Urban Traffic Flow Volume Modeling for Beijing Using a Mixed-Flow Model

This paper proposes a new mixed-flow model to capture the main statistical features of traffic volume flows over Beijing transportation networks. The model consists of three parts i.e. the major part decided by residents' everyday travel, which remains relatively stable and follows a certain M-shape curve, the random fluctuations whose magnitude follows time variant super-Gaussian distribution, and “peaks” whose arriving rates obey the negative exponential distribution. This model can describe well the arriving behaviors of the “peaks” in the traffic volume flow. Further analysis of “peaks” arrives in negative exponential distribution and the traffic flow volume is in a multifractal time series. The obtained results shed light on our understanding of the origin and characteristics of the urban traffic flow, which are thus useful for traffic prediction and control.