Vehicles are becoming ‘edge devices’ of the IoT world, and the increasingly critical and differentiating role played by software is forcing OEMs to become software companies. Sandeep Terwad, Associate Vice President of Tata Technologies spoke about trends, challenges and the evolving landscape of connected vehicles. Edited excerpts.
Can you take us through the evolving ADAS technologies and their impact on automotive safety and innovation?
ADAS has evolved from rudimentary safety features like rear parking sensors to sophisticated, AI-powered systems that play a central role in improving road safety and enhancing driving experience to pave the way for true autonomous mobility in almost all cars soon. On the sensor side, radars have become increasingly sophisticated, offering higher resolution and improved performance in detecting objects and obstacles in adverse weather conditions.
Lidars have become smaller and more affordable, providing detailed 3D mapping and precise object detection. These sensors, in combination with AI algorithms and ML techniques, make ADAS systems more perceptive, and better at decision-making and predictive capabilities.
Can you take us through some regulatory challenges and compliance considerations in the development of ADAS solutions?
Compliance with safety standards established by the NHTSA in the US and similar bodies in other regions is essential to ensure that ADAS features meet minimum safety requirements and do not pose undue risks to drivers, passengers, or other road users. The ADAS technology may require regulatory approval and certification before being deployed in production vehicles. Getting the certification involves submitting technical documentation, test results, and safety assessments to authorities for review. This process is slightly time-consuming and expensive and requires close collaboration between OEMs, suppliers and regulatory agencies.
Automotive OEMs and suppliers also now need to carefully consider liability issues, product liability laws, and contractual obligations to mitigate legal risks and ensure compliance with applicable laws and regulations in case ADAS features are involved in accidents or do not function as intended.
What are the future trends in ADAS, including the convergence of AI, technology and automation?
My view is that ADAS will evolve into a more affordable and indispensable component of vehicles across the spectrum. Level 3 will become the minimum level preferred by endusers. Advancements in sensor fusion, AI, and machine learning will enhance the perception and decisionmaking of ADAS systems, making more accurate and predictive responses possible. Companies are exploring the integration of AR into ADAS solutions to enhance situational awareness and improve driver decision-making processes. This could revolutionise how drivers interact with their vehicles and the road.
ADAS will become a key differentiator for OEMs in their product offerings and the USP will be safety, comfort and convenience. Strategic partnerships and collaborations between OEMs, suppliers, and tech companies like TTL will become more prevalent, helping to leverage synergies and accelerate innovation in ADAS development. An OEM ecosystem that has better AI models will be ahead of the curve.
What are the most prominent changes you have seen in the industry in the past few years?
There has been a paradigm shift in the automotive industry in the past few years, mainly in the Connected, Autonomous and Sustainable areas. This shift has been driven by technology advancements, evolving user preferences, and integration of cloud computing, SDV, connectivity, and mobile apps. Regulatory bodies the world over have also contributed to policy changes that promote electric vehicles (EVs) and alternative powertrains, including [by the use of] subsidies, infrastructure support, tax incentives and even funding programmes.
In the case of EVs, there have been advancements in the past few years in battery technology. In general, the ePT components and charging infrastructure are becoming better day by day. In the case of Autonomous and Connectivity, there has been a significant advancement in ADAS, sensor fusion, the integration of AI and ML, over-the-air updates, remote diagnostics, etc. These are some of the changes brought in by technology. The end-users are demanding personalised experiences in their vehicles, leading to the integration of voice assistants, customisable interfaces, and adaptive driving modes tailored to individual preferences.
Vehicles are becoming increasingly connected to smartphones, smart devices, and IoT ecosystems, enabling seamless integration with mobile apps for remote control, vehicle tracking, and digital key access. OEMs are realising that the vehicle is now an edge device of the IoT world, with software playing a crucial role. OEMs are transforming themselves into software organisations making the suppliers also change likewise. A slew of standards, bodies, and alliances have formed to aid these changes in the last few years.
How has the auto landscape evolved in the 26 years of your experience? What are your challenges today?
Globalisation has led to an increase in competition and collaboration among automotive manufacturers, suppliers and external software providers like Tata Technologies. India, with its skilled technical base, has become a significant player in the automotive industry in the past several years, driving growth and innovation. At the same time, regulatory requirements, especially related to emissions, safety standards and data privacy, have become more and more stringent, influencing vehicle design, manufacturing processes and business strategies. The rise of mobility-as-a-service, like shared mobility and subscription-based models, has disrupted the traditional business model, forcing OEMs to adapt to challenging market dynamics and customer expectations.
As for the biggest challenges, my view is there is still room for improvement in the efficiency of battery technologies and ePTs (electric powertrains) to bring out a better balance in range and cost. Also, integrating complex software systems for ADAS and infotainment seamlessly without incidents is a challenge, considering the shrinking vehicle timelines.
On the business challenges, there is increased and intense competition from traditional OEMs and new entrants to differentiate their products and services. Adapting to the shift towards mobility services and shared mobility models requires OEMs to diversify their revenue streams, develop new business models, and forge partnerships with mobility service providers.
How do you see Tesla’s eventual entry to India being pivotal to the auto tech ecosystem?
I hope it brings in the needed investments in EV infrastructure and manufacturing, and encourages collaboration between Tesla and Indian companies, startups, and research institutions. This could lead to technology transfer, JVs and partnerships in areas such as battery technology, autonomous driving and renewable energy, fostering innovation and boosting the capabilities of the Indian auto tech ecosystem. Elon Musk’s presence in India could attract investment from global players in the auto tech sector and encourage top talent to join the growing EV industry in the country. This could fuel job creation, economic growth, and technological advancement in India’s auto tech ecosystem, positioning the country as a hub for innovation in electric mobility.
Can you take us through some aspects of industrial automation?
AI and machine learning have already started impacting industrial automation and manufacturing processes, for example, in predictive maintenance by analysing data from sensors, machine logs and maintenance records. Based on these, it can schedule predictive maintenance for that machine or plant. Computer vision systems nowadays inspect products on the production line for any anomalies, surface and dimensional variations, and other imperfections in real time to ensure high-quality standards. AI and ML algorithms optimise supply chain operations by forecasting demand, optimising inventory levels, and streamlining logistics processes.
Tata Technologies is innovating with cobots that work alongside human operators to increase production efficiency without compromising safety. These cobots are equipped with sensors and AI capabilities to adapt their movements and responses to their human counterparts. This synergy leads to more efficient assembly lines, where precision and safety are enhanced by robotic assistance.
How can AI and IoT lead to breakthroughs now? Some say that most features have been invented and from now on, there will be only incremental improvements.
There is still some way to go in the AI and IoT space. I do not think it will be incremental innovation, nor can we afford it to be that. There is still space for including contextual intelligence in a system so that it can adapt and personalise its behaviour based on real-time context, user preferences and environmental factors. This could revolutionise user experiences.
We need a breakthrough in edge computing technologies that could enable more efficient, real-time AI inference and decision-making at the device level. There is also a need for standardisation and interoperability across different devices, platforms and protocols, and seamless integration frameworks to unlock new possibilities for AI and IoT applications.
This feature was first published in Autocar Professional’s July 1, 2024 issue.