Mobility Matters Extra - The most important dataset in transport planning
Good day my good friend.
This is what we call in the UK ‘a bit of a cold snap.’ Which means countless thousands of litres of fuel spent ‘warming up the car’ before getting in it. Of course, you should clear your windscreen before heading off, but its not good for your engine or fuel consumption. So don’t do it.
If you have any suggestions for interesting news items or bits of research to include in this newsletter, you can email me.
James
The most important statistic in transport just got published
On Friday, the results of the 2021 Census Travel to Work questions were released. I won’t go into detail on the results, apart from to say that there were relatively few places in the UK where the majority of people worked from home, despite the Census being taken during COVID. But this is the most important statistic in transport planning.
Despite the fact that the majority of trips that people take are not for commuting, it is the commuting trip and how we do it that affects how we assess transport schemes. Where we lack good survey data, the origins and destinations of trips are derived from travel to work data. Modal split is the same. Values of travel time are driven by the value of the commute. So, this data is important.
So important, that the Office for National Statistics felt it is necessary to publish a warning about its quality for planning purposes. Such as issues affecting the quality of work from home data “is likely to be concentrated in populations with high rates of furlough. We expect this to be closely connected with characteristics variables such as:
health and age
employment variables including industry and occupation
geographical concentrations of these variables
For this reason, take extra care when interpreting multivariate travel data or data for geographies below “Region”.”
The impacts of this data on how we do our work over the coming 10 years are yet to be fully understood. To what degree do we think that the situation with COVID was so unique that we simply disregard the data? Or adjust it in a way that is considered ‘normal.’ If we know what normal is, and can apply our adjustments to millions of households. Or maybe we see it for what it is - one dataset taken in the middle of a pandemic - and stop relying on it in our analysis and to make decisions.
Graph of the week
In a cost of living crisis, and in a time when we are meant to be trying to get more people on buses, seeing bus fares rising again is…not a good thing. But this has been happening for a long time.
Something else interesting
Maintaining infrastructure is important, but not sexy enough and doesn’t get anywhere near the attention it does. Which leads to emergencies, such as this example of the Brooklyn-Queens Expressway in New York. And its costly, to the tune of $2.2 trillion.