This repo contains miscellaneous R scipts, documentation and figures related to the Propensity to Cycle Tool.
This repo is not needed to run the PCT on your computer. For that, see pct-load.
The project is funded by the Department for Transport (DfT) so the initial case studies will be taken from the UK. However, it is expected that the methods will be of use elsewhere. For that reason, attempts have been made to make the examples generalisable. All examples presented here are reproducible using data stored in the pct-data repository.
If you run the following lines of code on from a local copy of the pct repository you will get the same results.
source("set-up.R")
# load some flow data
fleeds <- read.csv("README_files/data/sample-leeds-centre-dists.csv")
# load the zones
leeds <- readOGR("README_files/data", "leeds-central-sample")## OGR data source with driver: ESRI Shapefile
## Source: "README_files/data", layer: "leeds-central-sample"
## with 25 features
## It has 3 fields
Now we can estimate propensity to cycle, by using the distance decay function from (Iacono et al. 2010):
where
To implement this understanding in R code we can use the following function:
# Distance-dependent mode switch probs
iac <- function(x, a = 0.3, b = 0.2){
a * exp(-b * x)
}Apply this function to openly accessible flow data:
fleeds$p_cycle <- iac(fleeds$dist / 1000)
fleeds$n_cycle <- fleeds$p_cycle * fleeds$All.categories..Method.of.travel.to.work
fleeds$pc1 <- fleeds$n_cycle - fleeds$BicycleNow we can create a simple visualisation of the result:
plot(leeds)
for(i in which(fleeds$Area.of.residence == leeds$geo_code[1])){
from <- leeds$geo_code %in% fleeds$Area.of.residence[i]
to <- leeds$geo_code %in% fleeds$Area.of.workplace[i]
x <- coordinates(leeds[from, ])
y <- coordinates(leeds[to, ])
lines(c(x[1], y[1]), c(x[2], y[2]), lwd = fleeds$pc1[i] )
}
\
Some of the examples pull data from the CycleStreets.net API. Once you have a token, you can add it in Ubuntu as a session variable using the following in your terminal
echo "export CS_API_KEY='my_token'" >> ~/.profileor system wide variable
sudo echo "export CS_API_KEY='my_token'" > /etc/profile.d/cyclestreet.shThe version of gdal needs to be newer than 1.11
rgdal::getGDALVersionInfo()## [1] "GDAL 1.11.2, released 2015/02/10"
# Should return GDAL 1.11.2, released 2015/02/10 (or newer)It is possible to use the following Personal Package Archive (PPA) to get the latest version of gdal on Ubuntu.
sudo add-apt-repository ppa:ubuntugis/ubuntugis-unstable && sudo apt-get update
sudo apt-get install gdal-bin libgdal-dev
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