F1 Data Junkie – Lap Elevation Data

Fans of cycling will be more than familiar with the idea of a profile map that details the elevation above sea level along a particular race stage.

Cycling map (Toue de France stage) profile/elevation map

(See also More Thoughts on Data Driven Storytelling for several more ideas on representing geospatial time series augmented by other sensor data.)

Although F1 circuit maps are provided by the FIA for each Formula One Grand Prix, they don’t give elevation data. Nor did a quick web search turn up any elevation maps.

In several previous posts on the topic of visualising F1 telemetry data I’ve plotted various map views, so I wondered whether I could generate elevation maps too… and it appears I can, using the Google elevation API:

F1 cct elevation data

The x-axis is distance round the lap, so if data from multiple laps is captured, we can start to get a more complete set of altitude data round the circuit.

Simply pass the API one or more sets of latitude/longitude co-ordinates, and I can get back elevation data. So for example, the above data (captured from the Vodafone Mclaren Live website) shows a lap by Jenson Button of the Malaysia circuit earlier this year.

So here’s what I’m thinking: how about a set of telemetric circuit guides derived from the telemetry data?

Here’s what we’d be competing with – the FIA circuit maps:

FIA Malaysia circuit map

To do this, I think it would make sense to use data captured across the whole of a race, putting it into meter wide sLap bins (or maybe moving average bins 3 meters wide?) and then recording for each bin:

– the average latitude and longitude, to try to generate some idea of racing line;
– the most common (mode) gear setting
– the most common “g-force” values to show directional forces on the car; (or maybe we could derive an angle of travel based on current and next, or current and previous locations?);
– the average (mean) speed (maybe with outliers removed?)
– some average of brake and throttle values?

As to how to display the map – the use of Google elevation data requires that a Google map is also displayed, so using something like this map/scatterplot mashup technique might be appropriate?

Having good (average) resolution data for lat/long around the circuit as a whole also means we should be able to generate a reasonable KML tour to view a lap animation in Google Earth (e.g. reusing this Google Earth path/tour simulator (Silverstone data, F1 car kmz model)).

The only thing is – I can’t get myself motivated to hacking the code required to do this today:-(

PS hmmm… seems like racing line data is avaliable on the Racecar Enginerring website (e.g. Formula 1 2010: Round 5 Barcelona tech data). There’s also this interesting article on GPS data – it’s just a shame that the resolution we get on a per lap basis from the Mclaren site is at too poor a resolution (one sample per second) to be able to do anything really interesting with it…

Author: Tony Hirst

I'm a Senior Lecturer at The Open University, with an interest in #opendata policy and practice, as well as general web tinkering...

4 thoughts on “F1 Data Junkie – Lap Elevation Data”

  1. Cool.

    A simulator called iRacing prides itself in the most accurate modelling of the tracks by using a process where they laser scan a track. The only problem is that it takes a while and is very expensive.

    If we could link up the GPS and elevation data in the way you propose it could emerge as a very cost-effective alternative, as you have approximately 600km of data to process that was almost free to obtain.

    For example, teams like Red Bull use rFactor Pro in their simulators, and it might be a great way to check the circuit model they have against this model to see which comes out more accurate?

  2. I guess the problem is that elevation is a much bigger factor in a bike race. One looks at those huge Category 1 climbs and is in awe of the riders heaving up it. They are big mountains, and it’s human power getting them up and down them.

    Contrast this with F1 data, and, well, it’s all a bit underwhelming. The elevation changes aren’t huge, and, well, with an engine as big and powerful as those, I don’t really care if there’s a steep bit of the track. If you could prove to me that elevation is of interest in F1, then I’m keen, but otherwise, I’d rather you stick to doing the other F1 data mashups – they’re much more interesting.


  3. The elevation is of importance because it tells you why the cars don’t accelerate so well or why they corner so quickly. To illustrate the example, think about Eau Rouge at Spa. The elevation change is massive and is directly responsible for why the cars can get through there so quickly. It’s also responsible for some of the accidents. In my experience, elevation changes are also one of the most important factors in how enjoyable a track is to drive. Again, drivers love Spa (very hilly) and the Nurburgring Nordschleife (even hillier), probably because of the way the elevation changes affect how the corners are taken and how the driver feels going through them.

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