Agent-based societal impact modeling for infrastructure disruption and countermeasures analyses

Infrastructure disruptions can severely affect societal well-being. Quantifying the societal impacts of infra-structure disruptions and identifying appropriate countermeasures to mitigate them are critical for decision -makers. In this regard, this study measured the societal impact by considering people's achievement/intoler-ance of survival-related activities and proposed an agent-based societal impact simulation model (ABSISM) for quantitative estimation of the impact. The ABSISM incorporated dynamic interactions between households' emergency behaviors, infrastructure disruption, and government countermeasures in typhoon disaster scenarios and designed decision rules for three types of agents: household, store, and shelter agents. Specifically, household agents acquire life-supporting resources (food and water) from store and/or shelter agents, and prioritize daily activities to perform under restricted resources by minimizing their experienced suffering level; store and shelter agents provide household agents with essential resources during a disaster. Additionally, the government's response measures (infrastructure recovery, forewarning information issuance, and distribution of supplies) were incorporated into the ABSISM as factors directly or indirectly influencing agents' behaviors. Finally, this study presented an illustrative case study of Osaka to demonstrate the ABSISM's practical applicability and examines the effectiveness of government countermeasures on reducing the societal impact, which could provide insightful information for emergency management and promotion of sustainable cities.

Automated summary

This study quantified the societal impacts of infrastructure disruptions by considering people's achievement/intolerance of survival-related activities and proposed an agent-based societal impact simulation model (ABSISM) for quantitative estimation of the impact. The ABSISM incorporated dynamic interactions between households' emergency behaviors, infrastructure disruption, and government countermeasures in typhoon disaster scenarios and designed decision rules for three types of agents: household, store, and shelter agents.