It seems that the Piccadilly line is only just getting back to normal after a problem with flat spots on the wheels of 50% of the trains: [TfL Link].
Looking at the data for the number of trains running, this seems to stem from around the 24th November (Thursday) when the numbers started to drop off. Analysing this data is problematic because of the noise inherent in the data collection process and the need to take weekends into account. There is also the launch of the Night Tube on the Piccadilly line which happened on Friday 16th December.
Plotting the total number of tubes running over a 24 hour period as a moving average makes things a bit simpler:
The data break is immediately evident on the 8th and 9th December, but the numbers can be seen to be dropping from the 23rd to the 28th. Then the 5th, 6th and 7th of December (Mon to Wed) just before the data break is particularly bad. It’s interesting to note that there were more tubes running on the 10th and 11th of December (Sat/Sun) than there were running on the 5th and 6th (Mon/Tue), which seems to be the worst period for the Piccadilly Line.
While this is quite an interesting exercise, the real value of this type of analysis is in the effect it has on the commuter. Spacing between tubes of 15 minutes were reported and sections of the line had no service at all. What I need to develop now is a way of generating these spatial analytics automatically from the data as we collect it.
Just to follow up on the last post about the launch of the “Night Tube”, the service launched on the Jubilee Line last Friday. There are now close to 40 tubes running over night at the weekend on the Central, Victoria and Jubilee lines. The chart above shows the number of tubes running on Thursday 6th October through to 23:57 on Sunday night. The morning and evening peak rush hours are evident for Thursday and Friday, then the first Jubilee Line night services can be seen in the trough between Friday and Saturday.
The interesting thing to do now would be to run a public transport accessibility analysis using the real-time running data to see which parts of the city are now more connected. As today is the second day of the Southern Rail strike, that might make another interesting subject. Using the Census travel to work data we could forecast the areas where people are going to be late for work because of transport failures. That could potentially give a measure of what effect any strikes, or even just “congestion” generally, is having on London.
On a technical level, one thing which is now becoming apparent is that the number of drop-outs from the API has increased. It used to be that there would be a few per day on the Northern Line (biggest data), but now they seem to be occurring randomly across all the lines. The CASA API has been collecting data since the London Olympics in 2012, so it’s long overdue for some maintenance.