Data fusion of passengers' travel information from different types of sources to infer mobility patterns and most used locations.

Thanks to the Intelligent transport systems (ITS), new technologies for data collection and processing have been developed. And data fusion techniques have been applied to improve the quality of the resultant model. In this thesis, the main objective is execute a data fusion metholody on different data sources, such as surveys, mobile application data, automatic fare collection(AFC) and router data, to estimate the origin-destination (OD) matrix of the public transport users from two French agglomerations: Agglomération de la région de Compiègne (ARC) and Agglomération Creil Sud Oise (ACSO). This thesis has been carried out within the research work of the Chair MIDT -Mobilité Intelligente et Dynamiques Territoriales – of the Université de Technologie de Compiègne -UTC- in Compiègne, France, in conjunction with other research projects and theses.