How do Self Driving Cars “See?” – Starweaver
AI self driving cars

AI Self Driving Cars

Google, Audi, Toyota, University of Oxford, Mercedes, Bosch, Nissan are working on a technology that can transform the automobile industry. No, it isn’t a robot or a concept car. They’re working on deep learning and reinforcement learning to build AI self driving cars.

Furthermore, many prototypes are already running on the streets. So far, they’re very successful in terms of low collision rates and sensing directions.

According to statistics, more than half of all fleet owners believe that they’ll get artificial intelligence in cars within 20 years. All in all, this domain has a very promising future. But have you ever think about how these cars work? Let us delve into this topic.

Working of an AI Self Driving Car

It is obvious that vision is the most crucial aspect in AI self driving cars. An autonomous vehicle relies on a camera as well as radar and LIDAR sensors. The primary task of a camera is to detect various objects with the help of object recognition models. Even though the camera can detect objects, it can’t detect depth. And that is why we need radar and LIDAR sensors.

Object Detection : AI self driving cars

In most cases, cameras use convolutional neural networks for detecting objects. In layman terms, a computer processes millions of images containing various objects and trains the model. After that, the camera uses this trained model for detecting humans, sign-boards, other vehicles, turns, etc.

Sensing the Depth

Besides cameras, most AI self driving cars use a radar to determine the distance from objects. Furthermore, radars compensate for cameras during dark. Radars also help in tracing various objects from different angles. This decreases the chances of collisions to a very high extent.

However, a radar is unable to point out the differences between different vehicles. This is where LIDAR resolves the issue.

Precise Measurements

Although camera and radar complete most of the work, LIDAR provides additional accuracy. LIDAR uses pulsing lasers to perform precise measurements. Instead of sound (radar), lasers perform the same tasks at a much higher speed.

Moreover, the wavelength also plays a vital role in accuracy. Just like radar, LIDAR can work in areas with lower illumination. It creates a 3D map of the surroundings, which helps the car to navigate with ease while avoiding obstacles.

What happens with Sensor Data?

After these sensors collect the data, computers and GPUs process them. Various models and scripts combine this data onto a computer. The computer takes these inputs and treats them as individual features. Thus, speed, distance, depth, possible options etc. help in building a reinforcement learning model. Most organizations use this concept to implement artificial intelligence in cars.

Our Take on the Topic

Many experts assert that this decade will be a pivotal time for technology. Many industries are going to witness dramatic changes. Transportation industry will observe a similar trend. Companies will develop highly accurate AI self driving cars which will hit the streets very soon. With the passing of each day, this concept is getting better and better.

Furthermore, with the integration of LIDAR in the existing system, we can expect that this industry will bloom rapidly. You might as well see a self-driving robot bringing groceries to your doorstep in the future. The future is bright, and self driving cars is just the beginning of it.


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