Castillo, EnriqueGrande, ZacariasCalviño Martínez, AídaSzeto, W. Y.Lo, Hong K.2023-06-192023-06-19201510.1155/2015/903563https://hdl.handle.net/20.500.14352/35589A state-of-the-art review of flow observability, estimation, and prediction problems in traffic networks is performed. Since mathematical optimization provides a general framework for all of them, an integrated approach is used to perform the analysis of these problems and consider them as different optimization problems whose data, variables, constraints, and objective functions are the main elements that characterize the problems proposed by different authors. For example, counted, scanned or “a priori” data are the most common data sources; conservation laws, flow nonnegativity, link capacity, flow definition, observation, flow propagation, and specific model requirements form the most common constraints; and least squares, likelihood, possible relative error, mean absolute relative error, and so forth constitute the bases for the objective functions or metrics. The high number of possible combinations of these elements justifies the existence of a wide collection of methods for analyzing static and dynamic situations.engAtribución 3.0 Españahttps://creativecommons.org/licenses/by/3.0/es/journal articlehttp://dx.doi.org/10.1155/2015/903563open access621.396.9656519.22-7flujoestimaciónprediccióntráficoflow observabilityestimationpredictiontrafficEstadísticaProbabilidades (Estadística)1209 Estadística1208 Probabilidad