Compatibility analysis of macroscopic and microscopic traffic simulation modeling

Abstract

To implement model predictive traffic control to reduce congestion, traffic state variables such as flow, speed, and density need to be accurately predicted with real-time measurements. To evaluate the accuracy of online prediction of a macroscopic traffic model, this paper compares the predicted flow, density, and speed from a macroscopic simulation model with those from a microscopic simulation model, using METANET and VISSIM respectively, on a section of urban freeway. Three levels of traffic demands and seven different time step lengths in macroscopic simulation were applied to evaluate the compatibility of the two models. It was concluded that in the macroscopic simulation model there exists an optimum time step length, under moderate to heavy traffic demands the predicted traffic states from the macroscopic simulation are consistent with the outputs from the microscopic simulation, and under stop-and-go traffic states significant difference exists between the two models.