Autonomous Vehicles

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Nowadays, AI is quickly surrounding us and affecting our daily lives. Its being used in products and services that we use on a daily basis like predicting texts, voice recognition and image recognition.

Self driving cars and mode of operation

They are a combination of AI, sensors, cameras and radars to operate without human intervention from a specific location to a predetermined destination using set of preconceived parameters.

Principle of Self driving cars is that system is developed infused with Machine Learning, Neural networks and Image recognition systems.

By using Neural networks: AI systems are able to identify patterns like traffic lights, street signs, curbs, pedestrians and other objects from imaging systems. This data is then fed to Machine Learning algorithms and collated to create parameters within car operates.

PYTHON, C++, LINUX experience are a must for developing AV's

ML's -> operational data collected from entire autonomous fleet and creating solution depending on pre-set parameters.

3 commonly used data sets in AI development:

Training set: train algorithms to understand different concepts like neural networks well as learning and producing results

Test set: determined how well algorithm is being trained using training data set

Validation set: select final algorithm model

Computer vision helps AV's in several ways:

3D mapping: