs, vehicle manufacturers want to reduce the dependency on vehicle-specific hardware. One way to do this is by de-coupling software and hardware development — commonly referred to as SDVs. For SDV development, car manufacturers must be able to build and test software for a vehicle that does not yet exist. This can be achieved by leveraging data and insights collected from vehicles on the road today to create a simulated cloud-based environment to improve future products and services.

In their new multi-year engagement, AWS and Stellantis will collaborate on two key initiatives to drive automotive innovation, invention, and reinvention:

• The first is a cloud-based virtual engineering workbench that will empower engineers to continuously develop, test, and deploy vehicle software to the Stellantis vehicle fleet.
• The second is a cloud-based global vehicle data mesh: a vehicle data platform, that can be extended by domain-oriented data lakes across engineering, manufacturing, supply chain, sales, and maintenance service. The data mesh is capable of processing exabytes of vehicle data and petabytes of other data to harness the wealth of data across the enterprise, break down data silos, and allows for data-driven innovation across all Stellantis departments.

Virtual Engineering Workbench

The virtual engineering workbench (Workbench) will become the backbone to help facilitate agile product development for new digital customer experiences that can be deployed readily across across geographies and brands.

The Workbench is an integrated developer environment (IDE) for SDVs that provides vehicle engineering and development workflows to manage data, develop, test, and deploy vehicle software, run simulations, and power training of machine learning and AI models using Amazon SageMaker. Engineers worldwide can have access to a broad set of secure tools and frameworks that support the end-to-end development of vehicle software. This access can be extended within the Stellantis network.

For high performance compute (HPC), the Workbench incorporates existing toolchains-as-a-service, as well as component libraries used by automotive engineers for virtualization of vehicle hardware and software components. HPC workloads are powered by Amazon Elastic Compute Cloud (Amazon EC2), the broadest and deepest compute platform, with over 475 instances and choice of the latest processor, storage, networking, and operating systems to best match the need for each workload.

The virtual engineering workbench will accelerate vehicle design, validation, and development by providing vehicle hardware and software virtualization on HPC resources. This allows for agile, model-based system engineering (MBSE) centered, feature-driven, and end-to-end vehicle hardware and software development (conformable to ASPICE, ISO26262, UNECE R155) and focused on left-hand side of V-model (integration verification and validation from day one).

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It integrates with best-in-class engineering practices and technology (MBSE, MBD, and virtual validation). The Workbench will act as a common platform to collaborate between Stellantis, suppliers, partners, and other third parties, allowing a seamless end-to-end development approach.

Cloud-Based Data Mesh

Automotive manufacturers are continuously challenged by the amount of data captured and created during the development and vehicle lifecycle, not to mention data produced by future car generations. This is accelerated by the need to design and launch incremental feature improvements.

Efforts to advance vehicle functionality have led to new approaches for storing, cataloging, and analyzing driving data captured from vehicles on the road today. Combining data from connected vehicle fleets transmitted over cellular networks with manually ingested data gathered during the development phase of new vehicles requires an advanced cloud-based data mesh architecture.

The goal of a data mesh is to create a single-point-of-truth while treating data-as-a-product and allowing a domain-oriented decentralization of data ownership according to existing organizational structures. This means each business unit retains ownership of its data, while simultaneously making it available to other business units. The Stellantis data mesh will be designed to collect and analyze vehicle and anonymized customer data and package it to create data products. Its potential future scope stretches from vehicle development to manufacturing, to vehicle sales and marketing, to after-sales services.

Data-driven organizations use information accessibility and collaboration tooling to accelerate development and encourage experimentation, all while lowering costs. Stellantis will use common standards to democratize data access, underpinned by a fully integrated global data platform.

A rich and diverse set of data — from vehicles and applications — will be available to Stellantis developers and data scientists. This will be built and organized across the full data lifecycle, starting with data collection from edge to enterprise, to storage, processing, labeling, simulation and model training, sharing, and updating. The global data mesh will support innovations for the customer experience and help unlock efficiencies across Stellantis.

The data mesh architecture will leverage Amazon S3 and will be based on a decentralized, domain-oriented data system to drive governed sharing across data lakes and data warehouses (“lake house architecture”). The data mesh is scalable and data products and services can be shared across multiple Stellantis brands, regions, and partners.

Conclusion

On the journey toward SDV, Stellantis and AWS will combine Stellantis’s automotive engineering experience with AWS’s breadth and depth of cloud services and unique culture of innovation to help create the tools for Stellantis’s next generation vehicle platforms. Through an integrated, end-to-end development environment for vehicle software, Stellantis will be able to accelerate automotive software development to deliver innovations quicker to its customers. The cloud-based data mesh allows Stellantis to overcome data silos and support data-driven decision making across the value chain.

Learn more at aws.amazon.com/automotive.