Abstract

AbstractIn order to control urban traffic with model-based control methods, a proper traffic model is very important. This traffic control model needs to have enough descriptive power to reproduce relevant traffic phenomena, and it also has to be fast enough to be used in practice. Therefore, macroscopic urban traffic flow models are usually applied as control models. These models are normally sampled temporally and spatially into discrete models so as to be simulated using digital computers. In this paper, a spatiotemporally discrete urban traffic model with a variable sampling time interval is proposed for model-based predictive control, which allows to balance modeling accuracy and computational complexity. The model is analyzed and evaluated based on the model requirements for control purposes. In addition, conditions are given to selecting suitable sampling time intervals for the models that are used to control urban traffic networks.

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