Agent-Based Modelling and Simulation of Crowd Evacuation: Case Study for Electric Train Cabin

Abstract

The agent-based simulation is a cutting-edge example of a fresh and clever technique intended to fulfil these goals. Numerous academics and researchers investigated the crucial merits, applicability, and contributions of this approach in a range of extreme situations and catastrophic scenarios. Their numerical analysis and mathematical simulations showed that the agent-based simulation framework is essential for providing a thorough knowledge of pedestrian behavior and human mobility in difficult emergency conditions. This work uses egress modelling to explore crew procedures' impact on evacuating train cabins under different fire scenarios.Based on the numerical simulations and analyses conducted via the Netlogo software package, Author’s found that two employees (contracted by the railroad company) in the lounge coach and two train hosts in the first-class coaches under emergencies achieve an efficient step toward evacuating a larger number of passengers. Nonetheless, passengers should be aware and familiar with the locations of these exit points, emergency signs, and egress paths to avoid any congestion, stampedes, and social attachment that may contribute to losses of life and delay the evacuation process. Also, an agent-based simulation is remarkably practical for determining intelligent practices and effective methods that can be adopted and followed to accelerate the evacuation process compared with other methods that are very difficult or unethical to apply, such as subjecting a group of people to a real fire event and predicting some methods to evacuate them based on the results.