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The formulation of pedestrian floor field cellular automaton models is generally based on hypothetical assumptions to represent reality. This paper proposes a novel methodology to calibrate these models using experimental trajectories. The methodology is based on likelihood function optimization and allows verifying whether the parameters defining a model statistically affect pedestrian navigation
