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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