driver-identification

The prevalence of smartphones have changed our lives, perhaps mostly for better but in a few cases they have caused harm. Gig-economies only made possible thanks to smartphones, and interestingly enough there are still disputes on whether they cause more good or harm, or differently put, what is their net contribution to the society.

A major issue in driver identification is lack of enough data from the target group of drivers. In this work I use Triplet loss to train neural nets that learn to discriminate between small chunks of driving data. Through this we significantly reduce the amount of data needed to perform accurate driver identification or verification.

This is one of my latest works in which I apply deep learning to problem of driver identification using GPS data collected from smartphone.