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Abstract
At a time when the impacts of climate change and increasing urbanization are making risk management more complex, there is an urgent need for tools to better support risk managers. One approach increasingly used in crisis management is preventive mass evacuation. However, to implement and evaluate the effectiveness of such strategy can be complex, especially in large urban areas. Modeling approaches, and in particular agent-based models, are used to support implementation and to explore a large range of evacuation strategies, which is impossible through drills. One major limitation with simulation of traffic based on individual mobility models is their capacity to reproduce a context of mixed traffic. In this paper, we propose an agent-based model with the capacity to overcome this limitation. We simulated and compared different spatio-temporal evacuation strategies in the flood-prone landlocked area of the Phúc Xá district in Hanoi. We demonstrate that the interaction between distribution of transport modalities and evacuation strategies greatly impact evacuation outcomes. More precisely, we identified staged strategies based on the proximity to exit points that make it possible to reduce time spent on road and overall evacuation time. In addition, we simulated improved evacuation outcomes through selected modification of the road network.
Author contributions
Kevin Chapuis: Conception and development of the original model and case study. Writing of the article and the documentation. Pham Minh-Duc: Development of the agent-based traffic model. Arthur Brugière: Development of the case study, model exploration and result mining. Jean-Daniel Zucker: Supervise model development and writing. Alexis Drogoul: Supervise model development. Pierrick Tranouez: Initial agent-based traffic model development and supervision. Éric Daudé: Conceptual development of the model. Patrick Taillandier: Development of the model, conception of the exploration and analysis, writing of the article.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data and codes availability statement
The data and codes that support the findings of this study are available at figshare following this doi (https://doi.org/10.6084/m9.figshare.16622437.v1). The packaged model can be run using the Gama platform, see https://gama-platform.org to download the proper version. A complete readme file has been added to the repository to ease the reproducibility of model results and figures presented in this proposal.
Notes
1 Which is actually a length given that Roads are represented as lines.
Additional information
Funding
Notes on contributors
Kevin Chapuis
Kevin Chapuis, after a master graduation in social sciences and philosophy, has done a PhD in computer science at University Pierre et Marie Curie (Paris 6) in 2016. Nowadays, he works on the interface between companion modeling and intensive analysis and exploration of complex descriptive ABM to support sustainable development
Pham Minh-Duc
Pham Minh-Duc earned a bachelorvelopment of the original model and case study. Writing of the article and the documentationexploratanoi, and is now studying Data Science at EURECOM. He worked at IRD as an engineer to implement agent-based traffic meta-models which are better suited for traffic simulation in Vietnam.
Arthur Brugière
Arthur Brugière, after a double master graduation in Computer Science in France and Vietnam, is currently doing a PhD in computer science in cotutelle at Sorbonne University (France) and Thuyloi University (Vietnam). His research subject focus on multi-level dynamical coupling in agent based models.
Jean-Daniel Zucker
Jean-Daniel Zucker holds an engineer degree in Computer Science and a PhD in Machine Learning. He is a Senior Researcher at the national institute of Research for development (IRD) focusing in Artificial Intelligence and Machine Learning (both interpretable or not) for Modelling Complex Systems and Medical Decision. His application domains are mainly bioinformatics decision support and environmental decision support (Floods, Tsunami and dengue epidemic in South East Asia).
Alexis Drogoul
Alexis Drogoul holds a PhD in Computer Science. He is a Senior Researcher at IRD and his work concerns the development of software tools (such as GAMA, http://gama-platform.org) for modelling and simulating socio-environmental systems for environmental decision support, particularly in Vietnam, where he has been working since 1999 with numerous partners.
Pierrick Tranouez
Pierrick Tranouez holds a PhD in Computer Science. He is a researcher at LITIS lab from University of Rouen Normandy. He is a specialist of multiscale agent-based models and simulations.
Éric Daudé
Éric Daudé is a Senior Researcher in geography at CNRS. His research focuses on the analysis of territorial risks, the study of surveillance and crisis management using agent-based simulation models. He is the scientific coordinator of the ESCAPE project.
Patrick Taillandier
Patrick Taillandier is a senior researcher in computer science in the unit of Mathematics and Applied Computer Science of Toulouse (MIAT) of the National Research Institute for Agriculture, Food and the Environment (INRAE). He spent five years at the University of Rouen, where he was an Associate Professor. Since October 2020, he has been hosted in Vietnam by the IRD and the University of Thuy Loi. His research focuses on agent-based simulation and has been particularly interested in recent years in the modeling of human behavior. He is one of the main developers of the GAMA platform.