Travel　time　estimation　on　road　networks　is　a　valuable　traffic　metric.　In　this　paper,　we　propose　a　machine　learning　based　method　for　trip　travel　time　estimation　in　road　networks.　The　method　uses　the　historical　trip　information　extracted　from　taxis　trace　data　as　the　training　data.　An　optimized　online　sequential　extreme　machine,　selective　forgetting　extreme　learning　machine,　is　adopted　to　make　the　prediction.　Its　selective　forgetting　learning　ability　enables　the　prediction　algorithm　to　adapt　to　trip　conditions　changes　well.　Experimental　results　using　real-life　taxis　trace　data　show　that　the　forecasting　model　provides　an　effective　and　practical　way　for　the　travel　time　forecasting.