Estimation of people flow in public transportation network through the origin-destination problem for the South-Eastern corridor of Quito city in the smart cities context

A novel mathematical model using Bayesian inference and Monte Carlo simulations successfully estimates people flow in Quito's South-Eastern public transportation corridor. The study leverages Origin-Destination Matrices (ODM) derived from passenger boarding and alighting data, applying the Metropolis-Hastings criterion to validate results. Key findings include the convergence of estimated flows, consistent origin-destination behavior patterns, and robustness against link variations. This approach offers a scalable solution for smart city planning, demonstrated through its application in Quito's transportation network.

Zapata, L. P., Flores, M., Larios, V., Maciel, R., & Antunez, E. A. (2019). Estimation of people flow in public transportation network through the origin-destination problem for the South-Eastern corridor of Quito city in the smart cities context. 2019 IEEE International Smart Cities Conference (ISC2), 181–186. https://doi.org/10.1109/isc246665.2019.9071778