Autonomous vehicle safety increased by use of multiple sensors in an aggregate technology

Numerous companies are working on autonomous or "driverless", cars that use sensors and software to control, navigate and drive the vehicle. As testing continues and challenges arise, safety, risk, and legal liability are becoming major concerns. The technology must be trusted to ensure that people can buy self-driving vehicles and vote for the government to permit them to use roads.

There are many digital technologies being used, each with its own methods and information. One example is sensor fusion technology, which combines multiple sensors to create a single, more accurate image of the vehicle's exterior environment.

Why Sensor Fusion?

It can be viewed in human terms.

Our bodies have many sensory organs that allow us to perceive the world around us. Despite being the most important sensor in daily life, vision only provides a small amount of information. We must use other sensors to complete our information about the environment, including hearing and smell.

This concept applies to AVs. AVs and advanced driver assist system (ADAS), technology currently use sensors that range from cameras, lidars, radars and sonars. Each sensor has its own benefits, but they also have limited capabilities.

Safety is an essential value in the automotive industry, where people can live their everyday lives. This is especially true for AVs where any mistake could cause further distrust. The ultimate goal of autonomous driving technology for most companies is to create a safer driving environment.

Each sensor can be specialized in the acquisition and analysis of specific information using sensor fusion technology. There are advantages and disadvantages to recognizing the environment around you, but also challenges that can be difficult to overcome.

Cameras can be very useful in classifying pedestrians and vehicles, as well as reading traffic signs and lights. Their abilities can be affected by rain, fog, snow, darkness, and snow. Radar and lidar are able to accurately determine the velocity and position of objects, but they do not have the ability to classify them in detail. Because they cannot classify colors, they can't recognize different road signs.

Sensor Fusion technology removes data distortion and lack by integrating different types of data. Sensor Fusion software algorithms can be used to complement information from multiple sensors and integrate overlapping data. This technology provides more intelligent driving and accurate environmental modeling thanks to its comprehensive data.

Camera plus lidar

Sensor Fusion is an essential technology to ensure safe driving conditions. So why does the automotive industry continue to focus on the combination of camera/lidar among all the sensors?

The completeness of information that can be derived from data from both the camera and lidar is the key to the answer. The sensor and lidar can be combined to create intuitive 3D graphics that are as easy and efficient as creating them on a computer. Lidar detects the 3D shape and coordinates it with 2D information from the camera. This allows Lidar to implement the environment exactly as if it were putting a texture on a 3D object.

Autonomous vehicles for our daily lives

Sensor Fusion is being seen as a promising solution to more precise autonomous driving technology. However, there are still challenges. They must be reliable enough to guarantee human safety and can be used on a variety of vehicle types in order to bring autonomous driving into everyday life.

As mentioned above, more sensors within a vehicle will improve the reliability and accuracy of recognition of the environment. However, more data must be processed, which can lead to expensive hardware that is less efficient. This makes it possible to use AI-based object recognition even on embedded platforms. This allows for lower costs and provides a hardware margin that can be used to implement advanced functions like Sensor Fusion. Sensor Fusion will play an important role in the industry's efforts to bring AVs and advanced ADAS systems to market.