[Paper Review] Cellular Automaton Based Simulation of Large Pedestrian Facilities - A Case Study on the Staten Island Ferry Terminals

Luca Crociani, Gregor Lämmel+2 more|arXiv (Cornell University)|Sep 11, 2017

Evacuation and Crowd Dynamics23 references3 citations

TL;DR

This paper proposes a multiscale simulation model combining cellular automata (CA) for microscopic pedestrian dynamics in terminal buildings and mesoscopic queueing for ferry schedules to evaluate the Staten Island Ferry terminals under current and projected future demand. The key finding is that the current terminal layout cannot handle projected peak demand, with boarding times exceeding 9 minutes in Whitehall, indicating urgent need for layout or procedural changes to maintain schedule integrity.

ABSTRACT

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.

Motivation & Objective

• To validate a simulation model of the Staten Island Ferry terminals against real-world peak-hour data for accuracy.
• To evaluate the performance of current terminal layouts under projected future passenger demand exceeding 3,600 per cycle.
• To identify operational bottlenecks in passenger flow, particularly during boarding and disembarking at St. George and Whitehall terminals.
• To provide data-driven recommendations for infrastructure or procedural modifications to improve terminal efficiency and maintain ferry schedule adherence.
• To demonstrate the effectiveness of a hybrid multiscale simulation approach combining microscopic CA and mesoscopic queueing for large-scale pedestrian facilities.

Proposed method

• A cellular automata (CA) model with discrete space and time grids simulates individual pedestrian movements within the terminal buildings at a microscopic level.
• The model uses a step-based time representation with fixed time steps and incorporates agent-based decision rules for path selection and door access.
• A mesoscopic queue simulation models ferry journey cycles, including departure intervals and passenger throughput, integrated with the CA-based terminal simulations.
• The simulation integrates both terminal buildings (St. George and Whitehall) and models passenger flows across gates, waiting areas, and boarding ramps.
• Model validation is performed by comparing simulated passenger travel times against observed data from on-field measurements during peak hours.
• Multiple simulation runs (30 iterations per scenario) are conducted to ensure convergence to a steady-state condition before analysis.

Experimental results

Research questions

• RQ1 How accurately can the proposed CA-based simulation model reproduce real-world passenger travel times during peak boarding and disembarking at the Staten Island Ferry terminals?
• RQ2 What are the projected impacts of future demand (exceeding 3,600 passengers per cycle) on passenger travel times and terminal throughput?
• RQ3 How do current terminal layouts and boarding procedures perform under projected future demand, particularly in terms of boarding duration and cycle time?
• RQ4 Which terminal (Whitehall or St. George) acts as the critical bottleneck in the ferry cycle under increasing demand?
• RQ5 What operational or infrastructural changes are required to maintain acceptable boarding times and schedule adherence under future demand projections?

Key findings

• The simulation model successfully validated against real-world data, with average boarding times differing by less than 10% from observed values in the base case scenario.
• In the 2017 demand projection, average boarding time at Whitehall reached 204 seconds (over 3.5 minutes), with the 95th percentile reaching 332 seconds (over 5.5 minutes), indicating significant delays.
• The maximum total boarding time in Whitehall reached 558 seconds (over 9 minutes), exceeding the 15-minute ferry schedule interval and threatening on-time operations.
• St. George terminal showed more favorable performance, with an average boarding time of 165 seconds (under 3 minutes), but still exceeded 5 minutes in the 95th percentile.
• The simulation revealed that the Whitehall terminal is the critical bottleneck due to longer travel times and higher passenger volumes, despite using two boarding doors.
• The results indicate that the current terminal layout is inadequate for future demand, necessitating modifications to either infrastructure or boarding procedures to maintain operational efficiency.