A methodology based on generalized linear mixed effects models and generalized mixed-effect random forests applied to APC data identifies segments and temporal patterns associated with undercrowding on a Milan public transport route.
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Spatio-Temporal Analysis of Public Transportation Undercrowding: Leveraging APC Data for a Comprehensive Evaluation of Usage Rates
A methodology based on generalized linear mixed effects models and generalized mixed-effect random forests applied to APC data identifies segments and temporal patterns associated with undercrowding on a Milan public transport route.