How Artificial Intelligence Drives Driverless Cars

Autonomous cars are some of the most talked-about and highly anticipated technologies today. Inside every one of these vehicles is another technology that gets a lot of publicity — AI. Without artificial intelligence, driverless cars wouldn’t be possible.

Many automated processes today use AI, from your YouTube suggestions to your phone’s predictive text. Self-driving cars are no exception but rely even more on this technology. In most places, AI is a convenience, but in driverless vehicles, it’s a necessity.

Why is artificial intelligence so crucial for driverless cars, and how does it work? Here’s a closer look.

Open Roads Need Intelligent Drivers

Driverless vehicles have been a reality for a while now without needing or using AI. There are 64 automated train lines in 42 cities globally, like Singapore’s MRT system. Letting self-driving cars onto crowded streets is more complicated than running a driverless railway, though.

Following a pre-determined path from point A to point B is straightforward enough for a machine. For instance, a freight train was able to travel 48 miles in 2019 because of AI. When you add a road full of other drivers and pedestrians to the equation, though, things get tricky. Driverless cars need to recognize and respond to moving obstacles, which is where AI comes in.

Self-driving cars use a system of cameras and sensors that feed information to AI software. This software then analyzes that data to understand the world around it, like where other cars are going or how close they are. It can then make driving decisions like braking and turning.

Why Artificial Intelligence Driverless Cars Need Training

AI programs, like people, get better at their job the more they learn. Since roads can be so dangerous, artificial intelligence in driverless cars needs to learn a lot. The more these AI systems encounter, the better they’ll be at recognizing and responding to unexpected situations.

Self-driving car companies go about this in two ways — simulated driving and road tests. They need a lot of both, too, since driving involves so many unique scenarios and variables. By 2018, Waymo’s driverless vehicles had already driven 6 million miles on roads and 5 billion in simulations.

As they drive, these vehicles collect data about how other drivers tend to react in different situations. They also need to keep up with road changes like new construction. With that information, they can start to predict how other cars on the road might act. When they can do that accurately and consistently, they’ll be safe.

Roadblocks with Artificial Intelligence Driverless Cars

People have been talking about the near future of self-driving cars for years now. You’ve probably also noticed that there aren’t any fully autonomous cars on the market yet. That’s because developing the AI in these vehicles has proved a challenging task.

First, it’ll take a while to train AI to anticipate the billions of possible traffic scenarios they could encounter. Even if they can make smart decisions, those depend on the accuracy of their sensors. The sensors on self-driving cars have to be almost flawless in every condition to be safe.

That level of technology is still a ways away. A self-driving Tesla once mistook a truck’s reflection for the sky, causing a crash. Machine vision isn’t at the level it needs to be for driverless car AI to work well.

The Future of Artificial Intelligence Driverless Cars

Artificial intelligence in driverless cars is imperfect right now, but it has lots of potential. With more training and technological advancement, they could become as good or better drivers than humans. When that happens, self-driving vehicles can finally populate our roads.

Who knows, maybe AI will power the roads of tomorrow. When the roads are full of self-driving cars, they’ll be far safer than they are today. To get to that point, though, AI technology has to improve. The road safety of the future depends on artificial intelligence.