When you go out onto the road, you see cars all around you. You are stuck in traffic, with thousands of cars behind you and in front of you. However, you see a person in a Tesla driving slowly past you, without touching his hands on the wheel, and you go “I wish my car did that”. He browses his phone, while the car moves forward and takes him to his destination. How does the car drive, without using your hands, or your feet? With the power of AI or Artificial Intelligence.

AI technology is not new, but it hasn’t been used in commercial based applications, until recently. Ai is now prevalent in cars, smart-home devices (Alexa, Nest, Google Home, Samsung QLED TV with ThinQ AI). The most fascinating aspect of AI is how it is being used to change the future of driving.

But how do they work? Well, self-driving cars use GPS, an internally created navigation system, and sensors to build a three-dimensional image of the environment. Data is used to make calculations on the distance, and to accurately predict the position the car is at for any given time.

Laser rangefinders which emit laser beams help the self-driving car determine what type of environment it’s currently in. They scan the environment using laser beams which calculates the distance to objects that are nearby. It calculates the time it takes for a beam to travel from and to the object.

Another important feature of self-driving cars is obstacle avoidance. Cars have an internal library, where obstacles are categorized based on how well the obstacle is a match based on a pre-determined shape and motion descriptions. For example, if a bike is traveling at 15 mph, as compared to 40 mph, the car will classify the object like a bicycle because of its low speed. So cars know based on how fast an object is traveling, what the object might turn out to be.

Lastly, cars have something called path-planning. Algorithms are used to determine the long-range plan for cars to follow, while constantly changing the short-range plan for the vehicle. Long-range plans include the destination from Point A to Point B, but the short-range plan includes methods to turn right or go forward. The short-range plan is based on how well the car is able to perform certain tasks. The plan removes any path that comes into contact with certain obstacles. If a car is not able to complete a short-range plan, based on the path given, the path is removed completely.

The paths that are remaining will be evaluated based on the speed, and the time it takes to complete the path. A set of short-range plans would be combined into a long-range plan.

Everything from mapping, to obstacle avoidance, and path planning is repeated until the self-driving car reaches its destination.

Here is an example of a code snippet for a self-driving car algorithm:

This code snippet is very complex, but programs such as TensorFlow and Keras are heavily used in the area of machine learning, deep learning, and AI. These programs allow you to create models or simulations which can run a variety of data sets to find and process images based on certain inputs given to the model.

Self-driving cars and AI are the future of transportation. However, we still have a long way to go before every person in the world has their own self-driving car. This would reduce the number of accidents caused by humans around the world. People with certain disabilities, for example, blindness, can use self-driving vehicles to get to their destinations safely and efficiently. Self-driving cars would reduce the number of emissions being produced because it would reduce the amount of traffic caused by accidents, which could be easily avoided in the first place. Cars provide us a way to see new places and meet new people. Having a self-driving car would give people access to new experiences, and would allow everyone to travel safely.

AI and Self Driving Cars- The Future of Transportation was originally published in AR/VR Journey: Augmented & Virtual Reality Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.