In the context of autonomous driving, two main stages are typically implemented: an image processing stage and a control stage. The first aims at extracting useful information from the acquired image while the second employs those information to control the vehicle.

As far as concerning the processing stage, semantic segmentation is typically used. The input image is divided in different areas with a specific meaning (road, sky, car etc...). Here is an example of semantic segmentation:

enter image description here

The output of the segmentation stage is very complex. I am trying to understand how this information is typically used in the control stage, and how to use the information on the segmented areas to control the vehicle.

For simplicity, let's just consider a vehicle that has to follow a path.

TL;DR: what are the typical control algorithms for autonomous driving based on semantic segmentation?

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    Can you provide more details and add some sources? – DuttaA Aug 23 at 13:41
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    Thanks. I added two reference videos and I tried to explain my question better – firion Aug 23 at 14:13
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    @DuttaA ,we should always keep this in mind,we arent here to stream video clips,we value time for other global scientific problems. – quintumnia Aug 23 at 18:12
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    @quintumnia well I saw the question was downvotd so I thought the question lacked sources...It is not my field so I really don't know what OP posted on these links – DuttaA Aug 23 at 18:17
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    I don't understand how the new paragraph could be useful in explaining my question better. It does not add any detail... – firion Aug 24 at 6:51

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