1. BRIAN LAWTON TRL

2. Page  2 Tea time teaser!  Roads with street lights have a higher average collision rate than roads without street lights.  Should we remove street lights? Why/why not?

3. Page  3 Possible explanations  People drive more carefully when there are no street lights  Collisions on roads with street lights are more likely to be recorded  Street lights are installed on busier roads  Street lights are installed on roads with higher collision risk  Any others?

4. Page  4 Another example  Motorways have a lower collision rate than other road types  Motorways typically have 70mph speed limits  Would increasing speed limits to 70mph on other roads reduce their collision rates?  But comparing like with like can be harder than it seems …

5. Page  5 Demonstration  We’re going to ‘analyse’ some collision data on some hypothetical high risk roads  Then we’re going to ‘do something’ to improve their safety  Afterwards, we’ll have a look at how unbelievably effective it was* 

6. Page  6 Where to target interventions?  Where should we spend our limited budget?  Our budget is …  £0  and …  0p  We need to improve the safety of our most dangerous roads through mind power alone!

7. Page  7 The mind is powerful!  Something must be done  This is something  Therefore, this must be done  Focus on the worst roads  Visualise lower ranked cards for them  We all want to see a reduction in KSI figures 

8. Page  8 It was just chance …  The apparent improvement* wasn’t real  We still weren’t comparing like with like  We biased both groups by the way that we selected them  The KSI numbers in both groups simply regressed towards the mean*  The fewer collisions there are, the greater the impact of the randomness element

9. Page  9 How is this relevant to road safety?  Historic collision numbers aren’t always a good indicator of collision risk  Don’t take (small) ‘before’ and ‘after’ collision numbers at face value, even when compared with a background trend  A more stable proxy for risk is often helpful:  e.g. if the intervention is intended to reduce vehicle speeds, measure speeds before and after  Thinking about how to measure effectiveness can aid choice of appropriate interventions

10. Page  10 So what have we learnt? Credit to www.xkcd.com (number 552)www.xkcd.com

11. Page  11 Thank you! Presented by Brian Lawton TRL Road Safety Scientist 1 st March 2016 Tel: 01344 770408 Email: blawton@trl.co.ukblawton@trl.co.uk