Agent-based simulation modeling of a Bus Rapid Transit (BRT) station using smart card data

Abstract

A Bus Rapid Transit (BRT) station with multiple loading zones tends to have a longer passenger-bus interface and, thus, lead to longer passenger walking times and longer bus dwell times than ordinary bus stops. As a way to reduce bus dwell times in a BRT station, this study focuses on eliminating delays in passengers' reaction to their desired bus by designing an improved passenger information system (PIS) that can increase passengers' certainty about the bus stopping location. This study develops an agent-based simulation model based on observations from a BRT station in Brisbane, Australia to reflect a real BRT operations and passenger flows. The input parameters for the simulation model are calibrated with actual data including smart card records, field measurements, and video recordings. After mapping passenger moving and waiting patterns, and allocation logic of bus loading areas, various what-if analyses can be performed to design better passenger information systems.