Various factors influence the speed data accuracy:
1. classification
2. the assumption that every car has the same length.
Always have a look at a larger sample of data and consult the V85, which is one of the best indicators of the typical speed.
There are various factors that influence the accuracy of the speed histogram that is displayed for a given road segment.
First of all, a prerequisite to accurate speeds is that the classification is accurate. In most cases this is not an issue, but if you see that your Telraam measures a very different split for, e.g., cars and cyclists, then the derived speed histogram will be affected by the misclassified cyclists, as their incorrectly (using a wrong assumed object length) derived speed will be mixed together with the speeds of objects that are actually cars.
Furthermore some scatter is expected even if every car passed in front of the Telraam at an exact 30 km/h pace, as we assume each car has the same length, which is of course not the case in reality. There are a few minis, and some big SUVs, that will be further away from the average size. In this case smaller (shorter) than average cars will be “measured” faster than 30 km/h, and larger (longer) than average cars will be “measured” slower.
This is also the reason why one should not take speed data from a small sample of cars very seriously, as this effect gets less visible when looking at a large (and therefore more average) sample of cars.
And finally, there are some outliers - artefacts - in the data, which can show up as unrealistically high (or low) measurement points in the speed histograms, so if you see a few (%) cars driving 70+ km/h in a 20 km/h zone, that does not mean that there were people actually racing in that street.
To get the most precise idea about the speeds measured in a given street, always look at a large sample of data (so not a single hour with very low traffic levels), and consult the V85 value which is one of the best indicators of the typical speeds, as it is practically unaffected by these spurious outliers.