Turner et al (2006) derived crash prediction models for this report’s predecessor and found a
pronounced ‘safety in numbers’ effect in the models. Using the crash prediction model for mid-block
locations, generic motorist and cyclist volumes can be used to demonstrate the impacts on the
expected crash rate of varying motor vehicle and cycle volumes. As shown in figure 2.20, an increase
in the proportion of cyclists to the overall traffic volume causes an increase in expected crashes at
mid-block locations, but the crash rate increases at a decreasing rate. That is to say, the crash rate per
cyclist goes down as the cycle volume increases.
Consider the following text:
Berg village and Hill village are renowned for the high number of cyclists living there. Berg village dealt with many traffic casualties because of narrower streets and lanes, While Hill village had wide streets, more traffic signals and a greater number of cyclists.

Which village had a greater traffic volume?