Estimating Network Fundamental Diagram Using Three-Dimensional Vehicle Trajectories

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Estimating Network Fundamental Diagram Using Three-Dimensional Vehicle Trajectories

Extending Edie's Definitions of Traffic Flow Variables to Networks

Saberi, Meead / Mahmassani, Hani S. / Hou, Tian / Zockaie, Ali

This paper evaluates measurement methods for traffic flow variables taken at the network level. Generalized Edie's definitions of fundamental traffic flow variables along highways are extended for considering vehicles traveling in networks. These definitions are used to characterize traffic flow in networks and form the basis for estimating relationships among network density, flow, and speed in the form of a network fundamental diagram. The method relies on three-dimensional vehicle trajectories to provide estimates of network flow, density, and speed. Such trajectories may be routinely obtained from particle-based microscopic and mesoscopic simulation models and are increasingly available from tracking devices on vehicles. Numerical results from the simulation of two networks, in Chicago, Illinois, and Salt Lake City, Utah, are presented to illustrate and validate the estimation methodology. As part of the verification process, the study confirms that the traffic flow fundamental identity (Q = K · V) holds at the network level only when networkwide traffic flow variables are defined consistently with Edie's definitions.