On Designing Day Ahead and Same Day Ridership Level Prediction Models for City-Scale Transit Networks Using Noisy APC Data. (arXiv:2210.04989v1 [cs.LG])

The ability to accurately predict public transit ridership demand benefits
passengers and transit agencies. Agencies will be able to reallocate buses to
handle under or over-utilized bus routes, improving resource utilization, and
passengers will be able to adjust and plan their schedules to avoid overcrowded
buses and maintain a certain level of comfort. However, accurately predicting
occupancy is a non-trivial task. Various reasons such as heterogeneity,
evolving ridership patterns, exogenous events like weather, and other
stochastic variables, make the task …

apc arxiv city data networks prediction scale transit