City traffic forecasting using taxi GPS data Yucheng Hu Qinghua (Tsing Hua) University Zhou Pei-yuan Center for Applied Mathematics For many big cities in China, traffic has become a major bottleneck limiting the development of the city. To take rational actions to control and manage city traffic, it is important for us to have a deep understanding on how the traffic system works first. Big data on city traffic that has recently become available provide new ways to understand traffic flow. Our group start to tackle this problem using GPS data collected from all taxis in Beijing. In this talk, I will mainly discuss a coarse-grained cellular automata model we develop aiming to reconstruct and forecast the city traffic flow. The coarse-grained model is less computational expensive than the microscopic car following model and can incorporate historical data into the model parameters in a way the macroscopic model cannot. Several potential applications of the model are discussed.