Path toward vehicle autonomy may be longer but will be fruitful

In a riveting interview conducted by Telematics Wire, GK Senthil delves into the world of automotive mobility, unraveling its multifaceted impact on the industry.

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Can you share your views on technological change or transition in the automotive landscape over the last decade?

Certainly! Change in the auto industry has accelerated over the last few years, with the need for sustainability, safety, hyper-personalization, and assistive technology as a priority. Moreover, we enter an era where connected mobility is not just a requirement but an experience consumers crave.

These priorities are being accelerated by adapting an ecosystem play with tight integration to vehicle hardware over providing individual or siloed apps and services, as was the trend in the initial days. This is not just from the perspective of Connected services but the entire lifecycle of vehicles like manufacturing, sales, service, and the “used car” life beyond the first buyer.

What might significantly impact this transition? Marrying predictive, AI/ML-based technology to provide contextual services for efficient, eco-friendly, convenient, and safe driving, if not fully autonomous, is the transition we have already started experiencing – this should accelerate quite steadily in the next few years.

We must innovate around Smart and flexible charging and energy management systems in EVs to ensure sustainability.

How will the in-vehicle infotainment system/device evolve in the coming years?

Moving forward, it is better to think about the cockpit as a whole rather than the infotainment system in isolation. Advancements in display technologies and increased processor capabilities are now paving the way for integrated cockpit systems that display relevant information in concert across instrument clusters and the head unit (and even the heads-up display).

With voice, gesture, and touch controls, sophisticated digital clusters, heads-up displays, wider screens, and tighter integration to vehicle hardware like cameras and other sensors, the best safety features and most relevant content for the occupants can be available.

While smartphone-based Infotainment systems provide convenience and a lower cost option for customers, lack of integration to vehicle hardware limits the capabilities of those systems. It is critical to have a unified view of the vehicle environment (traffic, weather), vehicle state, and the driver’s inputs (destination, route, music, etc.) to provide the best driving experience.

What are your views about the connected vehicle ecosystem in India?

Though the penetration is quite low, the connected vehicle ecosystem is evolving beyond basic services such as location tracking, emergency management, remote diagnostics, and convenience services like a remote start. We see the tech being adopted rapidly to efficiently manage a Fleet of vehicles through features such as trip management, fuel accuracy, driver behavior monitoring, and micro-billing systems. With the rising number of electric vehicles, we also see EV connect, charge and control management picking the pace in India. I expect integrating the vehicle-connected ecosystem into 3rd party services to advance rapidly in the next few years.

How do you see leveraging data for utmost safety and convenience in the coming years?

Data is, of course, the fuel for connected cars. As carmakers, we are optimizing the use of data to drive our customers’ capabilities. For example, given access to the video from the vehicle’s camera feed, the infotainment system can tell exactly which upcoming turns to take – reducing complexity while improving safety. We can solve many complex challenges by leveraging AI and ML technologies. Detecting drunk driving, Accurate directions with AR-based navigation systems, detecting micro collisions for insurance purposes, determining exact fuel left, understanding driving behavior, etc., are all possibilities to enhance driving and ownership experiences for personal and fleet vehicles. These would rely on continuous data streams of vehicle and environmental states combined with powerful algorithms processed mostly on the edge.

Is there any product that you would particularly want to talk about?

With our innovation hats on, we set out to enhance customer experience at the vehicle dealerships. Leveraging advanced Computer vision algorithms, we developed a product we call “Gatekeeper.” This AI-based license plate recognition enables dealer associates to quickly identify and associate the incoming vehicle with appointments for much faster service. It is live in more than 200 dealerships across India, and they are quite happy with how this product improves customer service. As of Dec 2023, we have processed more than 2.5M license plates while extending the solution to even opening the facility gates automatically, further reducing manual interventions.

What are your views about the path toward vehicle autonomy?

Over the last decade, most have realized that the dream of a fully self-driving vehicle (not requiring any human intervention) is farther away from reality than we once thought. Despite that, forms of autonomy have come to fruition in several smaller yet useful forms, from basic features like adaptive cruise control to advanced conditional automation with vehicles handling steering, braking, acceleration, lateral control, and navigating intersections! That’s quite exciting indeed.

Significant changes have been made in technology strategy. Most players are now moving away from long-range lidar to a combination of camera & radar systems (or even adapting additional ultrasonic) thanks to rapid increments in computer vision accuracy over the last few years via advancements in Machine learning techniques.

Automotive giants and start-ups are now more focused on solving narrow-range scenarios (like portions of a town, closed-loop shuttles, deliveries, etc.). That’s probably the most viable path since scaled adoptions, even in constrained environments, provide significant learning to improve the technology, which will help solve additional constraints. In essence, the path may be longer than expected but will be fruitful.

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Read the article here aswell

https://www.telematicswire.net/path-toward-vehicle-autonomy-may-be-longer-but-will-be-fruitful/

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