Technology in Autonomous Vehicles

Technology in Autonomous Vehicles

Introduction

Automakers are now building self-driving vehicles, but they’re not the only ones who can use these technologies. Here’s what you need to know about how cars get around themselves.

LiDAR

LiDAR is a laser-based detection system that uses lasers to measure the distance to objects. It’s used in autonomous cars, drones and robots. LiDAR technology has been around since the 1960s, but it wasn’t until recently that it became affordable enough for use in consumer products like automobiles.

The most common type of LiDAR today is “time-of-flight” (TOF), which sends out pulses of infrared light at targets and measures how long they take before returning back to their source based on their reflection time; this allows them to accurately determine distances within centimeters with each pulse sent out

Radar

Radar is a type of sensor that uses radio waves to detect objects. It’s used to detect objects in the distance, which is why it’s so useful for autonomous vehicles. Radar can be used for obstacle avoidance and has a very high resolution (meaning it can detect very small details). Radar also works well in fog, rain, snow and other weather conditions where visibility may be poor or limited because it doesn’t rely on light from the sun like cameras do.

Computer vision

Computer vision is the process of using computers to recognize and understand images. It is a key technology for autonomous vehicles, as it can be used to identify objects in images, detect their position and track their movement.

There are many types of computer vision:

  • Image classification – identifying whether an image contains certain objects (e.g., “is this picture showing a dog?”). You may also see this referred to as object recognition or object detection.
  • Scene understanding – determining what’s going on in an image based on its content (e.g., “this person is standing at an intersection”).

GPS satellite navigation

GPS is used to track the location of the vehicle, determine its speed and direction of travel, and determine its route taken. The technology allows vehicles to be tracked by their owners or others who may be interested in knowing where they are at any given moment. GPS works by using satellites orbiting Earth which communicate with ground stations, then transmit signals back down to earth using radio waves that can be picked up by receivers like those found in smartphones or cars equipped with satellite navigation systems (GPS).

Intel RealSense cameras, sensors and more

Intel RealSense cameras are used in autonomous vehicles. These cameras can see in 3D, they can see in the dark and they can even see through fog and dust.

These technologies help make autonomous vehicles safer.

  • LiDAR and radar are two technologies that help autonomous vehicles avoid obstacles and detect nearby vehicles.
  • Computer vision helps autonomous vehicles detect pedestrians, cyclists and other vehicles.
  • GPS satellite navigation helps locate the vehicle’s position on a map so it can be compared with other objects around it to determine what needs to be avoided or stopped for at any given point in time when driving in traffic.
  • Intel RealSense cameras, sensors and more help with object detection by providing depth information about what’s going on around you as well as helping determine where objects are relative to each other (e.g., detecting an object behind another).

Conclusion

Autonomous vehicles are becoming a reality, but there’s still work to be done. Technology has made huge strides in recent years, but it will take time before these vehicles can be deployed on our roads safely. We hope this article has given you a better understanding of some of the key technologies involved in autonomous car development and how they work together to create safer vehicles for everyone.