Sunday 27 January 2013

Seasonality of road casualties

The other day a few people were discussing on Twitter whether cycling was statistically more dangerous, in terms of casualties per mile, during winter than during summer. This is something I tend to wonder while cycling home in the dark, so I thought I'd try and investigate.

I used DfT's data on reported road casualties in 2011,  the most recent year available. Using just one year's data means the patterns observed may be affected by unusual weather patterns in that year, so you should treat the results as fairly provisional. Another issue with the data is unreporting, so I have focused on fatal or serious injuries which we assume are less likely to be unreported.

Most of the data cleaning and analysis was done with R, and I've copied my code at the bottom of the post. I'm no expert at R so I'm sure the code could be improved, but if anybody wants to use it then feel free.

The DfT data includes all kinds of roads casualties including those suffered while atop horses or tractors, but to keep things simple I've restricted the analysis to pedestrians, cyclists and car occupants (excluding taxis and private hire vehicles). The chart below shows the total number of fatal and serious casualties in England and Wales by road user type and month in 2011:

You can see the different patterns for each mode more clearly if you split them out:

What you see are very clear seasonal patterns for pedestrians and cyclists, with pedestrian casualties rising as winter draws in and then reaching a trough in summer, and cyclist casualties following more or less an opposite trend. There doesn't seem to be much of a pattern for car occupants, although the number of casualties is highest in December and January.

Here's the same chart for London:

The raw numbers shift around a lot because London's mode share is so different, with a lot more pedestrians and cyclists and less car traffic than in the rest of the country. But the seasonal patterns look a little different too. In particular there is a much bigger increase in pedestrian casualties towards the end of the year, and December has nearly twice as many as January.

For cyclists the obvious explanation for higher casualties in summer months is that more people cycle at that time of year. For pedestrians the logic is less clear. It doesn't seem likely that there is much more walking done in the winter months than in the summer. So the winter months, particularly December, just seem to be more risky. Nationally, the worst days for fatal or serious pedestrian casualties in 2011 were the 9th, 12th and 16th of December. There was plenty of snow that month but I wonder whether there is also some sort of 'Christmas party effect' at work here, on both pedestrians and drivers (by the way, in the US the deadliest day for pedestrians is apparently New Year's Day - see also this).

To calculate a casualty rate you divide casualties by some measure of traffic or trips. For pedestrians there's no such data that I know of. But TfL count cars and bikes passing various points on the London road network, and they have made the cycling data available via FOI in the form of this big Excel spreadsheet. This data is patchy for some count points but you can fill in the gaps with estimates based on the ones with complete data.

The other option for estimating monthly cycle trips is to use TfL's counts of cycle hires. The chart below compares monthly trends in fatal/serious bike casualties, TfL cycle counts and cycle hires, by expressing each month's figure as a ratio of the average.

Now, you probably shouldn't read too much into this comparison as it's comparing one imperfect data source with another two imperfect ones gathered at different spatial scales. But it does look like there is a bigger increase in casualties between January and June than there is in either of the trip indicators. This suggests, again very provisionally given the limitations of the data, that the number of casualties per cycling trip may be lower in the first few months of the year than in summer.

We really need a more comprehensive analysis to establish if this really is the case, but if it was what would explain it? Perhaps people who cycle all year may be more careful or skilled than those who only take to their bikes in summer. Maybe drivers may look out for cyclists more in winter. At this stage, we just don't know.


  1. Traditional “road safety” wonks refer to winter months as worse because of more hours of darkness and the higher chances of snow and ice.

    Snow and ice is a very interesting area: take a look at Dec 2010 in London for example. My interest is that it shows a classic case of risk compensation by road users. What happens is that because snowy/icy conditions are so inherently hazardous (zero coefficient of friction with ice, ice may be invisible, snow may cover ice, be difficult to predict in degrees of slushiness etc.) slight injuries (and also rates per trip for all modes) go up.

    However, with the more reliable Serious Injury category, the total goes DOWN. Part of the reason for this is that people travel less (so the IS rate per journey may not go down, or not as much), but it is also that people take more care. In other words, motorists CAN take more care if they are pressured into doing so – in this case having to slow down and be generally more alert.

    Dr. Robert Davis, Chair Road Danger Reduction Forum

  2. Would be good to see whether this picture changes if averages of multiple years worth of data (if available) were taken into account. Should help reduce the 'noise' of daily/weekly weather conditions.

  3. Could you post the dataset in csv please?

  4. Hi Mike, sorry for the delay in getting back to you. The dataset is 38mb in size so too big for me to share easily. You can download the raw data yourself from here

    And if you want to merge the files as in my example above the best thing is to install R and just copy my code.

    1. 38Mb, that's small ;*) I've hacked that dataset around a bit in the past with Access and mapinfo. I'm just learning SAS so this looks like an interesting application for self study instead of learning another language..

  5. I am agree with Anonymous. It show's about road casualties that pedestrians and cyclist are dealing throughout the winter and summer season.


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