1. A method for learning transportation models of an associated transportation network, comprising: receiving validation information from at least one ticketing validation system, the validation information including at least one of a timestamp, a location, or a ticket identification of a traveler on the associated transportation network; reconstructing each of a plurality of trips in accordance with the received validation information; estimating an origin and a destination from the reconstructed plurality of trips; estimating at least one of an arrival time or a destination time corresponding to each of the plurality of reconstructed trips; generating a demand model of the associated transportation network in accordance with the estimated origin, destination and the estimated at least one of the arrival time or the destination time; retrieving, from an associated database, an assignment model of the associated transportation network; simulating the transportation network in accordance with the assignment model to acquire origins, destinations and the estimated at least one of the arrival time or the destination time; reconstructing a set of simulated trips derived from the simulated origins, destinations, and the estimated at least one of the arrival time or the destination time; comparing the set of simulated trips to a corresponding set of reconstructed trips; determining, from the comparing, a difference between the set of simulated trips and the corresponding set of reconstructed trips; in response to the determined difference, iteratively adjusting at least one parameter value associated with the assignment model; receiving, from an associated user device, a selection of an infrastructure change to the transportation network the infrastructure change comprising at least one of a route change, a new stop added, a new vehicle added, a stop removed, a new train line added, an addition of one or more vehicles on a same route, or a new train station; and simulating the transportation network in accordance with the iteratively adjusted parameter value associated with the assignment model utilizing the selected infrastructure change and providing to the user the simulated transportation network, wherein at least one of the receiving, reconstructing, estimating, generating, retrieving, simulating, comparing, determining, and adjusting is performed by a computer processor.