The future of automotive: software-defined vehicles (SDVs)

The traditional concept of a vehicle is undergoing a dramatic transformation. One of the key driving forces behind this transformation is the emergence of Software-Defined Vehicles (SDVs). An SDV represents a departure from conventional vehicles, offering a unique value proposition driven by software innovation and digitalisation.

Unlike traditional vehicles, where the passenger and driving experiences were largely determined by mechanical and electrical systems, SDVs place software capabilities at the forefront. These vehicles continuously evolve throughout their life cycles, thanks to the ability to deliver software updates and enhancements.

In operational terms, SDVs are defined by their software, acting as the “brain” of the vehicle. They contain critical information, such as design parameters, failure-mode event analyses, quality fix procedures, and manufacturing processes. This combination of data enables SDVs to self-diagnose and correct discrepancies as they arise.

While automakers are eager to embrace the potential of SDVs, they face various challenges. Economic conditions and uncertainty about aligning with customer expectations for new business models pose obstacles. Furthermore, the complexity of coordinating software integration among stakeholders, including OEMs, suppliers, and technology collaborators, can lead to delays.

However, the benefits are clear. SDVs allow for feature-rich, personalized experiences, and they support a shift towards customer-centricity. Shared mobility is on the rise, with a growing number of individuals questioning the need to own a vehicle, particularly in regions like Europe. To meet these changing demands, automakers must adopt more agile and flexible approaches to management and technology stacks.

To fully leverage the potential of SDVs, vehicle manufacturers are exploring open software ecosystems that invite third-party app developers to contribute, akin to smartphone app stores. This approach empowers consumers to decide which apps are successful, encouraging innovation and customisation.

SDVs also require a rethinking of how vehicles are designed, developed, and maintained. Hardware virtualisation and advanced simulation capabilities are critical for early software testing and validation, reducing the risk of critical bugs or safety hazards. The shift-left testing approach emphasizes early testing in the development cycle

The increasing digitisation of vehicles generates vast amounts of data, which necessitates effective data management across the ecosystem. Connected vehicle data is growing exponentially, reaching 117 exabytes by 2027. Software platforms, powered by cloud, artificial intelligence, and agile methodologies, will shape the future digital experience in vehicles.

Source: Software-defined vehicles: Engineering the mobility revolution | Deloitte

Infographic titled "Deloitte’s perspective on SDVs: Solution space" highlighting six key areas: Autonomous driving, Power train and vehicle motion, User-centric experience, Architecture core blueprint, Software-based R&D and operations, Data-driven and usage-based services. Centered on a cloud and SDV.
Source: Software-defined vehicles: Engineering the mobility revolution | Deloitte

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