Using Machine Learning to Predict Car Accident Risk

We pose the car accident risk prediction as a classification problem with two labels (accident and no accident). It could equally be posed as a regression problem (number of accidents), but on our timescale (one hour) we don't expect to see more than one accident per road segment so this simplifies the problem a bit. There are of course other approaches, but this is the one we take here. Commonly traffic is modeled by a Poisson or Negative binomial model. We can use the seven years and roughly half a million car accident records as our positive examples.