Mobility modeling through mobile data: generating an optimized and open dataset respecting privacy
Résumé
Modeling and understanding people’s mobility at a temporal and geographical space are very strict requirements for developing better strategies of urban public and private transportation systems as well as establishing improved business techniques. FluxVision solution from Orange Applications for Business provides general statistical indicators of people’s attendance, origin, and mobility for some events with high privacy guarantees. This work proposes a methodology to instantiate these statistics by solving, to the extent possible, all its underlying constraints. The provided mobility scenario includes specific information about people attending one or several days in the analysis period. We recreate this scenario with virtual humans, proposing a synthetic and open dataset that matches the original statistical data. The results show that the proposed methodology is very efficient to model people’s mobility, and the generated data has a low error rate compared to the original one.
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