Agent‐based simulator of dynamic flood‐people interactions

Abstract

This article presents a simulator for the modelling of the two‐way interactions between flooding and people. The simulator links a hydrodynamic model to a pedestrian model in a single agent‐based modelling platform, Flexible Large‐scale Agent Modelling Environment for the Graphical Processing Unit (FLAMEGPU). Dynamic coupling is achieved by the simultaneous update and exchange of information across multiple agent types. Behavioural rules and states for the pedestrian agents are proposed to account for the pedestrians' presence/actions in/to floodwater. These are based on a commonly used hazard rate (HR) metric to evaluate the risk states of people in floodwater, and by considering two roles for the pedestrians: evacuees or responders for action during or before the flood event, respectively. The potential of the simulator is demonstrated in a case study of a flooded and busy shopping centre for two scenarios: (a) during a flood evacuation and (b) pre‐flood intervention to deploy a sandbag barrier. The evacuation scenario points to changes in floodwater hydrodynamics around congested areas, which either worsen (by 5–8%) or lessen (by 25%) the HR. The intervention scenario demonstrates the utility of the simulator to select an optimal barrier height and number of responders for safe and effective deployment. Accompanying details for software accessibility are provided.

Flood-pedestrian simulator for modelling human response dynamics during flood-induced evacuation: Hillsborough stadium case study

“…The flood-pedestrian simulator dynamically couples a hydrodynamic model to a pedestrian model within the same agent-based modelling (ABM) framework, FLAMEGPU (Shirvani et al, 2020;Shirvani et al, 2021). The pedestrian model adopts a standard social force model that accounts for the dynamic interactions occurring between moving pedestrians in a built environment (Li et al, 2019;Jiang et al, 2020).…”

“…Therefore, HR-related flood risk states are used based on the categorisation of flood risk to people reported in the UK Environment Agency (EA), as listed in Table 1. The navigation agents are set to act as a shared communication interface between the flood agents and pedestrian agents, where the information is dynamically exchanged between the three agents (Shirvani et al, 2021). This interaction mechanism allows a pedestrian agent to pick up a HR quantity from the navigation agent at its location and autonomously flag itself with one of the flood risk states listed in Table 1.…”

“…Given its serial approach to the coupling, FlooPEDS is not ideally suited to incorporate the dynamic feedback from the moving pedestrians onto the floodwater flow. Shirvani et al (2021) developed a flood-pedestrian simulator by taking a parallel approach to achieve the dynamic coupling between the hydrodynamic model and the social force model, both being ABMbased and running from a single ABM-based framework, Flexible Large-scale Agent-based Modelling Environment for the GPU (FLAMEGPU). The flood-pedestrian simulator on the FLAMEGPU framework benefits from the computational speedup and high dynamic memory capacity of the Graphics Processing Unit (GPU).…”

“…The twoway interaction condition allows to capture both the response of moving pedestrians to the floodwater and the back interaction of pedestrians' presence on the floodwater flow. Enabling the two-way interaction condition was found to significantly affect the model outcomes in and around congested areas: predict reduced flood risk for the pedestrians in low to medium risk areas and increased risk for those around high risk areas (Shirvani et al, 2021). In Shirvani et al (2020), the social force model of the same simulator was further augmented with empirical datasets and experimentally derived formulas to incorporate nonuniform body characteristics and more variable moving speed and stability states of pedestrian agents in floodwater.…”

“…Discussions of key findings and limitations are finally presented. Because the flood-pedestrian simulator is flexibly configurable to adopt other case studies and evacuation scenarios, its source code on the FLAMEGPU framework, including all the agent characteristics and/or rules, is made openly available (Shirvani and Kesserwani, 2021a), as well as the datasets from the simulated case studies (Shirvani and Kesserwani, 2021b) and a video supplement that visualises the simulations in real time (Shirvani, 2021).…”