  The widespread adoption of smartphones in recent years has made it possible
for us to collect large amounts of traffic data. Special software installed on
the phones of drivers allow us to gather GPS trajectories of their vehicles on
the road network. In this paper, we simulate the trajectories of multiple
agents on a road network and use various models to forecast the short-term
traffic speed of various links. Our results show that traditional techniques
like multiple regression and artificial neural networks work well but simpler
adaptive models that do not require prior training also perform comparatively
well.
