JiaweiXue / DIRSIM

An agent-based model that simulates how social-physical multilayer system recovers after a disaster

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

DIRSIM: Disaster Infrastructure Recovery Simulator

An agent-based model that simulates how a socio-physical multilayer system recovers after a disaster.

Project

  • National Science Foundation 1638311 (CRISP Type 2/Collaborative Research: Critical Transitions in the Resilience and Recovery of Interdependent Social and Physical Networks).

Introduction

  • DIRSIM simulates the post-disaster recovery (PDR) of the social-physical system, enabling us to understand its details and evaluate various policies.
  • It is composed of three successive components: (1) network definition; (2) agent interaction modeling; and (3) agent-based simulation.
  • Network definition: build the three-layer network using mobility phone location data, Point-of-interest (POI) foot traffic data.
  • Agent interaction modeling: specify how agents interact with each other during the PDR process.
  • Agent-based simulation: simulate the recovery of each agent in the three-layer network temporally.

Publication

An Agent-based Model of Post-disaster Recovery in Multilayer Socio-physical Networks. Jiawei Xue, Sangung Park, Washim Uddin Mondal, Sandro Martinelli Reia, Tong Yao, Satish V. Ukkusuri*. Sustainable Cities and Society. 2024.

Requirements

  • Python 3.6
  • Mesa 0.9.0

Directory Structure

  • 0_data. Released: the shapefile of Texas; the recovery level of physical infrastructures; Not released: mobile phone location data; POI data from SafeGraph (https://www.safegraph.com/).

  • 1_data_preprocessing. extract mobile phone location data within the five counties.

  • 2_network_constructor. define agents in the three-layer network.

  1. Codes in "network_constructor/home/" define nodes and edges in the human layer.

  2. Codes in "network_constructor/poi/" define nodes and edges in the social infrastructure layer.

  • 3_model. the code under "model/" is our ABM model. It takes the outputs of previous codes and simulates the dynamic of the three-layer system.

  • 4_validation. validate the simulation outcome with ground truth from mobile phone location and POI data.

  • 5_results. simulate the system recovery under the nine scenarios.

  • 6_figures. figures in this GitHub repository.

Overview

Overview of used data, three-layer socio-physical network, and the agent-based model (ABM) for post-disaster recovery.

Simulation Flowchart

The long-term PDR process. (a, b) The dynamics of recovery levels (i.e. $r_{a}(t)$) for agents representing users and POIs. (c) The flowchart that summarizes the procedure of agent interactions in the PDR process.

License

MIT license

About

An agent-based model that simulates how social-physical multilayer system recovers after a disaster

License:MIT License


Languages

Language:HTML 99.4%Language:Python 0.6%