One of my favorite algorithms for this is Expectation Maximization [0].
You would start by estimating each driver's rating as the average of their ratings - and then estimate the bias of each rider by comparing the average rating they give to the estimated score of their drivers. Then you repeat the process iteratively until you see both scores (driver rating, and user bias) converge.)
You would start by estimating each driver's rating as the average of their ratings - and then estimate the bias of each rider by comparing the average rating they give to the estimated score of their drivers. Then you repeat the process iteratively until you see both scores (driver rating, and user bias) converge.)
[0] https://en.wikipedia.org/wiki/Expectation%E2%80%93maximizati...