Software-defined vehicles: the future of automotive is here

Modern vehicles are entirely different from their predecessors, and it’s not just about the integrated software solutions, but rather the user experience these solutions provide. It’s a bold claim, but it’s true—the only thing traditional cars and software-defined vehicles really have in common is their ultimate goal: getting from point A to point B. Laying out the specifics, more than 160 OEM executives were interviewed by Deloitte in 2024, and the results showed that there was a strategic shift toward SDVs, with 69% of OEMs implementing a centralized decision-making approach for SDV strategies to achieve consistency, cost-effectiveness, and quicker response times.

Strategic alliances are becoming more and more important, especially in operating systems, cybersecurity, and autonomous driving. The downside is that technical and business leaders have different perceptions of SDV readiness. At a high level, vehicle development is an intriguing niche, but let everything be in order. Keep reading to learn how modern software and hardware have changed the automotive industry.

The transformation of the automotive industry

The market for software-defined vehicles was valued at USD 50.81 billion in 2024 and is expected to increase at a compound annual growth rate (CAGR) of 19.47% from 2024 to 2034, reaching around USD 300.98 billion.

Chart 2: Software-Defined Vehicles Market Size (2023-2034)

Source: Precedence Research

With software-centric innovation, the automotive sector is going through a fundamental transition. Software-defined vehicles (SDVs) are the result of replacing conventional mechanical systems with sophisticated electronics and complex software stacks. Big data streams from sensors, cameras, and connection modules can be processed by centralized Electronic Control Units (ECUs) and domain-specific controllers, which OEMs and Tier 1 suppliers are progressively investing in. This change makes it possible to make decisions in real time, allocate resources effectively, and continuously improve functions through over-the-air (OTA) updates.

Among the major advancements are the incorporation of connected vehicle technology, electrification, and advanced driver assistance systems (ADAS). Powerful on-board computers are used in modern cars to control everything from autonomous drive algorithms to battery management in electric powertrains. Software is now the primary factor influencing performance, safety, and user experience. Previously dependent on separate ECUs for every subsystem, traditional automotive architectures are evolving into flexible software platforms that can be quickly updated, fixed, and improved.

The accepted principles of competition are being rewritten by alliances between tech firms and manufacturers. Cloud-based data analytics, machine learning algorithms, and high-level programming frameworks allow for ongoing vehicle function improvement, generating a feedback loop for quicker innovation. Consumers now anticipate smooth communication, customized user interfaces, and regular updates—aspects that are more commonly seen in consumer electronics than in conventional automobiles.

What are software-defined vehicles?

In addition to reflecting the progressive transition of cars from highly electromechanical terminals to intelligent, expandable mobile electronic terminals that can be continuously upgraded, the term “software-defined vehicles” describes a case in which the quantity and worth of software (including electronic hardware) in a vehicle surpasses that of the mechanical hardware. In simpler terms, SDV is a modern approach to vehicle electronic architecture. The conventional method relies on certain physical components for the vehicle’s operation. For instance, replacing hardware parts, like the head unit or display screen, is necessary to upgrade the infotainment system in a conventional car. In contrast, the software-defined approach to car manufacturing implies that the software can do these tasks. You’ll need to modify and implement the automotive software rather than the hardware. If the hardware allows it, adding new capabilities like voice control, better navigation, or vehicle apps can be done without altering any physical parts, which makes the upgrading process more economical and efficient.

The architecture of software-defined vehicles

Software-defined vehicles’ architecture is based on the combination of a modular software stack and robust computational platforms, allowing for real-time processing and ongoing feature updates. Distributed electronic control units (ECUs) with preset functions for certain subsystems, such as the powertrain, entertainment, or body control, were the foundation of automotive electronics in the past. However, the siloed approach resulted in limitations in communications, scalability, and security.

Usually referred to as domain controllers or high-performance computers (HPCs), modern SDVs combine these functions into a smaller number of powerful central computing machines. These controllers use high-bandwidth in-vehicle networking technologies like Ethernet to operate many domains, including advanced driver assistance systems (ADAS), infotainment, and the chassis. By enabling smooth data transfer between sensors, actuators, and software programs, centralized architecture improves processing efficiency.

A strong software stack supports this architecture. A platform (usually Linux-based) is used for non-essential applications like infotainment and cloud connectivity, while a real-time operating system is used for safety-critical tasks. In addition to minimizing interference and lowering the possibility of system-wide failures, containerization, and hypervisors segregate various software components. The ability to update over-the-air (OTA) guarantees that these cars always have the newest security patches, feature additions, and bug fixes.

This architecture also incorporates contemporary data management best practices. Third-party services, machine learning techniques, and cloud infrastructure can all be seamlessly integrated thanks to high-level application programming interfaces (APIs), middleware, and data orchestration layers.

Essentially, here are the most critical parts of software-defined vehicle architecture:

• Centralized computing. Powertrain control and driving assistance are all integrated into specific units by high-performance domain controllers.
• In-vehicle networking. High-bandwidth data sharing between sensors, actuators, and onboard software modules is enabled via an Ethernet-based connection, facilitating system integration and ongoing software updates.
• Telecom equipment and connectivity. Vehicle-to-everything (V2X) communication is made possible by 5G or LTE modems, providing real-time data transfer of OTA updates, remote diagnostics, and cloud-based applications for increased efficiency and safety.
• Backend systems. Utilizing machine learning algorithms for predictive maintenance, traffic pattern analytics, and feature optimization, cloud systems manage data, analytics, and storage.
• APIs and secure integration. Open interfaces promote innovation in ride-sharing, fleet management, and customized entertainment, allowing third-party services and apps to communicate with vehicle data.
• Surrounding infrastructure. Intelligent traffic lights, edge computer nodes, and road sensors provide connectivity outside of the car and provide the system with real-time data on traffic, hazards, and road conditions.

New features enabled by software-defined vehicles

Over-the-air (OTA) updates
Software-defined vehicles make use of robust connectivity to deliver regular software updates over the air, keeping core functions like driver assistance, and powertrain control current without a visit to the workshop. For example, a battery management program in an electric vehicle can be refreshed for improved range or charging efficiency whenever it is needed. This functionality maximizes performance and reduces downtime.

Advanced Driving Assitance Systems (ADAS)
Lane-keeping, adaptive cruise control, and automatic emergency braking are just a few of the new ADAS features that SDVs can quickly update by centralizing management within high-performance processing hardware. To provide more precise hazard detection, over-the-air support enables real-time optimization of sensor fusion algorithms, which include radar, lidar, and cameras. Examples include Tesla’s Autopilot, which enhances lane-centering maneuvers and collision avoidance, increasing user confidence and overall security.

Personalized user experiences
Software-defined cars provide scalable personalization by integrating user data from all domains. Driver profiles are securely stored in the cloud and can be used to regulate the climate, seats, and mirrors. This also applies to infotainment, such as voice assistant settings or favorite music streaming apps. For example, drivers can move their digital profiles across cars with Volkswagen’s ID models, giving them a consistent, user-focused driving experience each time.

Predictive maintenance
SDVs can keep an eye on things like tires, brakes, and fluid levels in real time thanks to sophisticated sensor suites and data analysis software. Automakers can anticipate any problems before they happen by processing that data in the cloud and notifying drivers to arrange service at the best times. BMW’s Condition Based Service system demonstrates how driving habits and mileage can be combined to provide insights into vehicle performance and create precise service reminders that reduce unscheduled downtime and prolong component life.

Subscriptions
Car manufacturers may activate features as needed thanks to modular software design, which opens up a new revenue source and increases driver autonomy. They can be remotely turned on and off to provide climate amenities like heated seats, improved navigation packages, and performance enhancements. For example, BMW has focused on offering subscription-based services like driving or parking assistance. Initially, the car manufacturer decided to offer subscriptions for heated seats. Yet, they faced significant backlash since customers felt like they were paying twice for something already installed at the factory. In a recent interview with Autocar, Pieter Nota, BMW’s board member for sales and marketing, explained that the company wants to add new features that drivers can activate after making a purchase, particularly for services that need constant data transfer. Examples of these features include advanced driving assistance and parking assistance. This strategy is consistent with the purchasing patterns of customers in other technological industries where monthly or yearly service fees are typical.

Vehicle-to-everything (V2X) connectivity
Cars can connect with each other, and the traffic infrastructure, including edge nodes, road sensors, and smart traffic lights. Through immediate updates about road conditions or upcoming red light signals, this data interchange continuously improves traffic flow, eases congestion, and guarantees increased safety. Toyota started equipping its vehicles with Dedicated Short-Range Communications (DSRC) technology, which allows vehicles to share information about braking, road conditions, and even parking spot availability. This technology ultimately paved the path for more intelligent and collaborative transportation systems.

Challenges and considerations in software-defined vehicles

Protecting the data vault
Data privacy is one of the biggest issues with software-defined vehicles (SDVs). From driving behavior analysis to customized infotainment settings, SDVs are continuously sharing large volumes of data with backend systems and outside businesses.  Automakers must guarantee strong encryption, safe storage, and open data-collecting practices as laws like the General Data Protection Regulation (GDPR) continue to change.  Failing to do so puts firms at risk of financial and legal consequences in addition to undermining user trust.

Ensuring the vehicle’s software is dependable
Reliability in SDVs is mission-critical. Any glitch, malfunction, or unplanned failure in software might have real-world safety repercussions. Automakers use redundancy and a fail-safe architecture, which involves several sensors and computation units cross-checking signals, to prevent these risks. Additionally, they adhere to strict automobile safety requirements like ISO 26262. As a result, there is a lower chance of catastrophic system failures since all stages of development—from design to validation—comply with strict thresholds.

Managing the complexities of integration
Across several electronic control units (ECUs), SDVs run millions of lines of code. For developers and integrators, this immense complexity presents a hurdle. Effective software integration requires modular program design, standard communications protocols, and stringent test frameworks. For seamless data flow from powertrain control to infotainment domains, OEMs must work closely with Tier 1 vendors and technology partners to unify diverse codebases.

Closing the gap in interoperability
The largest issue with current vehicle systems is interoperability, particularly when using external services like cloud computing or smart infrastructure. Data sharing may be impeded by closed interfaces, making holistic vehicle-to-everything (V2X) connections challenging to accomplish. Cross-industry collaboration and the establishment of open standards allow for the rapid enablement of novel applications like autonomous driving, traffic flow, and predictive maintenance.

Repair and maintenance for vehicle health
Considering the growing popularity of software-defined vehicles, maintenance and repair involve more than just basic mechanical solutions. Professionals require advanced diagnostic tools and knowledge to identify software problems, firmware bugs, and buggy updates. Over-the-air (OTA) fixes can fix some problems remotely, but expert hands-on repair is still necessary for hardware and software malfunctions or embedded code flaws. Then, to meet the changing digital needs of SDVs, repair shops need to continuously invest in training and certification.

Getting over regulatory barriers
SDVs frequently have to deal with disjointed international legislation when navigating the legal system. Multinational firms have compliance issues due to regional variations in data security, emissions regulations, and vehicle design standards. A further barrier is presented by safety requirements, such as ISO 26262 and those on cybersecurity, that call for thorough testing and documentation to provide consistent reliability across all markets. One factor contributing to these difficulties is autonomous vehicle policy. While certain countries have implemented pilot programs and temporary regulations to allow for self-driving technology, others have more restrictive laws, creating a patchwork of limitations that deters testing and deployment across international borders. Furthermore, consumer protection regulations that require openness in the collection, storage, and utilization of personal data are still being created.

The future of software-defined vehicles

The concept of software-defined vehicles is not a new one, yet vehicle manufacturers have to adapt their business models to facilitate the integration of new software architecture to meet consumer demands and ultimately ensure safety, because it is the most critical of all vehicle features.

Want to learn more insights about what modern vehicles offer? Interested in how Avenga can facilitate software development beyond the automotive market? Contact us.