05/06/2013 09:35 BST | Updated 04/08/2013 06:12 BST

Ever Wondered How Fast and Far Britain Moves? Here's the Answer

Are you a woman? You are more likely to travel faster than men at the weekend, but will be slower during the week. Are you aged 50-54? It might surprise you to know that you are among the fastest age group in the country. Are you in a boy band? I can't help you there.

But I can explain much much more about travel patterns in the country, because I am managing director at Route, an outdoor research company that has tracked the entire population's movements across four years. And I mean tracked; we give GPS devices to willing participants, collecting information about their speed every second - but also their vibration, and hence the type of transportation. Over 28,300 participants, so far. We can estimate the average speed for someone living in Milton Keynes and Sheffield, Achiltibuie and Westward Ho! This has shown us that travel distances are 14% greater than previously thought.

So it is a fascinating thing to look at the survey in all its glory. With 19 billion data points about the whole country's movements, there are a lot of ways to 'slice the pie'. But here are a few of the first findings emerging about Britain's overall speed - which is entirely new knowledge in the public realm.

The average speed for a Briton - whether they are hopping onto buses and trains, popping to the shop in the car - is slower than you might imagine. We move at 18.2km per hour, the equivalent of 11.3mph. We walk an average of 15km (just over nine miles) in a week, which contributes to our speed. And when you think of the traffic congestion and large amount of local travelling we do, this is less of a shock.

Age groups differ in their speeds, and this is probably due to the availability of cars (or, for 15-17 year olds who travel at an average of 14.34km per hour, the lack thereof)- and the increased pace of life as we grow careers and responsibilities over our lives. So we get increasingly faster, roughly until the age of 55.

I can offer no particular explanation for the fact that Britain travels faster on a Sunday. It certainly debunks the idea of 'Sunday drivers', though that's a fallacy anyway. Are we able to travel more freely because of a lack of commuting flows? Are we legging it to the shops during the limited trading hours? Whatever the reason, Sunday sees Britons travelling at an average of 20.6km per hour. That's 14% faster than weekday travel.

As you might imagine, those of us in work travel faster: an average of 19.6km per hour, compared to 16.8km per hour for those who are unemployed or retired. The picture becomes more detailed, however, if we look at walking speeds- which are very close for these two groups (3.38 and 3.35kmph). So greater speeds by workers are achieved by their vehicular travel. (Don't forget, this is an average- so that could be trains, planes, or automobiles). And workers spend proportionally less time travelling than non-workers compared to their overall distances, getting more mile for their money. Vroom vroom.

By the hour, it seems that we are quicker when going to work than when leaving, as shown by the chart below:


Data can tell you lots of different stories; it depends what question you ask. If we look at overall speeds for the two genders, we find that there is barely any difference- men travel at an average of 18.4km, and women 18.1km per hour. Perhaps we aren't so different after all? Well, that is a different story when we look at the total distances travelled. In a week, women cover 197km and men 288km. The latter figure is nearly a third again of the former.

What I find most fascinating about the things I'm starting to discover is that the travel data confirms what we already knew about our country: that there is a great deal of diversity in behaviour across the regions. We are not all following in one direction. To scratch the surface- Geordies and those from Cardiff are unusual in that they travel faster at weekends than during the week; on the whole, the trend is for the opposite. These data can sing many different tunes.