Tesla could beat Waymo in the race to self-driving future

Autonomous driving technology is currently in its infancy, but evolving rapidly. More companies are testing autonomous vehicles than ever. Tesla and Waymo are two prominent names competing to capitalize on the opportunity of becoming the industry leader in the self-driving future, but employ different technologies to achieve those goals.

One of the major difference between Tesla and Waymo is the sensors they use for self-driving. Tesla cars relies on computer vision and Waymo uses LiDAR.

LiDAR stands for Light Detection and Ranging, which is a system that uses lasers for detection. There are sensors on-board that detects the reflected laser light and measures the distance to a target.

A computer vision system uses cameras to capture the environment and processes images in real-time through a machine learning neural network.

Advantages of Computer Vision

Low Cost

The main benefit of a camera based system is that it costs a lot less to install cameras on a car and it can be trained through computer learning to recognize objects. With this system you can drop the car in an unfamiliar environment and it could still find its way.

Can read traffic signs

Another benefit of a camera based system allows the car to read signs. The current road infrastructure is set up for human vision and the camera system is based on this vision. It read signs in real-time and respond accordingly, like a human would.

Looks like a regular car

There are no odd looking domes popping out of the body of a car in camera based setup. The built-in cameras allows for a very sleek design which preserves the aesthetics of the car.

Maybe the only disadvantage of this system is that it takes a lot more machine learning and software development, requiring a lot more computing power.

Read more: https://www.wheelsjoint.com/tesla-could-beat-waymo-in-the-race-to-self-driving-future/