The last blog on SDV’s (https://www.vamsitalkstech.com/5g/vertical-industry-insights-automotive-reinventing-automotive-engineering-for-software-defined-vehicles-%c2%bd/) discussed the business challenges in turning the automotive industry from a hardware-focused industry into a software-centric industry. We discussed both the problems and the benefits of the fact that current electronic architectures are decentralized, expensive, and hard to build, which makes it hard to maintain and add new features. This blog will discuss how a leading ISV, Continental Systems, overcomes these with a well-rounded architecture deployed in the cloud.
Technology Challenges in creating Software-Defined Vehicles
Software-defined vehicles,or “smart cars” or “connected cars,” are vehicles that are equipped with advanced software, sensors, and communication technologies that enable them to communicate with each other and with other business systems in their vicinity. While software-defined vehicles have the potential to transform the automotive industry, there are several technical challenges involved in churning these out at scale.
These include –
- Designing for Security: Software-defined vehicles are vulnerable to cyberattacks that could compromise the safety of their occupants. From the ground up, developers need to address this challenge, using robust security measures, such as encryption, authentication, and intrusion detection, to protect the vehicle’s communication networks and data.
- Ensure Data privacy: Software-defined vehicles generate and collect vast amounts of data, including personal and sensitive information about the vehicle’s occupants. All of this data needs to collected, stored, and used in compliance with relevant data privacy and security regulations.
- Platform Standardization: Software-defined vehicles are composed of many different systems and components, each with its own protocols and interfaces. To enable interoperability and ensure compatibility, developers need to establish common standards for software-defined vehicles.
- Safety and reliability: Software-defined vehicles rely on complex software and communication networks to operate. To ensure their safety and reliability, developers need to implement rigorous testing and validation processes and establish clear protocols for system failure and recovery.
- Cost: Software-defined vehicles require significant investment in research, development, and infrastructure. Developers need to balance the costs of developing and deploying software-defined vehicles with the potential benefits and revenue streams that they can generate.
A Platform for Software-Defined Vehicles
Now that we have set the stage, we will discuss a framework called CAEdge, which has been designed by Continental Automotive. My goal is not to promote a certain platform, but to talk about it in terms of best practices for automotive software architecture.
From [1] –
Moreover, as the convergence of vehicles and cloud computing continues, new software-defined architectures, integration, and operations competencies become necessary. Simultaneously, Digital Lifecycle Management enables the creation of new business models, go-to-market strategies, and partnerships.
However, with the distribution of massive datasets and the rise of distributed work setups, cutting-edge security technologies are imperative. Ensuring encryption during transfer/rest, complying with data residency laws, and enabling secure developer access are common security challenges. These challenges are addressed using CAEdge technology, which provides the necessary protection for data in motion and at rest and ensures appropriate access control to protect the organization’s sensitive data.
The software defined vehicle of the future will make it possible, among other things, to simply add some functions later as an update and to maintain or upgrade performance (Function as a Product). With the CAEdge framework, Continental is laying a decisive foundation for this development. In addition, a powerful cloud solution from Amazon Web Service (AWS) accelerates the development processes and meets the strictest security and compliance requirements of vehicle manufacturers.
Continental’s High-Performance Computers (HPCs) and Zone Control Units (ZCU) are the basis of the software-defined vehicle. The powerful HPCs form the computing backbone and provide the necessary computing power for the software functions in the vehicle. So vehicles can be further developed throughout their life cycle and become an integral part of their owners’ and users’ digital life. The ZCUs act as communication gateways, provide intelligent power distribution, and reliably execute vehicle functions.
Architecture Diagram showing the CAEdge Framework (credit – AWS)
Common security issues like data residency regulations, encryption during transport and storage, and secure developer access are all addressed by CAEdge technology.
The following modular building blocks form the framework:
- Scalable Compute Platform – AWS cloud-connected, high-performance embedded computer with a software stack for the automobile industry.
- Cloud – Cloud solutions for programmers and consumers.
- DevOps Workbench – Toolchain for the complete software lifecycle, including software development and maintenance.
The speed with which organizations must adapt to become software-centric creates new difficulties and opportunities, such as:
- Current electronic architectures are decentralized, costly, and difficult to create, making them challenging to maintain and extend.
- Vehicle and cloud convergence necessitates new software-defined architectures, integration, and operational capabilities.
- New business models, go-to-market strategies, and alliances are made possible through Digital Lifecycle Management.
In addition to the deployment of large datasets and distributed work arrangements, cutting-edge security measures are required.
The acronym CASE – for Connected, Autonomous, Shared and Electrified – summarizes the changing industry with new business models including vehicle features on a subscription basis, direct-to-consumer channels, and the growing need for first-party data, new service delivery mindsets, and transformed supply chains with software, sensor, satellite support and battery charging and many other ecosystems.
Conclusion
This two-part blog series covered SDVs to some degree of depth. While there are significant hurdles to overcome, the potential benefits of software-defined vehicles, such as increased safety, efficiency, and sustainability, make them an area of significant interest and investment in the automotive industry.
References
[1] Reinventing Automotive Engineering for Software-Defined Vehicles https://aws.amazon.com/blogs/industries/reinventing-automotive-engineering-for-software-defined-vehicles/
[2] Deloitte “Software-Defined Vehicles – A Forthcoming Industrial Evolution” https://www2.deloitte.com/cn/en/pages/consumer-business/articles/software-defined-cars-industrial-revolution-on-the-arrow.html