Self Driving Vehicles :
Driverless cars or Self Driving Vehicles, unmanned ground vehicle, an autonomous drone, these are all examples of driver-less vehicles. These are basically normal vehicles with some abnormal features or some magic running under their hood. This magic consists GPS and of a bunch of sensors and some algorithms running side-by-side (machine learning algorithms to be exact). Now, what are these sensors? And how do they work? These are various optical sensors somewhat similar to a camera, these sensors continuously scan the road or the path of our driver-less vehicle or various objects such as other vehicles, traffic signs, lane markings and people on the road similar to a modern camera face-detection that continuously scan the scene and looks for potential faces in it, and then notifies those faces by drawing a box around them. Similarly, these optical sensors in a self-driving or a driver-less vehicle looks for other vehicles & stuff and then feeds all the information that it has received or scanned to an algorithm which takes over the control of the vehicle, processes the information received from all the sensors and then respond accordingly, and it does all this stuff in real time, which means, there is almost a negligible gap between receiving the information and responding to it.
Now, since we have brought up the term ‘machine learning’, let’s discuss a bit about it. Machine learning is a technique (or a combination of number of algorithms) which build upon the human brain and its capability to learn things. Similarly, machine learning is a technique/algorithm where a device(computer) can learn from its past experience and use it in future scenarios where it might be needed. Sometimes it is also referred to as ‘artificial intelligence’ since, all we are trying to do is make the computer intelligent, to respond on its without the need of a human inter-action. To understand intelligence better, we have to first learn about its predecessors like data and information. Data can simply be termed as raw facts and figures; data alone is meaningless. Data is then worked up (processed and refined, or summarized) to form information. Therefore, we can say that, information is meaningful data. Then comes knowledge, which is a collection of information stored for future referencing. And finally when this stored information (knowledge) is verified then it leads to the formation intelligence. The best way to understand what intelligence is, is to go through the phase,” learning from your mistakes”. When we commit a mistake, we tend to remember it and whenever the same circumstances arise we recall it and avoid it repeat it, learning from our past experience. This is called intelligence. And with time our intelligence increases or it grows. And this basically everything that these self-driving vehicles do, they gather data, process it, collect it, verify it, and finally use it.
And since, these vehicles work on machine learning, therefore, they will mke make mistakes like driving on the wrong side, over-speeding, and many more that humans often make. Which makes them much safer as compared to a normal vehicle driven by a human. These can be considered as the future for all the vehicles.
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