Sensor Fusion Is an Important Step for Autonomous Vehicles; a Quick Overview

 

Sensor Fusion

Sensor fusion is a software that combines data from different sensors to improve application and system performance. Increasing demand from various end-use industries for different applications, such as consumer electronics, military, industrial, healthcare, home automation, and automotive among others, has boosted the demand of sensor fusion to a great extent in the global market. Smartphone is a common example of sensor fusion implementation.

Sensor fusion is an important process in the modern world, where people constantly need to make sure that their systems work or are able to function in the event of a malfunction. For example, use of radar for traffic control, infrared for military operations, radio waves for communication, etc. The science behind sensor fusion is somewhat difficult, though well researched, because it involves many mathematical and scientific principles. The first part of the science behind sensor fusion is in sorting through all the different sources of data, i.e., radar, radio, etc.

Next the algorithm, which takes this data and breaks it down into the different sources of data, i.e., speed, angle, frequency, etc., then processes the data to form an overall picture of the speed of a vehicle in question. Because of the complicated nature of this process, most modern vehicles come equipped with their own on-board computers which perform the bulk of the processing needed to sort through all the sensors, fuse them, and create a meaningful report. Sensor fusion takes the idea of combining different sensors and machine knowledge and makes it work to provide decision making benefits while minimizing the uncertainty of human error.

Automotive sensor fusion depends on the correct sensor combination. This software enables auto calibration, enables gesture detection, enhances context awareness, and improves accuracy. Advance driver assistance systems (ADAS) is the outcome of automotive sensor fusion. Thus, car makers increasingly adopting this technology to boost their growth in the fast-growing ADAS and automated driving market. Sensor fusion bring inputs from multiple radars, LiDAR, and cameras to form a single model or image of the environment around a vehicle.

The rising demand for electric and autonomous vehicles is increasing the demand for fusion sensors in the automotive sector. For instance, Ford Motor, the United States-based automaker, plans to invest US$ 11 billion in electric vehicles by 2022 and have 40 hybrid and fully electric vehicles in its model lineup.


Location: India

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