Artificial intelligence and data science-powered systems which promote safe mobility for all there is no limit to human imagination. Not only are these advancements making cars affordable, but they are also making them environmentally safe a feat that was hard to achieve until recently. https://www.loginworks.com/blogs/how-artificial-intelligence-and-data-science-are-reshaping-automobile-industry/

1. HOW ARTIFICIAL INTELLIGENCE AND DATA SCIENCE ARE
RESHAPING AUTOMOBILE INDUSTRY?
The automobile industry is poised at the brink of an automotive revolution. From hybrid and
electric vehicles that offer a balanced driving experience to artificial intelligence (AI) and data
science-powered systems which promote safe mobility for all, there is no limit to human
imagination. Not only are these advancements making cars affordable, but they are also
making them environmentally safe, a feat that was hard to achieve until recently. According
to a report published by the International Organization of Motor Vehicle Manufacturers, the
automobile sale statistics from 2005 to 2017 have seen a constant growth, and this trend is
expected to continue in the future.
While innovation has always shaped the automobile industry, change in the fields of artificial
intelligence and data science is the new bandwagon of growth.
This correlation of data science with automobiles has further spurred the demand for data
science courses.
With car manufacturers like Tesla and Ford upending the dynamics of the automobile
industry, there is no denying the fact that AI and data science in automobiles is more than a
brief trend. Vehicles with features like automatic locks and Bluetooth are now passé, and
thanks to the contributions of AI and data science, autonomous vehicles are now reshaping
the automobile industry.

2. AUTONOMOUS VEHICLES AS THE PRESENT AND FUTURE
As mankind becomes more dependent on technology and expects more innovation out of
every sector, it is hardly surprising that the automobile industry would be any different. Over
the past few decades, car manufacturers have worked relentlessly to link automotive
hardware to software, and the results are promising. As smart ‘driver assistants’ slowly
wedged their way into cars, connectivity features became commonplace. Today, cars come
equipped with personal assistants that inform drivers about lane departures and provide
automated features like emergency brakes, collision avoidance, and blind spot warnings.
WHAT ARE AUTONOMOUS VEHICLES?
While these ‘smart’ cars are available in the mass-market, when it comes to automation, it is just the tip of the

3. iceberg. Powered with advances in data science coupled with AI, car manufacturers are looking at a different
goal altogether – making vehicles genuinely autonomous. Truly autonomous vehicles are being designed with a
vision in which the passenger taps the destination into a smartphone, steps inside the vehicle, and is driven by
the computer. These genuinely autonomous or driverless cars is where the automobile industry is headed.
The truly autonomous vehicle is still a vision for manufacturers; however, significant leaps have already been
made in this direction.
The Society of Automotive Engineers (SAE) has defined five levels of autonomous control.
These levels range from full manual control (Level 0) to complete automation (Level 5). While most car
manufacturers are at partial automation (Level 2).
Car companies like Audi and Tesla are already making Level 3 (manual intervention is required in some
situations) a success.
ROLE OF DATA SCIENCE AND AI
The concept of autonomous cars has taken wing because of the opportunities that data science and AI has
provided to carmakers. Manufacturers have collected massive amounts of data on human responses to traffic
conditions, collision and obstacle avoidance, how people react, what a driver is most likely to do when faced
with certain situations, road networks, and weather conditions. Once collected, this data is processed in a
dynamic fashion using data science tools and techniques. The insights derived from these tools are then fed
into AI algorithms to make autonomous driving possible.
The assistive features and self-driving abilities are provided by AI algorithms developed using insights derived
from the data science tools. An important factor that comes into play while designing an autonomous vehicle is
that no two road situations are ever the same, and hence rigid rules cannot be set. Consequently, there comes
the need of a self-learning system that adapts from millions of miles of driving data. This correlation between
data science and artificial intelligence is what constitutes the core of an efficient autonomous vehicle.
SHARED MOBILITY
While self-driven cars are the most attractive innovation in the automobile industry, AI and data science have
more roles to play.
Car manufacturers are designing car systems that promise overall better mobility to their drivers. These cars
come packed with features which use real-time data to assist car drivers.
These include self-learning diagnostic systems that warn about impending failure, user interfaces that
recognise individual drivers’ preferences, navigation systems that make journeys shorter by using traffic
modelling and real-time data, and much more.
When change is happening on all fronts, the market for the automobile industry is only expected to see rapid
growth.
This is supported by Tractica’s market estimates in which they predict that the automotive AI market could
reach $14 billion by 2025.

4. The advancements in AI and data science have triggered a future in which cars will not only be safely driven but
will be driven by AI systems as well. With these additions, the very face of mobility and transport is changing,
and for all the right reasons. While the concept of self-driven cars may sound far-fetched at first, the
innovations in this sector have hastened the pace of change. AI and data science are not just reshaping the
automobile industry, but are now adding an altogether different dimension to the entire concept of
transportation.
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