I'm analysing road safety data. I have counts for the number of accidents that occur on different roads:
ggplot(data, aes(as.factor(Road_Type), fill=as.factor(Accident_Severity))) + geom_bar(position="stack")
Looking at this, Road_Type=6 (corresponding to "Single carriageway") appears most dangerous, however I do not have counts for the total number of traffic or the length of the roads (i.e. Road_Type=6 may have had 1million cars travelled on it, whilst only 10 cars may have travelled on Road_Type=9). Thus, I am struggling to identify which roads are the most dangerous (because I feel those Road_Types with significantly more cars on are generally more likely to have a greater number of accidents).
Is there a technique I can use to find the "weighted" dangerousness of roads (i.e. by taking into account the possible relationships between the number of cars and accidents)?