The Machine Learning Behind Self-Driving Cars

Self-driving cars, also known as autonomous cars, are cars that can drive with little or no human effort. An autonomous car is supposed to drive you from one city to another while you are sleeping, relaxing, or doing your business. In this article, I will introduce you to the machine learning behind self-driving cars. 

Self-driving cars have received considerable attention recently, in large part due to the technology boom in machine learning and artificial intelligence. In recent years, machine learning has moved from being forgotten to the largest investment in research and development of many organizations around the world. 

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Simply put, machine learning has given us the ability to automate a lot of manual work that would previously have taken some form of human knowledge or skill. 

In case of self-driving cars, Machine learning is used to give the brain to cars by doing things like automatically detecting people and other cars around the vehicle, with other important tasks like staying in the lane, changing lanes, and following the GPS commands to reach to the final destination with a greater speed and high accuracy. 

So how do self-driving cars work? How can computer scientists, engineers and software developers program computers to make them drive cars? Well, in this article, I will take you to step by step through everything about the Machine Learning behind self-driving cars.

The Levels of Automation in Self-Driving Cars

When talking about self-driving cars, most technical experts refer to levels of automation. The level of automation of self-driving cars refers to the proportion of driving performed by a computer compared to a human. The higher the level, the more driving is performed by a computer. Look at the image below for an illustration.

levels of self-driving cars
  • Level 0: All car features and systems are controlled by humans.
  • Level 1: Minor things like cruise control, automatic braking, or sensing something in the blind spot can be controlled by the computer one at a time.
  • Level 2: The computer can perform two or more automated functions simultaneously, such as throttle and steering. A human is always needed for safe operation and emergency procedures.
  • Level 3: The computer can simultaneously control all critical car operations, including throttle, steer, stop, navigate and park under most conditions. A human driver should always be present in case he is alerted to an emergency.
  • Level 4: The car is fully autonomous, with no need for a human driver, in certain driving scenarios. For example, the car can drive by itself when it is sunny or cloudy, but not when it is snowing and the lanes are covered.
  • Level 5: The car is completely capable of driving autonomously in all situations.

So what level we have reached? Most self-driving cars that we hear about in the news today such as those made by Tesla and Waymo are at level 2. They’re at the level where they can drive fairly well on their own, but a human driver is still required to ensure safe operation of the vehicle.

Machine Learning Behind Self-Driving Cars

Self-driving cars today use a combination of various advanced hardware and software technologies to drive them. A typical autonomous driving system will go through 3 stages to perform its driving.

The three stages that contribute to the machine learning behind self-driving cars are detection, understanding and control.

At the detection stage, cameras and various sensors are used to see all the objects around the car, such as other cars, humans, bicycles and animals. These are the eyes of the car, which constantly see all around it, 360 degrees.

At the stage of understanding, various machine learning algorithms, mainly computer vision, are used to process information from sensors. For example, we could have a computer vision system that processes video from cameras around the car, to detect all the other cars on the road around it.

Such a system would ideally be able to detect where cars are located, what size they are, how fast and in what direction they are moving. In reality, these systems are designed to map the entire environment around the car. All this information will be fed into the self-driving control phase.

In the control phase, the autonomous driving system will process all the information that the computer vision system was able to extract. Based on this information, he will control the car. By knowing the entire surrounding environment, what is around the car and how it changes, the job of the control system is to move the car safely and to its destination.

It activates the brakes if the car in front slows down, changes lanes if it needs to exit, and activates the wipers if it is raining.

The most important concept of machine learning behind self-driving cars is Computer vision. Computer vision is the meat of the autonomous car system. An ideal system will be able to accurately detect and quantify every aspect of the car’s surroundings – moving objects, stationary objects, road signs, street lights – absolutely everything. All of this information is then used to decide how exactly the car should move next.

When We Can See The Machine Learning Behind Self-Driving Cars in Action?

For self-driving cars to be accepted and used by people daily, they have to perform perfectly. As humans, we can forgive another human when he makes a small mistake, but on the other hand, we are aggressively critical when a computer or machine makes a mistake.

Computers are supposed to work, without any errors. They are machines, after all, so the expectations are much higher. We often expect machines to be an order of magnitude or more precise than us. The bar is just a lot higher.

On top of that, we have legal considerations. You can bet your last dollar that new laws and regulations will need to be put in place once autonomous driving is fully underway.

Who will responsible in the event of the accident? Should cars be able to drive faster now since they are autonomous? Do we need to be in the car at all times? These are all questions that need to be answered at some point for self-driving cars to take to the roads in full force at level 5.

Overall, self-driving cars are a big plus for the company. We can expect less pollution, less traffic, more efficiency and safer driving when cars become self-sufficient. Technology is moving in the right direction and will hopefully bring a bright and self-sustaining future.

I hope you liked this article on the Machine Learning behind Self-driving cars. Feel free to ask your valuable questions in the comments section below.

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