Digital Cockpit

Modern digital cockpit platforms became extremely complex in terms of architectures, technologies, and use cases these need to serve. OEMs  must integrate various elements, including base operating systems, virtualization and application development frameworks, automotive-specific features (functional safety, diagnostics, telematics, systems bootime) and AI-enhanced voice assistants. This growing complexity is clearly visible in studies relate to vehicle recalls - more and more recalls are caused by software issues. Additionally, we can observe delays in new vehicles releases caused by immature software platforms. 

How to address challenges emerging from growing complexity of modern digital cockpit platforms?

• Hardware consolidation and virtualization -  usage of hypervior software to host mixed-critical applications on one hardware platform
• Decouple software from hardware to enable portability and reusability accross different car lines
• Leverage virtual development workbenches to boost productivity and communication between distributed teams
• Use AI tools to streamline development process and increase software quality
• "Shift left" approach - start testing and validating software through cloud-based virtual ECUs without the need to wait for the target hardware
• Leverage CI/CD pipelines and cloud-native technologies (Docker, Kubernetes) to manage larg-scale deployments
• Ensure a proper talent pool with hands-on experience in developing digital cockpit technologies
• Implement reliable OTA mechanism for future updates and necessary bug fixes

When you enter the car you want to have all systems ready within seconds, especially for the features realetd to displays or cameras which are essential from safety perspective. The challenge OEMs are facing is related to the optimization of "cold boot KPIs" like instrument cluster tell-tales, static and dynamic splash, early audio path or RVC (rear view camera).

How to tackle this challenge:

• Focus on system bootloader optimization
• Early boot sequence tuning
• Define clear dependency definitions for host OS
• Ensure proper startup manager and system lanuch components configuration
• Displays and camera middleware optimization

Dynamic proliferation of software in vehicles presents numerous challenges, with cybersecurity concerns being one of the most crucial to address. That’s why cybersecurity shouldn’t be considered a trend - it’s rather a core priority for OEMs and service providers. This is a serious threat that might impact drivers and passengers safety. That's why cybersecurity solutions should support vehicle's whole life cycle.

How to address this challenge:

• "Security by design" and "system hardening" - making sure that the automotive system is secured starting with low-level parts of the system through proper boot and access management policies
• Implement secure Service Oriented Architecture (SOA), cryptography and TLS technologies to ensure safe and secure communication between the cockpit domain controller and other ECUs
• Develop software in accordance with ISO/SAE 21434 requirements
• Implement Cybersecurity Management System (CSMS)
• Use dedicated AI cybersecurity solutions for digital cockpits to prevent malicious attacks and prompt injections 

The increasing complexity of modern cockpit domain controllers (CDC) and infotainment platforms necessitates specific skills and expertise across a broad spectrum of technologies. Development of a trully software-defined vehicle (SDV) remains a complex challenge, and it cannot be solved in isolation by any company. That's why OEMs build strong partnerships with semiconductor companies and hyperscalers to facilitate development process and reduce time to market.

Car producers can also benefit from the support and cooperation with digital engineering software service companies like Tietoevry.  Through the flexibility and various engagement models offered by these companies, OEMs can:

• Tap into specialized technical expertise in a timely manner
• Quickly enhance their necessary competencies
• Hand over less priority activities and focus on top R&D activities
• Learn modern software development process best practices