“India’s talent pool in AI and software engineering is a unique strength“

ADT: How do transformative technologies accelerate SDV development in India?

Rao: India’s automotive sector is undergoing a shift toward Software-Defined Vehicles (SDVs), driven by both global trends and local demands. Several key transformative technologies are accelerating this shift in India: The adoption of high-performance computing (HPC) and zonal computers in vehicle architectures is consolidating functionalities across fewer, more powerful processors —resulting in reduced wiring weight, and enabling upgradability. This architectural simplification is a critical enabler for SDV scalability. A growing number of Indian vehicles now support over-the-air (OTA) updates and adoption of service-oriented architecture (SOA) middleware such as Adaptive AUTOSAR that enables easier updateable ECUs. Continuous integration/continuous deployment (CI/CD) practices enable more agile and iterative software releases while cloud-based development enables global scaling. Secondly, the acceleration of electric vehicle (EV) adoption, driven by strong government incentives (such as FAME II and state-level subsidies), is opening new software-driven innovation pathways. The newer EV platforms rely on software for battery management, motor control, thermal management, and AI-driven features such as battery health estimation and virtual sensors for motor positioning.

ter Waarbeek: Another key driver is the integration of Level 2 ADAS features, such as lane keeping, adaptive cruise control, and emergency braking. India’s latest launches have seen features such as park assist which add immense value for drivers in congested urban areas. These software-defined systems require perception algorithms, sensor fusion, and integration with control algorithms. AI is a transformative force, especially in areas like driver behavior modeling, virtual sensors, predictive maintenance, and personalization. Together, these technologies are helping Indian OEMs transform legacy offerings into SDVs. India’s large work force in global technical centers is meaningfully contributing to the global SDV landscape as well. India’s large talent pool in AI, software engineering, and embedded systems is a unique strength. Many global OEMs and Tier-1s have set up engineering centers in India to leverage this talent—not just for cost advantages, but for the depth of technological advancement. The combination of technological readiness and engineering talent makes this an exciting moment for SDV development in India.

What role does MathWorks play in supporting these technologies?

ter Waarbeek: MathWorks plays a central role in supporting the development and deployment of the application software layer. The SDV stack typically consists of a hardware layer (microcontrollers/microprocessors), a middleware layer, an application software layer, and connectivity to the cloud. For decades, automotive customers have used Simulink, a simulation-lead development environment, to model control algorithms and reuse implementations across hardware platforms. As SDVs enable over-the-air (OTA) updates, the software architecture is shifting from rigid, signal-based designs to flexible, discoverable SOA. Simulink has evolved to support these new architectures. MathWorks provides automatic code generation of safety-critical C or C++ code for a wide range of targets—including HPCs, microcontrollers, FPGAs, and CPUs. With the decoupling of hardware and software in SDVs and the rise of middleware, MathWorks has extended its code generation capabilities to support integration with AUTOSAR Classic, AUTOSAR Adaptive, ROS, and proprietary middleware platforms. This ability to reuse control algorithms and generate code for specific targets and middleware reflects the core advantage of Model-Based Design, which remains central to the MathWorks development philosophy. To support the SDV requirement of separating software from hardware, MathWorks enables virtualization at multiple levels, such as Model-in-the-Loop(MIL) and Software-in-the-Loop(SIL). This enables development of application software early in the development cycle prior to the availability of middleware and hardware. Tools like RoadRunner support the creation of virtual environments, which are essential for simulating real-world driving scenarios—especially in ADAS development, where extensive testing is needed.

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Rao: In India, we are incorporating localized assets such as two and three-wheelers, and culturally relevant road furniture into these simulations. Simulink also supports integration with commercial and open-source third-party tools, enhancing interoperability in complex SDV workflows. As DevOps and CI/CD practices become standard, MathWorks tools support cloud-based access and development (code generation and in-the-loop testing), data connectivity, and cloud deployment. MathWorks is enabling customers to develop application software that is updatable, providing flexibility to deploy code on a range of targets, enabling virtualization to speed up software development, and integrating with CI/CD practices - all critical to application software success in SDV programs.

Can you provide examples of successful implementations in the automotive industry?

Rao: In the area of ADAS, MathWorks is enabling engineers to develop and validate algorithms tailored for Indian driving conditions. In collaboration with ARAI (Automotive Research Association of India—India’s premier automotive R&D, testing, and certification body), MathWorks developed a workflow to bring recorded data from Indian roads into simulation environments. Working with a leading commercial vehicle OEM, MathWorks tools and workflows supported automation of data annotation, generation of realistic 3D scenarios, virtual modeling of sensors and vehicles, ADAS algorithm integration, and custom performance metric definitions. These efforts enabled effective development and validation of collision detection warning systems in real-world Indian scenarios. Among the many examples in AI, MathWorks supported another prominent commercial vehicle manufacturer in developing an AI-powered chatbot that leverages generative AI and natural language processing (NLP) to transform vehicle diagnostics. Built on Retrieval-Augmented Generation (RAG) architecture with large language models (LLMs), the chatbot interprets service manuals to provide accurate, real-time responses—enhancing diagnostic precision, reducing repair time, and improving the experience for both technicians and vehicle owners. With a growing influx of young engineers entering the automotive workforce, the need to equip them with domain-specific skills is pressing. MathWorks is uniquely positioned to address this challenge due to its strong roots in both the automotive industry and academia.

ter Waarbeek: One notable example is the AUTOSAR course—a tri-party collaboration between MathWorks, Continental, and Amrita University—designed to provide in-depth understanding of AUTOSAR architecture, tools, and methodologies. Another successful initiative, developed with Bosch and NIT-Calicut, addressed the shortage of systems engineering talent. The results were compelling: months of on-the-job training were eliminated, enrollment increased by 250%, and over 90% of students provided positive feedback. A long-standing success story comes from Ather Energy, an EV startup committed to building India’s first intelligent electric scooter. From incubation to production, Ather partnered with MathWorks to evaluate design alternatives in weeks instead of months, reduce testing time by 50%, and resolve field issues rapidly, accelerating their journey to market. Today, MathWorks supports innovation across technology domains including EV, ADAS, AI, and SDV, and across industry segments such as two-wheelers, passenger cars, commercial vehicles, global technical centers, research institutions, and academia. As young India looks forward to smarter and cleaner mobility solutions, MathWorks continues to play a key role in enabling the development of future-ready features through its deep expertise in automotive technology and engineering workflows.