The forecast of urban mobility in the long term is one of the great challenges of planning of the urban transport. The classical model for traffic demand forecast is represented by one algorithm based of following four steps: trip generation, trip distribution, mode choice and route assignment. The contestation of traditional method, based of statistical data collected on one period, shall be improved by usage of demographic model. The demographic model is pertinent for estimation of trip generation. The use of the demographic approach with data from repetitive surveys makes it possible to get insight in the behaviour dynamics of individuals belonging to the several generations at various stages of their life cycle. The decomposition of temporal effects into an effect of age and an effect of generation (cohort) makes it possible to draw the sample profile during the life cycle and to estimate its temporal deformations. It is the fundamental concept of the 'age–cohort' model which has been developed in INRETSDEST (France – from January 2011, the INREST–DEST is a part of The Institute of Science and Technology for Transport, Development and Networks – IFSTTAR: www.ifsttar.fr), basically for projection of car household ownerships, and after it is adapted for forecast of mobility on long term. The comparison of forecasts between the 'age–cohort' model and the growth factors method shows the relevance of the demographic model. Sensitivity tests of the model, as well as the capacity of the model to carry out simulations are also justified. The application of the model relates to the agglomeration of Lille (France), where we have three data surveys at approximately 10 years intervals.

urban mobility, age, cohort, transport planning, mobility forecast model