Cellular Automaton Based Simulation of Large Pedestrian Facilities - A Case Study on the Staten Island Ferry Terminals
This work addresses capacity planning for a critical mass transit system in New York City, but it is incremental as it applies existing simulation methods to a specific case study.
The paper tackled the problem of evaluating how the Staten Island Ferry terminals will handle increasing passenger demand, proposing an integrated simulation approach that combines microscopic cellular automata for terminal buildings and mesoscopic queue simulation for ferry journeys, resulting in recommendations for future demand management.
Current metropolises largely depend on a functioning transport infrastructure and the increasing demand can only be satisfied by a well organized mass transit. One example for a crucial mass transit system is New York City's Staten Island Ferry, connecting the two boroughs of Staten Island and Manhattan with a regular passenger service. Today's demand already exceeds 2500 passengers for a single cycle during peek hours, and future projections suggest that it will further increase. One way to appraise how the system will cope with future demand is by simulation. This contribution proposes an integrated simulation approach to evaluate the system performance with respect to future demand. The simulation relies on a multiscale modeling approach where the terminal buildings are simulated by a microscopic and quantitatively valid cellular automata (CA) and the journeys of the ferries themselves are modeled by a mesoscopic queue simulation approach. Based on the simulation results recommendations with respect to the future demand are given.