OUR DATA
The school run has big impact on London peak time traffic. We've brought together government data sources on the distances pupils travel and London average driving rates to provide more insight.
Our Dashboard
According to our National Travel Survey [NTS] analysis, the average driving rate for a London primary pupil travelling under 1 mile to school is 7%, that driving rate increases to 65% for distances 1-2 miles. The distance pupils have to travel to school is a huge determinant of how they travel. So, we've created a primary school travel model using pupil travel distances and NTS average London driving rates. The dashboard below enables you to explore our model, to better understand school run traffic for primary schools, and work out which school trips are most likely to be made sustainably and which are likely to be driven. You can take a look from a city-wide view, or break it down to Inner or Outer London, borough, ward, school type and even school. Knowing which kind of trips will likely generate the most driving, and the areas and school types where those trips are most prevalent, helps us understand which sustainable school run solutions - walking, scooting, cycling, cargo bikes, public transport or school bus - are needed.
Our discoveries about primary school run
How we modelled the analysis
How can this data help you?
About our Dashboard
What does our dashboard show
The dashboard focuses on London primary pupil travel. We picked primary pupils first, because this is where driving rates in London are highest. We have modelled the distances that pupils are travelling to schools across London, and applied the NTS school driving rates to these distances. We have included independent schools so we can get a full picture, and have modelled their pupils distances, since these aren't disclosed publicly. This provides insight into how primary pupils are most likely to be travelling to their schools throughout London. The information is provided by school, by school type, by ward and by borough, and comparisons are also provided.
We advise all users to review our Methodology tab for a full understanding of modelling assumptions and also our User Guide for help navigating the dashboard insights.
Key Findings
We've summarised the key themes on primary pupil travel that have come through from our model. From pupil travel modes across distances and boroughs and how school types have an impact. Find out about our insights here.
Caveats
These are modelled driving rates subject to the caveats and assumptions listed in our methodology. The model is derived using estimated pupil travel distances and average London school run driving rates. It will therefore not account for factors that will cause variation from average driving rates such as car ownership levels, safe availability of walking & cycling alternatives, accessibility of public transport, congestion zone, school culture etc.
How to use the dashboard
You can click on the green tabs/panels to navigate to different analysis snapshots. On each tab, you can then filter to select a school, school type, ward or borough of interest. This will display the analysis on the tab for that selection. We've also created a User Guide with more detail.
"We're campaigning for healthier, safer streets in our borough"
Select your borough as you go through the tabs/panels. As you navigate through you will be able to understand the length of trips that pupils in your borough are travelling, how many pupils are travelling different trip lengths and which wards and schools in your borough have the highest propensity for school run driving.
"I'm a ward councillor - my residents are always complaining about school run traffic"
"I'm a parent at a school and I really want the area at drop off and pick up to be safer"
Select your ward as you go through the tabs/panels. As you navigate through, you will be able to understand how far pupils are travelling to the schools in your ward, how your ward compares to others and what schools in your ward will have the highest propensity for school run driving. You can also check your neighbouring wards for the same - as there may be a high number of school run car journeys travelling through your ward to access adjacent schools.
Select your school and ward as you go through the tabs/panels. As you navigate through, you will be able to understand how far pupils are travelling to your school and to schools nearby that may also be contributing to traffic levels around your school . If the majority of pupils at a school are travelling under one mile - enabling safe pupil walking and cycling is our recommended solution to reducing school run traffic. If there are high proportions of pupils travelling over 1 mile to a school, additional solutions for these families - cargo bikes that carry children dedicated school buses, and public transport will be necessary.
"We're a bike company - we want to expand into cargo bikes"
Cargo bikes can be helpful for many journeys but they are particularly valuable for trip lengths that children begin to find hard to walk or cycle themselves. On our dashboard, you can use a city-wide view to identify hotspots where pupils are travelling over 1 mile to school.. these would be the places to target.
Why did we create IT?
As we looked for data to understand the school run traffic in our local area better, we found that there was no way to easily understand what was driving (excuse the pun) the school run traffic levels around us and how these impact the wider ward and borough. We knew we needed to continue to promote sustainable travel within our children's schools, but what about neighbouring schools & wards? What was going on there? We had to do a lot of data crunching to be able to take impactful action within our local area, so we created our London primary school travel dashboard to save this step for others.
Any questions?
Please feel free to give us an email at hello@solvetheschoolrun.org.