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For the extra-super simple version that won't work in real life, you could use the template matching function. You store all the signs you want to recognise into your hard drive, you load it, and keep searching for those.
For a more realistic solution in real world, I suggest you have a look at the Cascade Classifier to identify road sign and then try to interpret them (maybe also on a first approach with the template matching approach). You could also have a look at that book that has a nice chapter on how to optimise the detection of object.
If you have trouble to identify the road sign as they are not parallel to your camera plan, have a look at the homography estimation with this tutorial. It could also be a way to directly identify and/or recognise signs in the road (using the feature descriptors approach).
Keep in mind that this is not an easy task (especially on a RaspPi) and you may have to deal with lot of tricks to make it apprends in your situation. But still, this is a really interesting challenge and you could expect not so bad results with all the OpenCV functionalities!
Enjoy ;-)
