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Computer-based simulation of pedestrian dynamics reached meaningful resultsin the last decade, thanks to empirical evidences and acquired knowledgefitting fundamental diagram constraints and space utilization. Moreover,computational models for pedestrian wayfinding often neglect extensiveempirical evidences supporting the calibration and validation phase ofsimulations. The paper presents the results of a set of controlled experiments(with human volunteers) designed and performed to understand pedestrian's routechoice. The setting offers alternative paths to final destinations, atdifferent crowding conditions. Results show that the length of paths and levelof congestion influence decisions (negative feedback), as well as imitativebehaviour of "emergent leaders" choosing a new path (positive feedback). Anovel here illustrated model for the simulation of pedestrian route choicecaptures such evidences, encompassing both the tendency to avoid congestion andto follow emerging leaders. The found conflicting tendencies are modelled withthe introduction of a utility function allowing a consistent calibration overthe achieved results. A demonstration of the simulated dynamics on a largerscenario will be also illustrated in the paper.

Avoid or Follow? Modelling Route Choice Based on Experimental Empirical Evidences