S. Liu, B. De Schutter, and H. Hellendoorn, "Model predictive traffic control based on a new multi-class METANET model," Proceedings of the 19th IFAC World Congress, Cape Town, South Africa, pp. 8781-8786, Aug. 2014.
Multi-class traffic flow models account for the heterogeneous characteristics of traffic networks. This leads to higher accuracy when applying them for on-line model-based control. We propose a new multi-class METANET model. The proposed model is an extension of the single-class macroscopic traffic flow model METANET. In the new model, each vehicle class is subject to its own single-class fundamental diagram, and is limited within an assigned space. In this paper, model predictive control is used for on-line traffic control based on the newly proposed model. A case study is implemented for illustrating the efficiency of the new multi-class model. More specifically, the simulation results show that the new multi-class METANET model leads to a better performance than single-class METANET model.