Estimates of crash rates per bkm

[Robinlovelace]

At Local Authority level

[Robinlovelace]

Double check - results are same as using routes.

[joeytalbot]

This involves getting route network data for commutes from the PCT, assigning each route segment to a London Borough, and calculating the total number of km travelled in each Borough.

This is to be used together with the number of crashes that happened during peak commuter hours.

Finer levels of spatial aggregation will require assigning route segments to individual roads.

[Robinlovelace]

+1 to doing it at the simple borough level first. Links to #14 which I also plan to do at the borrough level first which means we could get an estimate not only of relative risk but also change in risk over time for each borrough. Comparing that with different amounts of infra will be really interesting and could pave the way towards scenarios of change resulting from new interventions in other areas of the country.

[joeytalbot]

Here are the results, using data for crashes during the morning peak (07:00 <= time < 10:00) in 2011 only. These are for all cycle casualties, including slight injuries.

If I restrict it to KSI only, the number of casualties is very low and in some boroughs there are 0 casualties. To avoid this we will probably need to use crash data from multiple years, but cycling levels are changing so the relationship with 2011 census data will be weaker.

[Robinlovelace]

Woa, this is very cool! I think using a 5 year window, 2009:2013 would help reduce noise in KSI rates. Is that KSI or does it also include slights? Great work in any case.

[joeytalbot]

This is KSI with a 5 year window.

[Robinlovelace]

Impressive! Is that all casualties or just KSIs?

[joeytalbot]

The outer boroughs where km_cycled is low consistently have more casualties per bkm. Waltham Forest looks like a great case study, as it has one of the highest casualty rates, and hopefully the Mini-Holland scheme will have reduced KSI in later years.

[joeytalbot]

It's KSI only

[Robinlovelace]

Fantastic.

[Robinlovelace]

We could subset to crashes during the commute peak times, e.g. 07:30 to 09:30 and 16:30 to 18:30.

[joeytalbot]

I already subset to the morning peak (07:00 <= time < 10:00)

[Robinlovelace]

Awesome.

[Robinlovelace]

Worth including the afternoon peak also?

[joeytalbot]

Morning and evening peak

[joeytalbot]

Here's the same for 2014-18 (Waltham Forest mini-holland began in 2015 I think)

[joeytalbot]

Of course, km_cycled are not accurate for these later years, but the change in KSI is noticeable

[layik]

Awesome work @joeytalbot.

[Robinlovelace]

Hey @joeytalbot where is the code that produces these results? Just taking a look...

[joeytalbot]

https://rpubs.com/joeytalbot/636356

[Robinlovelace]

Nice results! My suggestion on the visualisation would be to use tmap, ggplot2 or other package to create legends. Geographic distribution of relative values is very interesting.

[Robinlovelace]

A bit of tweaking and I think the figures will be ready for the report. I suggest saving them in the figures folder of this repo.

[joeytalbot]

https://rpubs.com/joeytalbot/636360

[joeytalbot]

This looks like a very strong exponential decay curve.

Hillingdon and City of London are interesting as boroughs that have lower KSI than expected given the level of cycling

[Robinlovelace]

Really interesting, supporting the 'strength in numbers' hypothesis.

[layik]

Hi @joeytalbot. Do we have the output of this? I am hoping I dont need to run scripts to get the data? Is that right? Just trying to get into the eatlas as per saferactive/saferactive-eatlas#10 and saferactive/saferactive-eatlas#12.

Thanks

[joeytalbot]

See saferactive/rate_per_borough.Rds for walking and cycling casualty rates at borough level