BriefCASE: The road ahead for software-defined vehicles

Software-defined vehicles (SDVs) use software to control operations, add new features and integrate innovative functionalities. While this software-centric approach enhances flexibility and accelerates innovation, it also introduces challenges such as cybersecurity risks, complex software management and hardware obsolescence.

Throughout this year, and on an ongoing basis 4, S&P Global Mobility engaged with key players in the SDV landscape, including Red Hat, Elektrobit, Valeo China, KPIT Technologies and Iflytek. Their insights revealed a dynamic market poised for transformative innovations, positioning SDVs as a cornerstone of future automotive technology.

"The arrival of SDVs is happening both very slowly and all at once," observed Francis Chow, Red Hat's vice president and general manager of in-vehicle operating system and edge. "Consumers … will expect to see these features in their next vehicle purchase." This shift compels a reevaluation of traditional design and development paradigms. Moritz Neukirchner, Elektrobit's senior director of strategic product management for SDV, emphasized that "it's all about software innovations and accelerating time to market." Managing software from diverse sources while ensuring cybersecurity compliance is critical. "Setting up strong security measures and following regulations are crucial for SDVs to reach their full potential," Chow said.

The allure of SDVs lies in their ability to offer advanced functionalities. Features such as AI-driven object detection, enhanced infotainment systems and predictive maintenance are gaining traction. "The promise of a vehicle that can improve over time … is one of the most appealing elements of the SDV," Neukirchner stated.

Traditionally, vehicle software development followed a linear model confined to initial production phases. The SDV model promotes continuous integration and iterative updates, compelling original equipment manufacturers to create robust software development environments capable of managing frequent updates while maintaining safety and performance standards.

Open-source principles are pivotal in this transition. By leveraging platforms such as Linux, automakers can foster collaboration and expedite development. "Open source provides a means to an end for the automotive industry," Chow said, highlighting how this collaborative approach reduces costs and accelerates the delivery of innovative applications amid rising pressures to deliver new features swiftly.

An architectural shift from domain-based to centralized electronic control units (ECUs) is needed for the evolution of SDVs. Jianmin Gu, chief technology officer at Valeo China, explained that centralized ECUs optimize resource utilization and simplify the vehicle's overall architecture.

However, the increasing interconnectivity of SDVs amplifies risks associated with cybersecurity and software failures. The industry is responding with stringent cybersecurity measures and adherence to rigorous safety standards. " KPIT is a member of the AUTOSAR Consortium, the SOAFEE Special Interest Group, and other collaborative efforts aimed at standardizing the industry and making it safer," KPIT Technologies said.

The future of SDVs is promising yet complex. Advances in artificial intelligence and machine learning are expected to enhance vehicle autonomy and user-centricity. The various applications of large language models "contribute to an improved user experience in cars," noted Lei Qin Hui, chief technology officer of Iflytek Intelligent Auto. "The combination of technology and human interaction creates a holistic experience for car users."The economic implications of SDVs are significant, opening doors to new revenue streams for manufacturers through subscription-based services for software updates and in-vehicle applications. This model mirrors trends in the software industry, where continuous delivery and service-based revenue are becoming the norm. "Automakers are beginning to understand that a significant portion of the software stack is not differentiating," Chow explained. "So much time and precious engineering resources are wasted reinventing nondifferentiating software." This awareness is prompting manufacturers to rethink their business models and focus on genuinely unique features.

For automakers, this transition is not just about keeping pace; it's an opportunity to redefine the driving experience and create a connected, intelligent and user-centric future.

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