Data Generated from Self-driving cars 2

Self-driving cars are a reality nowadays and soon, they will become all-pervasive to an extent that they will no longer be a surprise on the streets. However, the potential of these vehicles not merely in the state-of-the-art technology, but also the amount of data that the process throws up and how they process it. The vehicles that will be launched can speed up to 35 mph with autonomous driving which is a decent level of autonomous driving. With big names like Volvo getting involved, this is surely signs of greater things to come with huge amount of investment.

It has been coming

The consumers have been hearing about these auto-pilot cars for some time now and they can hardly wait for them to launch. In fact, while the promise is there, the difficulties keep springing up which is precisely why even names like Volvo have taken a cautious, testing step by introducing a short pool of users to their own autonomous driving cars. However, it is not the automobile technology that is the impediment. It is the real-time processing of so much data that makes it all too difficult and companies are trying to manage this issue through various innovations.

Data Generated from Self-driving cars

How much data should they manage?

If data is the problem, then the question that follows automatically is how much data is coming through. The statistics is staggering; 40 TB of data per eight hours of driving is beyond humongous, it is literally data flooding the system both in and out. For a single hour of driving, 4000 GB of data is generated as compared to a maximum 2 GB of data usage that an average person does. This is precisely why new modes of communication technology are required to tackle this problem and make sure that data exchange doesn’t produce a break in the seamless experience.

Maps will never be the same

Apart from the humongous data, there are other things that you need to take care of. One of the most important factors in this regard is the maps which is an absolute necessity when it comes to self-driving cars. Not only has it needed a complicated map that is beyond the Google Maps where each inch is perfected with the correct information but also it has required exact lane information with continuous traffic updates even within 100 meters. In short, maps will eat up a lot of data and new modes of street mapping are required.

The division of data

While there is a lot of data, it’s not all jumbled up and confusing as it may sound. The data coming through can be broadly categorized into three sets. The technical data will consist of hazards, impediments and turns that need to be consistently fed into the system. Societal data or the crowd-sourced data, on the other hand, will consist of traffic reports that come through the reports received from the people on the road. The third set consists of personal data which will have all the locations and what will be the stop time at a location.

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