  Computer-based simulation of pedestrian dynamics reached meaningful results
in the last decade, thanks to empirical evidences and acquired knowledge
fitting fundamental diagram constraints and space utilization. Moreover,
computational models for pedestrian wayfinding often neglect extensive
empirical evidences supporting the calibration and validation phase of
simulations. The paper presents the results of a set of controlled experiments
(with human volunteers) designed and performed to understand pedestrian's route
choice. The setting offers alternative paths to final destinations, at
different crowding conditions. Results show that the length of paths and level
of congestion influence decisions (negative feedback), as well as imitative
behaviour of "emergent leaders" choosing a new path (positive feedback). A
novel here illustrated model for the simulation of pedestrian route choice
captures such evidences, encompassing both the tendency to avoid congestion and
to follow emerging leaders. The found conflicting tendencies are modelled with
the introduction of a utility function allowing a consistent calibration over
the achieved results. A demonstration of the simulated dynamics on a larger
scenario will be also illustrated in the paper.
