To forecast the urban traffic flow more effectively, this paper proposes a Network Tomography based traffic flow prediction model. The model builds a spanning tree based on Network Tomography, estimates traffic probability distribution in road network subnet by Expectation Maximization (EM) algorithm, forecasts the traffic flow according to the flow conservation in road network. Experimental results show that the new model has higher estimation accuracy compared to the Artificial intelligence model.
