AI is Already Driving The Future of Connected Cars

Connected Cars and Our Future The evolution of end user devices isn't surprising – you can surely relate to the excitement gen...

Connected Cars and Our Future

The evolution of end user devices isn't surprising – you can surely relate to the excitement generated by the unveiling of Windows PC in 1990 and iPhone in 2006. This time, however, it is the automobile industry that undergoes an interesting change. 

Smart vehicles have created lots of hype and rightly so. In the next 15 fifteen years, the automotive industry is bound to exponentially expand and transform. As forecasted by Gartner there will be 250 million connected cars on the road by 2020. 

What is a Connected Car?

A connected car basically is a vehicle with internet access and WAN. You can share internet access with other devices both inside as well as outside the vehicle. Because the car will be using and generating a lot of data, it can help create new business models. 

Connected cars would be like moving computers. So it is important to have the right infrastructure that can process and analyze the data. And this future of connected cars will be driven by AI. 

What is Al?

Thanks to AI technology, you will not drive your car the same way again. This technology not only is useful in processing and analyzing data, but it changes the way your electronics systems work. Instead of stereos, connected cars would have sophisticated applications similar to ones in our PCs and smartphones. 

This is made possible by sensors which are becoming cheaper, yet more sensitive and reliable with every passing day. Dozens of ‘smart’ sensors will be installed in connected cars, and they’ll help collect, process and analyze massive amounts of data. 

Cloud connectivity makes the concept of connected cars more exciting. Your car, like your smartphone, would update applications directly from the cloud. Similarly, data collected from sensors can be sent to the cloud for storage. The data from the sensors can be directly forwarded to the cloud, or it can be transmitted peer-to-peer through a V2V or V2I set up. This way clouds can function as the central directory of all street and city level views. 

As you can guess, connected cars will generate incredible amounts of data. And efficient processing of this kind of data will require superior machine learning and AI capabilities. These two processing powers are already being used in advanced computing and for recognizing images. 

An IHS technology report published recently revealed that the usage of AI systems in vehicles will grow from 7 million to 122 million from 2015 to 2025. AI will be the new standard. More importantly, it will change the way humans interact with cars and how they interact with us. 

Yes, you can expect smarter interactions with connected cars. These include voice recognition, gesture prediction, virtual assistance, driver monitoring, and natural language processing. Not only can drivers speak to their cars through AI, but they can also expect a response in return. 

AI is also necessary to make advance driver assistance systems (ADAS) a commercial reality. Functions like camera based machine learning systems, radar bases detection units, driver evaluation and sensor fusion engine control units are all necessary for autonomous vehicles. For connected cars to work, it is important that cars are able to recognize objects, adapt to new road conditions and even predict actions. 

We are moving along the path that would lead our vehicles to full autonomy however that is going to be one long road. We are still many years away from autonomous level 4 cars for the general public. However, from 2017 and beyond, we are going to achieve significant milestones which will help us build the needed infrastructure for collecting data and creating maps in real time for ADAS.

How can cars become autonomous?

Well, the first way is recording the “millimeter precision” – this means identifying and recording locations of stationary objects. This method can be useful for recording directions and precise lane information. But the problem with this approach is that it will be expensive and extremely time-consuming. More importantly, it will require ongoing updates so the that the information does not become obsolete. 

The second way to do this is through the deployment of semi-autonomous vehicles to collect data which will require an entirely new generation of cars with super sensors. However, only a few cars will be ready for this by 2017. 

The final option coming in this year is to use new technology to collect data from the non-autonomous vehicles already on the road. 

For example, signals of abrupt steering changes at one point can help identify an obstacle. Similarly, slipping wheels and the usage of wipers could be noted to get information about the weather in a particular area. 

The wonders of machine learning that will take place from all this data can help develop better ADAS systems for the upcoming generation of cars and also provide insight for making better models of such next generation vehicles.

Author Bio:
Rachael Everly is a passionate blogger and an avid luxury car lover currently associated with Alfa Romeo Central Florida, dealers of luxury cars in Orlando Central Florida. 



Vyas Infotech: AI is Already Driving The Future of Connected Cars
AI is Already Driving The Future of Connected Cars
Vyas Infotech
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