Quantifying MyCiTi supply usage using Big Data and Agent-Based Modelling

Cape Town's Bus Rapid Transit (BRT) system, MyCiTi, uses an Automated Fare Collection (AFC) system that generates large volumes of transactional data on a daily basis. This can be considered Big Data. The AFC in its raw format, however, is incapable supporting supply and demand analysis (e.g. studying bus occupancy rates). Agent-Based Modelling (ABM) used to analyse such for purpose. paper discusses the development calibration MATSim-based ABM BRT system. It shown data-formatting algorithms are critical preparation modelling activities. Furthermore, appropriate parameters requires careful consideration terms collection, simulation testing, justification, which discussed. furthermore shows calibrated generate outputs as on-board volumes, system-demand overview, even individual commuter path choice behaviour. Finally, validation exercise model developed this study able provide good estimates (R2 = 0.85). is, recommended further research conducted into agent choices through simulation.