Participatory Modeling and Simulation with the GAMA Platform

Taillandier, Patrick; Grignard, Arnaud; Marilleau, Nicolas; Philippon, Damien; Huynh, Quang-Nghi; Gaudou, Benoît; Drogoul, Alexis

doi:10.18564/jasss.3964

Cited by 32 publications

(27 citation statements)

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“…Additionally, some movement behaviors are already pre-coded and can be easily reused. Many transportation models were produced in the last years with the GAMA platform [14]. However, these models have not focused on the impact of future mobility options and they have not provided a generic framework to investigate potential impacts of these options.…”

Section: Limits Of the Existing Tools For Traffic Simulationmentioning

confidence: 99%

The Impact of New Mobility Modes on a City: A Generic Approach Using ABM

Grignard¹,

Alonso²,

Taillandier³

et al. 2018

Springer Proceedings in Complexity

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Mobility is a key issue for city planners. Being able to evaluate the impact of its evolution is complex and involves many factors including new technologies like electric cars, autonomous vehicles and also new social habits like vehicle sharing. We need a better understanding of different scenarios to improve the quality of long-term decisions. Computer simulations can be a tool to better understand this evolution, to discuss different solutions and to communicate the implications of different decisions. In this paper, we propose a new generic model that creates an artificial micro-world which allows the modeler to create and modify new mobility scenarios in a quick and easy way. This not only helps to better understand the impact of new mobility modes on a city, but also fosters a better-informed discussion of different futures. Our model is based on the agent-based paradigm using the GAMA Platform. It takes into account different mobility modes, people profiles, congestion and traffic patterns. In this paper, we review an application of the model of the city of Cambridge.

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Section: Limits Of the Existing Tools For Traffic Simulationmentioning

confidence: 99%

The Impact of New Mobility Modes on a City: A Generic Approach Using ABM

Grignard¹,

Alonso²,

Taillandier³

et al. 2018

Springer Proceedings in Complexity

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“…There are a lot of simulations that used an agent-based model to implement. Patrick [4] simulated traffic using an open-source tool (GPL), integrated into the GAMA modeling. He provided a modeling approach that is particularly well-fitted for microsimulation.…”

Section: Related Workmentioning

confidence: 99%

Covid-19 Disease Simulation using GAMA platform

Duong

Sơn

Dinh

2020

2020 International Conference on Computational Intelligence (ICCI)

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In less than three months after its emergence in China, the Covid-19 pandemic has spread to at least 180 countries. In the absence of previous experience with this new disease, public health authorities have implemented many experiments in a short period and, in a mostly uninformed way, various combinations of interventions at different scales. These include a ban on large gatherings, closure of bordersindividual and collective containment, monitoring of population movements, social tracing, social distancing, etc. However, as the pandemic is progressing, data are collected from various sources. On the one hand, authorities allow to make informed adjustments to the current and planned interventions and reveal them. On the other hand, an urgent need for tools and methodologies that enable fast analysis, understanding, comparison, and forecasting of the effectiveness of the responses against COVID-19 across different communities and contexts. In this perspective, computational modeling appears as invaluable leverage as it allows us to explore in silico a range of intervention strategies before the potential phase of field implementation.

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“…Among the existing open-source generic platforms such as Mason, Netlogo or Cormas, one of the most suitable for traffic simulation is GAMA [10]. Indeed GAMA provides modelers a complete modeling language (GAML: GAma Modeling Language) and different features that can be used by modelers to develop traffic models [20]. It has already been used for several traffic models such as the ones proposed by [7,16].…”

Section: Agent-based Urban Traffic Frameworkmentioning

confidence: 99%

“…Vehicle operational level rely on the GAMA advanced driving skill, which consists in attributes and methods dedicated to the driving behavior of agent. [20] proposal provides more details about additions brought by the advanced driving skill.…”

Section: Mobile Entities: People and Vehicle Agentsmentioning

confidence: 99%

A Multi-modal Urban Traffic Agent-Based Framework to Study Individual Response to Catastrophic Events

Chapuis¹,

Taillandier²,

Gaudou³

et al. 2018

Lecture Notes in Computer Science

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Open Archive Toulouse Archive OuverteOATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible To cite this version: Chapuis, KévinAbstract. Urban traffic is made of a variety of mobility modes that have to be taken into account to explore the impact of catastrophic event. From individual mobility behaviors to macroscopic traffic dynamics, agent-based modeling provides an interesting conceptual framework to study this question. Unfortunately, most proposals in the domain do not provide any simple way to model these multi-modal trajectories, and thus fell short at simulating in a credible way the outcomes of a catastrophic event, like natural or industrial hazards. This paper presents an agent-based framework implemented with the GAMA modeling platform that aims at overcoming this lack. An application of this model for the study of flood crisis in a district of Hanoi (Vietnam) is presented.

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Participatory Modeling and Simulation with the GAMA Platform

Cited by 32 publications

References 0 publications

The Impact of New Mobility Modes on a City: A Generic Approach Using ABM

The Impact of New Mobility Modes on a City: A Generic Approach Using ABM

Covid-19 Disease Simulation using GAMA platform

A Multi-modal Urban Traffic Agent-Based Framework to Study Individual Response to Catastrophic Events

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