A method for optimizing the comfort in a railway vehicle of a fleet of railway vehicles circulating on a same railway track, the railway vehicle including at least one active suspension system parameterized by a set of adjustment parameters, characterized in that: - each vehicle of the fleet comprises tridimensional acceleration sensors, - the railway track is cut out in segments, - for each segment, the method includes campaigns for optimization of the set of adjustment parameters, such that: • during the first optimization campaign, at each passage of the suspension system on the segment, a first set of adjustment parameters, specific to this passage, is predefined and applied to the suspension system, and a comfort quality index is calculated on the basis of tridimensional accelerations measured by the sensors, and then a metaheuristic algorithm is applied for determining second set of adjustment parameters, • during each following optimization campaign, at each passage of the suspension system over the segment, one of the sets of adjustment parameters determined by the previous optimization campaign is applied to the suspension system and the comfort quality index is calculated, and then the metaheuristic algorithm is applied for determining new sets of adjustment parameters, the metaheuristic algorithm taking into account the calculated comfort quality indexes, to deduce parameters that seems the most appropriate to improve the comfort on the segment, and • each optimization campaign is common to several vehicles of the fleet of vehicles circulating on the same track, the data relative to each optimization campaign being shared in common. - each vehicle of the fleet comprises tridimensional acceleration sensors, - the railway track is cut out in segments, - for each segment, the method includes campaigns for optimization of the set of adjustment parameters, such that: • during the first optimization campaign, at each passage of the suspension system on the segment, a first set of adjustment parameters, specific to this passage, is predefined and applied to the suspension system, and a comfort quality index is calculated on the basis of tridimensional accelerations measured by the sensors, and then a metaheuristic algorithm is applied for determining second set of adjustment parameters, • during each following optimization campaign, at each passage of the suspension system over the segment, one of the sets of adjustment parameters determined by the previous optimization campaign is applied to the suspension system and the comfort quality index is calculated, and then the metaheuristic algorithm is applied for determining new sets of adjustment parameters, the metaheuristic algorithm taking into account the calculated comfort quality indexes, to deduce parameters that seems the most appropriate to improve the comfort on the segment, and • each optimization campaign is common to several vehicles of the fleet of vehicles circulating on the same track, the data relative to each optimization campaign being shared in common. • during the first optimization campaign, at each passage of the suspension system on the segment, a first set of adjustment parameters, specific to this passage, is predefined and applied to the suspension system, and a comfort quality index is calculated on the basis of tridimensional accelerations measured by the sensors, and then a metaheuristic algorithm is applied for determining second set of adjustment parameters, • during each following optimization campaign, at each passage of the suspension system over the segment, one of the sets of adjustment parameters determined by the previous optimization campaign is applied to the suspension system and the comfort quality index is calculated, and then the metaheuristic algorithm is applied for determining new sets of adjustment parameters, the metaheuristic algorithm taking into account the calculated comfort quality indexes, to deduce parameters that seems the most appropriate to improve the comfort on the segment, and • each optimization campaign is common to several vehicles of the fleet of vehicles circulating on the same track, the data relative to each optimization campaign being shared in common.