Modeling passengers' orderly and disorderly boarding behavior in a transit system

Cluster and other complex phenomena of bus flow easily occur due to such factors as bus stop location, passenger distribution and boarding behavior in a transit system. A new cellular automaton model which simultaneously considers these factors, particularly the passengers' orderly and disorderly boarding behavior, is proposed in this paper. Numerical simulation results, which match the analytic results well, show that the model can explicitly depict the space-time trajectories of bus movement along a bus line, reproduce the cluster and jam phenomena of bus flow, and quantitatively evaluate the impacts of various factors on bus average speed. The study provides insights on formation mechanism of cluster phenomena under different boarding modes, advocates orderly boarding behavior and helps the optimization of locating bus stations.