What Is The Role Of AI In Future Cars

Did you know that investments in Artificial Intelligence (AI) in the automotive sector exceeded over $1bn in the year 2019? Not just that. It is anticipated to grow at a rate of 35% CAGR between the years 2020 and 2026.

AI has been nothing less than disruptive in the automobile market over the last few years. With several science-fiction films sowing the seeds for human creativity and technical competence to roll out something as futuristic as driverless cars, we could safely say that we are almost there in replicating this vision.

Companies like Google, Uber, Tesla, and more are testing out self-driving cars rigorously both on-road and in their premises, showing promise of an autonomous future. All this has been immensely possible due to the role of AI in this segment, where concepts of a neural network, deep learning, clustering, regression techniques along with the Internet of Things are making this a reality today.

Besides, AI is also being extensively used in manufacturing these supercars, in assembly lines, and serving a myriad of purposes apart from taking charge of the driver seat. With so many advancements happening in this sector, we felt they had to be addressed on a dedicated write-up.

So, here are some amazing ways AI is being used to shape our future cars.

Role Of AI In Future Cars -

AI As The Driver

We’ve been looking at the news on AI-driven cars for quite some time now but there’s still a lack of clarity among masses. When it comes to artificial intelligence in driving, there are two aspects:

     Driving assist

     And driverless

  - Driving Assist

Driving assist is where artificial intelligence constantly gathers data, analyzes them, detects patterns and anomalies, and offers insights to a driver to optimize the safety, security, and comfort associated with driving. They are also referred to as smart cars.

We are looking at insights like notifications when a window isn’t shut properly when a spare part is most likely to malfunction, fuel-usage and optimization statistics, blind-spot monitoring, emergency braking, assisted steering, and any aspect that could prevent an accident.

  - Driverless

These are the futuristic supercars most of us can’t wait to get into. Completely driverless, these cars can drive autonomously without needing any assistance or supervision of a driver. In layman terms, they are filled with sensors, processors, and algorithms that take millions of driving decisions every minute. They are optimized to the extent that they can detect pedestrians, bad weather, bad road conditions, sudden animal crossing, and other instances for safe riding experience.

They are considered safe in the fact that The US National Highway Traffic Authority has shared an estimate of reducing close to $300bn in collisions and crashes.

Forecasting Maintenance

We touched upon this before. There is an aspect in data science called predictive analysis, where historic and concurrent data are studied and analyzed to come up with forecasts and estimates for the future.

These help one get insights into what might happen in the future. This is applied in automobiles to detect and estimate accurately the time a spare part could malfunction, oil light could get exhausted, batteries would drain out, and more.

The significance of predictive analytics and AI is not just alerting the driver about a probable malfunction but going a step beyond – autonomously getting them serviced. So, when an AI-powered car notices the oil lights could exhaust, it immediately takes actions to replenish it either by sending out a notification to the owner through the app or order it online with granted accesses.

Driver Assessment

This is the age of the on-demand economy. From travel and transportation to food delivery, the impact the on-demand economy has created is unlike any other. As the number of on-demand cabs and transportation services increases, the need for safer roads increases as well.

Artificial intelligence can help businesses recruit better drivers with the help of the same predictive analytics concept. They can run background checks easily, process historic data and get insights on any previous accidents the driver has been responsible for, the reasons behind it, if the driver overworked, attitude towards passengers, are they more likely to cause an accident in the future and more.

Like we said, predictive analytics is also about offering solutions. So, when a business comes across emotionally vulnerable drivers, they can offer them adequate training and counseling sessions to help them become better drivers.

Insurance Claims

Artificial intelligence is disrupting all aspects of the automobile industry and car insurance claims are no exception. This technology can be put to good use to process insurance claims faster and more precisely.

Not just this. AI is also disrupting the automotive insurance sector in the fact that it deploys chatbots to answer customers’ redundant queries and use manpower for more complex questions and concerns.

With the help of predictive analytics and risk assessments, insurance companies are also coming up with better pricing for their policies. This goes to the extent of personalized insurance as well.

AI In Car Assembly Lines

Robots in assembly lines are nothing new but the way they have evolved thanks to algorithms and data processing is. Deep learning, an AI wing is anticipated to receive a boost in terms of funding in the next couple of years, resulting in an optimized manufacturing and driving process.

With the help of AI, manufacturers are now able to

     Increase by 20% equipment availability

     Reduce by 25% inspection expenses

     Predict orders and tackle excess stock

     Detect unit malfunctions

     Minimize yearly maintenance by 10%

AI In Marketing And Targeting

From running simulations of ad campaigns and precisely targeting users and personalizing content, AI is being used in marketing and the advertising industry. When it comes to the automotive sector, assisted cars that generate huge amounts of data can be used by brands to accurately target their audiences to promote their products such as nearby service centers, engine oils, upholstery maintenance, gas stations near drivers and more.

Wrapping Up

If you notice, data lies at the fulcrum of all AI-driven activities. As data generation touchpoints increase, we could see newer ways of implementing artificial intelligence to serve drivers and passengers and make our roads safer.

In the coming years, it will be interesting to see other creative implementations of AI in the automobile market. Let us know in your comments what you feel would be something new to arrive.


Author Bio - Hardik Shah works as a Tech Consultant at Simform, a leading custom software development services provider. He leads large scale mobility programs covering platforms, solutions, governance, standardization, and best practices. 

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