The applications of AI in automotive industry more than the concept of self-driving cars. Read on to know more about it…
Modern cars now come equipped with a plethora of autonomous bells and whistles that help people drive safer on the roads. However, the ever-approaching advent of the era of self-driving cars continues to remain several years in the future. The question is, where are we in the process of developing self-driving cars, and how does AI play a role currently as well as in the future of the autonomous transportation industry?
The applications of Artificial Intelligence (AI) in automotive industry more than the concept of self-driving cars. Artificial Intelligence can do more than drive — infact it can keep us connected, on schedule, and safe even when we are driving ourselves. The value of Artificial Intelligence in automotive manufacturing and cloud services will exceed $10.73 billion by 2024.
While there is a great deal of technology that has been poured into the development of self-driving cars, there’s no doubt that Artificial Intelligence has held a leading role. After all, autonomous transportation is one of the main stomping grounds of the fledgling machine learning revolution. And, of course, the idea of Machine Learning (ML) is largely made possible by AI, as it gives computers the ability to independently find patterns in various sets of data, allowing it to make predictions and decisions based off the results.
Having masses of information available allows self-driving cars to “think” in increasingly complex ways that integrate everything from driving in a straight line to something as nuanced as detecting an object in a vehicle’s path and stopping before a collision.
Beyond Self Driving
AI is not only changing what a vehicle can do, it is also changing how vehicles are built. AI does more than respond to what is happening in the vehicle’s vicinity. Powerful AI deep-learning algorithms can accurately predict what objects in the vehicle’s travel path are likely to do. A pedestrian on the sidewalk? AI in self driving cars knows they might step into the street at any moment. A vehicle stalled in the turn lane? AI anticipates that it might start moving again.
The most valuable aspect of AI in automotive applications is that it is constantly learning, and adjusting the rules it uses to navigate the road. Each vehicle makes the information it learns available to the rest of the fleet. The result is a virtual neural network of self-driving vehicles that learn as they go.
Whether autonomous cars shuffle us around with an AI driver, or if driver assist merely lends a helping hand, connected vehicles need gobs of data to do their thing. The application of Artificial Intelligence cloud platforms ensure that data is available when needed.
While a number of automakers and automotive startups are working on AI applications for the automotive industry, two companies lead the pack in the development of truly driverless cars — Google and Tesla.
Data Monitoring
Unlike conventional vehicles, connected vehicles can do more than alert us with check-engine lights, oil lights, and low-battery indicators. AI monitors hundreds of sensors and is able to detect problems before they affect vehicle operation.
By monitoring thousands of data points per second, AI can spot minute changes that may indicate a pending component failure — often long before the failure could leave you stranded.
