Analysis and Simulation of Intervention Strategies against Bus Bunching by means of an Empirical Agent-Based Model

In this paper, we propose an empirically based Monte Carlo bus-network (EMB) model as a test bed to simulate intervention strategies overcome the inefficiencies of bus bunching. The EMB is agent-based which utilizes positional and temporal data buses obtained from Global Positioning System (GPS) constitute (1) set empirical velocity distributions (2) exponential interarrival time passengers at stops. sampling then performed on these two derived probability yield stochastic dynamics both buses’ motion passengers’ arrival. Our generic can be applied any real-world network system. particular, have validated against Nanyang Technological University’s Shuttle Bus by demonstrating its accuracy in capturing bunching shuttle buses. Furthermore, analyzed efficacy three strategies: holding, no-boarding, centralized-pulsing, incorporating rule into model. Under scenario where same velocity, found that all improve waiting travelling times commuters. However, when different velocities, only centralized-pulsing scheme consistently outperforms control periodically bunch together.