Introduction
Modern cars are no longer just a bunch of nuts and bolts – they are far beyond, a computer encased into a finely tuned and carefully crafted body. Beyond flashy features like over-the-air updates and self-driving tech, software is quietly revolutionizing every aspect of the automotive industry – from how cars are designed and built to how they’re driven, maintained, and even recycled. Next I would like to propose classification of the full chain digitalisation bound to the SDV paradigm. In this article, we’ll explore six levels of software-driven transformation, each building on the last, that are reshaping the automotive landscape. Whether you’re a driver, an engineer, or just curious about the future of mobility, this journey will show how software is turning cars into smarter, cleaner, and more sustainable partners.
Level 1: Software Defines Capabilities
Vehicle capabilities are the cornerstone of a brand’s identity, shaping its model lines and variants. While earlier vehicles relied on hardware innovations, software now drives their evolution. This marks the first level of a paradigm shift in vehicle engineering.
Engineering Impact
Over-the-air (OTA) updates enable real-time software patches, performance tuning, and feature rollouts (e.g., Tesla’s Autopilot refinements).
Digital twins simulate updates and edge-case scenarios in virtual environments, reducing reliance on physical prototypes (e.g., GM’s Ultifi safety testing).
Industrial Shift
Monetization and customization: Business models are shifting toward subscriptions (e.g., BMW’s heated seats) and à la carte features (e.g., Porsche’s horsepower unlocks).
Reduced recalls: OTA updates minimize dealership visits for software fixes, cutting downtime and logistics costs.
Green Angle
Digital twin testing: Virtual simulations slash the need for physical prototypes, reducing material waste and energy use.
Extended hardware lifespans: OTA optimizations (e.g., Tesla’s battery management) delay replacements, curbing e-waste.
Level 2: Software Defines Design
In recent years, the automotive industry has shifted from manually crafted vehicle designs to digital platforms that enable feature-driven software development. This transformation paves the way for new design tools and collaborative workflows, replacing outdated hardware with cutting-edge computing and communication systems.
Engineering Impact
HPC/Zone Controllers: Centralized computing (e.g., Tesla’s Hardware 4.0, Bosch’s zFAS) replaces fragmented ECUs, enabling real-time processing.
Simplified topology: Automotive Ethernet and unified protocols (e.g., SOME/IP) streamline communication, cutting wiring by up to 30%.
Industrial Shift
Dynamic application deployment: High-performance computing (HPC) platforms allow region-specific feature rollouts (e.g., Toyota’s cold-weather battery preheating).
Micro-applications: Smaller, frequent updates replace bulk OTA packages (e.g., Mercedes’ “Feature-on-Demand” micro-updates).
Green Angle
Reduced wiring: Simplified topologies lower copper usage and vehicle weight, improving energy efficiency.
Energy-efficient HPC: Zone controllers optimize power distribution (e.g., Ford’s Smart Energy Management).
Level 3: Software Defines Architecture
Modern vehicles are dynamic platforms designed for upgrades and expansions. They're not just static hardware with a thin layer of software anymore. This architectural shift introduces modularity, enabling hardware and software to evolve independently. It also opens the door to new partnerships, breaking the traditional barriers of the automotive industry.
Engineering Impact
Information system topology includes smart modules: Modular components like NVIDIA DRIVE AGX Orin or Bosch’s smart sensors integrate into unified architectures.
Smart modules (modified zone controllers) determine vehicle capabilities: Upgradable hardware/software units (e.g., Qualcomm’s Snapdragon Ride Flex) enable feature scalability (e.g., adding autonomous driving via software).
Third-party integration: Open APIs enable automakers to incorporate third-party apps and hardware (e.g., HERE Maps navigation, Brembo brake optimizations).
Industrial Shift
Third-party partnerships: Automakers collaborate with developers to expand feature ecosystems (e.g., Ford’s integration of Android Automotive OS).
App stores for vehicles: Platforms like Mercedes’ MB.OS Marketplace monetize third-party software/hardware.
Green Angle
Reduced redundancy: Smart modules consolidate functions (e.g., one compute unit handling infotainment and diagnostics), cutting material use.
Circular upgrades: Third-party modules (e.g., refurbished battery controllers) align with sustainable reuse practices.
Level 4: Software Defines Engineering
When the vehicle-level architecture is clear, agile, and supported by advanced tooling, it’s time to align hardware engineering with established software practices. This marks a fundamental shift: hardware is no longer a static, dedicated design – it’s becoming hardware as code. Just as software evolves through iterative updates, hardware now adapts dynamically, enabling vehicles to grow and improve over time.
Engineering Impact
Dynamic topology with hard/soft expansion points: Vehicles incorporate modular interfaces (e.g., Tesla’s hardware slots, NVIDIA’s Drive AGX) for physical (hard) and software (soft) upgrades.
Feature-centric paradigm: Engineering prioritizes user-facing capabilities (e.g., GM’s Ultium platform integrating battery, motor, and autonomy) over individual ECUs.
Phased certification: Features (e.g., Tesla’s FSD beta), modules (e.g., Bosch’s radar systems), and final configurations are certified independently, accelerating time-to-market.
Industrial Shift
Agile certification workflows: Regulators like NHTSA adopt phased approvals (e.g., Mercedes’ Level 3 autonomy certification in stages).
Collaborative ecosystems: Automakers pre-certify modules (Qualcomm’s AI chips) with tech partners to streamline compliance.
Example: Ford’s BlueCruise certified hands-free driving separately from core vehicle safety.
Green Angle
Redundant hardware elimination: Feature-centric designs remove unused components (e.g., duplicate sensors), cutting material waste.
Energy-efficient modularity: Dynamic systems activate power-hungry features (e.g., autonomy) only when needed, optimizing energy use.
Level 5: Software Defines Manufacturing
Fully digitized products are driving a tectonic shift in manufacturing processes. No longer constrained by rigid assembly lines, factories are evolving into dynamic, software-driven ecosystems. From the earliest design stages, it’s clear where and how to build a vehicle, what changes to the production line are necessary, and how much they’ll cost. This transformation enables unprecedented flexibility, efficiency, and sustainability.
Engineering Impact
Transition to assembly sites: Flexible, decentralized production hubs replace rigid assembly lines (e.g., Tesla’s Gigafactories using modular workstations for parallel workflows).
Heterogeneous module integration: Production technologies (e.g., NVIDIA’s Omniverse digital twins, ABB’s adaptive robots) unify diverse components (batteries, sensors, AI chips) into cohesive products.
Reconfigurable assembly points: Modular platforms (e.g., GM’s Ultium) allow factories to adapt workflows for different vehicle configurations (SUVs, trucks) on the same line.
Industrial Shift
Decentralized production: Regional assembly sites (e.g., Toyota’s “local-for-local” hubs) reduce shipping distances and costs.
Dynamic supply chains: Software tracks and allocates modules (e.g., Bosch’s sensor kits) to factories based on real-time demand.
Example: Volkswagen’s MEB platform enables factories to switch between EV models (ID.4, ID.Buzz) in hours. Ford’s 2024 AI-driven system tracks and allocates modules (e.g., Bosch’s sensor kits) to factories based on real-time demand.
Green Angle
Waste reduction: Flexible assembly sites minimize overproduction and unsold inventory.
Material efficiency: Optimized integration of heterogeneous modules cuts scrap (e.g., BMW’s 30% scrap reduction using AI-guided cutting).
Reconfigurable vehicles: Assembly points allow post-purchase upgrades (e.g., battery swaps), extending vehicle lifespans.
Level 6: Software Defines Lifecycle
The transformation doesn’t stop at manufacturing – it extends to the entire lifecycle of a vehicle. Responsible development is now economically driven, as modular and localized designs require shorter, more efficient supply chains. By designing vehicles with recycling in mind, automakers are unlocking new opportunities for sustainability and cost savings.
Engineering Impact
Supply chain-integrated design: Volkswagen’s MEB platform is designed with recycling in mind, using modular battery packs that can be easily disassembled and reused. VW’s Salzgitter plant, operational since 2023, focuses on battery recycling, aiming to recover 97% of raw materials.
Closed-loop systems: Tesla’s Gigafactory Berlin integrates a closed-loop recycling system, recovering 92% of battery materials and feeding them back into production. Audi’s 2025 PPE platform integrates closed-loop recycling, recovering 95% of battery materials for reuse.
Industrial Shift
Dynamic regional rebalancing: Ford’s real-time supply chain adjustments during the 2023 semiconductor crisis, leveraging AI to reroute components and minimize production delays.
Globalized, customer-tailored supply chains: BMW’s “Local for Local” strategy sources batteries from CATL in China, Northvolt in Sweden, and AESC in the US, tailoring supply chains to regional demands.
Example: Volkswagen’s MEB platform enables factories to switch between EV models (ID.4, ID.Buzz) in hours, optimizing production for regional markets.
Green Angle
Localized sourcing: Volvo’s 2023 commitment to use 100% fossil-free steel from SSAB’s HYBRIT initiative, reducing CO2 emissions by 90% in its Swedish factories.
Waste reduction: Toyota’s 2023 “Beyond Zero” initiative combines just-in-time manufacturing with AI-driven demand forecasting to eliminate overproduction and reduce waste by 30%.
Example: Redwood Materials’ 2023 expansion in Nevada recycles batteries from Tesla, Ford, and Panasonic, recovering 95% of critical metals like lithium, cobalt, and nickel.
Conclusion: The Unavoidable (R)Evolution
The automotive industry isn’t chasing trends – it’s adapting to survive. Software-defined vehicles represent a pragmatic fusion of engineering ambition, industrial efficiency, and environmental stewardship. While challenges like battery recycling, ethical sourcing, and regulatory fragmentation persist, the direction is clear: cars will keep evolving into smarter, leaner, and cleaner machines.
Today’s industry already has most of the tools necessary to drive toward a more personalized and sustainable future. It’s a field ripe for innovation, where startups can – and will – emerge and grow. The only question left is: Where to focus to succeed? There’s no single answer. Instead, it’s an opportunity to evolve and revolutionize every aspect of the automotive industry, from design and manufacturing to ownership and recycling.
This transformation isn’t optional. For engineers, it demands fluency in code as a core material. For industries, it requires agility in an era of disruption. For the planet, it offers a roadmap to reconcile mobility with sustainability.
The road ahead is coded, but the destination is open-ended – shaped by collaboration, innovation, and the choices we make today.
The automotive industry is at a crossroads. For engineers, it demands fluency in code. For industries, it requires agility. For the planet, it offers a roadmap to reconcile mobility with sustainability.
The road ahead is coded, but the destination is open-ended – shaped by collaboration, innovation, and the choices we make today.
