| Re: Putting a number on the effect on passengers of cancellations Posted by John D at 17:47, 14th May 2025 |     |
Cancellations seem to still be a big thing on GWR
Latest figures show overall 3.68% cancelled
Reliability isn't great either, only 66.03% on time
0.31% are short formed (below the DfT agreed minimum)
https://www.gwr.com/-/media/gwr-sc-website/files/about-gwr/what-you-can-expect/our-performance/GWR-Periodic-Web-Report-P2513.pdf
So anyone with return journeys, each with change of train (4 trains in total) has high chance of not arriving on time (if train actually runs)
| Re: Putting a number on the effect on passengers of cancellations Posted by grahame at 07:09, 11th May 2025 | |
It seems logical to me to include catchment population and scheduled service frequency amongst the factors in measuring the effect of cancellations on passengers as well as the cancelation rate, but my initial algorithm is quite a basic one. I have chosen population rather than journey numbers because journey numbers are heavily influenced by the very lack of an appropriate (reliable and frequent enough) service.
Place,population,gap,cancellation,factor
Bath Spa,100000,12,3,3600000
Bradford-on-Avon,10000,20,3,600000
Chippenham,40000,30,3,3600000
Frome,25000,50,3,3750000
Melksham,25000,120,6,18000000
Salisbury,45000,30,2,2700000
Swindon,250000,12,4,12000000
Tisbury,2500,60,1,150000
Trowbridge,40000,20,3,2400000
Warminster,25000,45,3,3375000
Yeovil Pen Mill,50000,75,3,11250000
| Putting a number on the effect on passengers of cancellations Posted by grahame at 14:59, 10th May 2025 | |
There's never been an obvious measure that I've seen to compare the effect of service cancellations on passengers. Which is a shame, because passenger trains are provided (or are supposed to be) for the people who use them - or could use them - and who live near the stations.
I remember a web site someehere to the south of where I live that use to shout that trains were cancelled for OPERATIONAL CONVENIENCE ... and clearly there is no measure there.
So what have I tried?
* The population within the station catchment area multipled it by
* The percentage of short notice cancellations over the past 12 weeks and multiplied that by
* The average daytime interval between trains in the most frequent direction
So for example - Frome -
Catchment area population - 25000
Average gap between trains in the same direction on the major service - 50
Cancellation Rate - 3 (percent)
Multiply together - 3,750,000 - and the lower the figure, the better
Trowbridge:
Average gap between trains in the same direction on the major service - 20
Cancellation Rate - 3 (percent)
Catchment area population - 40000
Multiply together - 2,400,000
Salisbury:
Average gap between trains in the same direction on the major service - 30
Cancellation Rate - 2 (percent)
Catchment area population - 45000
Multiply together - 2,700,000
Tisbury:
Average gap between trains in the same direction on the major service - 60
Cancellation Rate - 1 (percent)
Catchment area population - 2500
Multiply together - 150,000
This is clearly not going to work particularly well for stations which are primarily destinations - the population of Looe, for example, is low and catchment is a poor choice. Similarly, where stations are predomianty city stations with long distance traffic and rail does not form so much of a short distance facility such as Plymouth they will be outside this symplistic envelope - but what do others think of the methodology before I share other figure in our area?
