The Future of Automobiles: Autonomous Vehicles and More

Recently, we discussed how artificial intelligence (AI) is used in the healthcare and manufacturing industries. In doing so, we explored modern hospitals along with the Tesla Gigafactory. In this series, however, we are pulling out of the Gigafactory in our brand-new semi-autonomous Tesla for a quality assurance test and to review all applications of AI in automobiles. Additionally, we will later cover all AI transport applications including those over rails, in the skies, and on the seas. Let’s discuss how AI is applied to every aspect of the transportation industry starting with autonomous vehicles.

AI Applications

AI is already revolutionizing the transportation industry, from manufacturing and vehicle safety to security and route optimization, all the way up to fully automated driving. It is also used to move goods more efficiently by optimizing load shedding and vehicle sharing. In these different applications, AI comes in many forms. In manufacturing, AI software is more so represented as physical cobots.

Cobot for industrial automation. Used to manufacture autonomous vehicles.

Whereas in the transportation industry AI is used in applications for positioning, autopilot, traffic management, and more. This said, what constitutes AI is the software coding behind the machine it operates.

Self-Driving Autonomous Vehicles

Advancements in autonomous vehicles (AV) have been amazing. Having cars, trucks, and buses that will drive themselves and even avoid accidents is a dream come true. Autonomous vehicles are an idea that immerged straight out of the Jetsons. Now, this technology is not only possible but is delivered at a consumer level.

Machine Learning In Autonomous Vehicles

Machine learning programs in self-driving can learn about an individual and their vehicle over time, adapting to their habits. That data can be uploaded from one vehicle to another allowing AI to continue advancing. Using the internet of things (IoT), a shared wireless data network, AI can exchange information across cobots and software applications alike to exponentially culminate a database of knowledge. The more AI learns the easier AI can learn. Advancements will lead to smarter, safer, and more efficient vehicles. Some are wary to place their lives in the mechanical hands of artificial intelligence, however, self-driving vehicles are much safer because they negate risk from the human factor.

Autonomous Vehicle Safety

Most accidents occur due to some form of human error. Autonomous vehicles’ AI cannot become distracted, will not speed, and cannot drive while intoxicated. Furthermore, current semi-automated vehicles like Tesla’s allow the driver to take control of the vehicle simply by grabbing the wheel. This allows the driver to relax while the autopilot is active. But if anything occurs that the AI did not predict the driver can take control at a moment’s notice. One stipulation is ensuring the driver remains focused while autopilot is active. This, however, is entirely in the hands of the driver. One solution could be to activate auditory notices as certain environmental aspects change. Such could include other vehicles that have gotten closer, vehicles in the blind spot, variations in the road, traffic ahead, and so on.

But let’s take a second to ask ourselves what runs the AI within these vehicles. A microchip of course! And a highly advanced one at that. Up Next; Tesla’s new D1 AI microchip.

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