Traffic flows time series in a flood-prone area: modeling and clustering on extreme values with a spatial constraint
Maurizio Carpita,
Giovanni De Luca,
Rodolfo Metulini
et al.
Abstract:Time series of traffic flows, extracted from mobile phone origin–destination data, are employed for monitoring people crowding and mobility in areas subject to flooding risk. By applying a vector autoregressive model with exogenous covariates combined with dynamic harmonic regression to such time series, we detected the presence of many extreme events in the residuals, which exhibit heavy-tailed distribution. For this reason, we propose a time series clustering procedure based on tail dependence which is suita… Show more
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