Master’s Thesis in Mathematics: A multi-class framework for a pedestrian cell transmission model accounting for population heterogeneity

This work is an extension of PedCTM, an aggregate and transient cell transmission model for multidirectional pedestrian flows in which pedestrian characteristics are assumed to be homogeneous across the population considered. Critically, one fundamental diagram relating pedestrian speed and flow to local pedestrian density is employed across the entire population. This work extends the model to population heterogeneity with a multi-class approach wherein each sub-population is assigned its own characteristic fundamental diagram. The model presented requires the implementation of an update cycle to minimize numerical dispersion of pedestrians across all classes. In addition, multi-class dynamics introduces an element of competition in determining the flow constraints of the various classes. A priority scheme is implemented that allows for static, dynamic and stochastic determination of flow priorities throughout the network over the course of simulation. An attempt was made to base the class-specific fundamental diagrams off of inference from a dataset related to the PedFlux collaboration. Ultimately, however, the implementation made use of the Kladek formula for the speed-density relation. Preliminary simulations and results are presented to serve as a proof of concept.