Last Updated on by Kumar Raja

How Data Science is Behind Autonomous Self-Driving Cars?

Back in the late ‘90s, autonomous driverless vehicles could just be seen in the science fiction movies and they seem to be far from the reality. In the past five years, there’s a significant development in the field of technology and driver less cars have taken shape from just being an idea to an inevitable innovation in the current age of Big Data. Autonomous driverless vehicles can be seen in the streets of California, Michigan, and London and this area of research is estimated to generate $7 trillion revenue to the global economy.

Data Science is one of the crucial technologies behind driverless vehicles. For autonomous vehicles to operate efficiently, they need to analyze data in real-time and this could only be possible with the application of Data Science.  By analyzing the data collected from the sensors, Data Science will help in better navigation of the autonomous vehicles. There’s no denial of the fact that Data Science has become a major game changing technology with several unique applications that are making human more comfortable and productive at less time. You can know in-depth about Data Science and decode the technology with our Data Science Training program.

Application of Data Science in Autonomous Vehicles:

An autonomous driverless vehicle has three major components namely

  • Sensors
  • Processors
  • Actuators
  • Vehicle to Vehicle Cloud Communication

Data Science helps in analyzing the Images and information gleaned from sensors and gives the system command via actuators. Based on this data, system controls physical actions like breaking and steering.

Data Science can also help in localisation. It analyzes the data that is collected from specific maps and sensors and it helps to track the location of your car. By making use of predictive analysis, the system can precisely anticipate the behavior of objects surrounding the vehicle. By analyzing the real-time data, Data Science will also help the system in planning the best routes to a destination.

Image Classification and Image Localisation are two different techniques in the process of object identification and for this Convolutional Neural Networks are used for performing convolutional operations on the images received from the sensors. There also many data-driven advanced algorithms in Data Science that will be used to convert real driving experiences into programmable information.

Conclusion:

The applications of autonomous vehicles are quite fascinating and the success rate of these systems relies heavily on the use of right data and right data processing systems i.e., Data Science.

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