Some propositions to find optimal conditions to simulate a flexible transport using an Agent-Based Model

This paper presents a method to assess the sensitivity of a flexible transport model based on agents and simulated using NetLogo. We simulate and we analyse a set of 124 transportation scenarios on several virtual networks and we assess their performance. Our main objective is to detect thresholds in the system scalability and efficiency. The research leads to three main results: (i) using Agent-Based Model, it is possible to significantly improve the global transport efficiency without any general objective function, (ii) there exists an optimal balance between the demand frequency and the number of simulated agents to simulate and perform a good flexible transport, (ii) to some extent, the network topological structure plays a non-negligible role in transport efficiency

Mise en place et évaluation d'un algorithme de répartition de charge pour les plateformes de simulations distribuées basées sur les systèmes multi-agents

International audienceCet article traite de la problématique de la répartition de charge dans les systèmes multi-agents à travers un algorithme qui assure la distribution de ces agents. Le besoin est né de l'observation de fréquents problèmes de surcharge lors de simulations basées sur ces systèmes multi-agents. Miro, qui est une plateforme de simulation à grande échelle de la mobilité urbaine en est un exemple concret. La difficulté de ces travaux se situe dans la considération des spécificités des plateformes de simulation orientée agent : autonomie des entités à distribuer et forte imprévisibilité du système. Nous adaptons un algorithme de répartition de charge appelé Comet aux spécificités des simulations distribuées à base d'agents. Cet algorithme est basé sur l'emploi d'un indicateur appelé " crédit " qui pour chaque agent quantifie son affinité pour chaque machine et détermine les meilleurs agents candidats à la migration. Hormis l'algorithme en lui même, ce document en présente une implémentation et une évaluation sur un simulateur développé avec Netlogo. Le but final est d'identifier les paramètres à prendre en considération pour assurer le bon fonctionnement de l'algorithme lors de son implémentation sur une plateforme réelle de simulation

An Agent-Based Framework for Urban Mobility Simulation

International audienceMobility study is composed of many research areas which one interests us: urban mobility. In the literature, urban mobilities are represented by analytical techniques like stochastic laws or they are defined by simulation tools like Multi-Agents Systems (MAS). The goal of our work is to define citizen behaviour in order to observe population dynamics by a simulation. This strategy is facilitated by a meta-model and a toolkit which are used with a particular method. The latter begins by a conceptual representation of each mobile and finishes by a mobility simulator. This paper aims at describing the mobility simulation toolkit. Thanks to this framework, mobility simulator development is sim- plified. It allows us to create distributed applications which are based on MAS

How to assess the robustness of a flexible transport using an Agent Based Model? : Some observations on optimal conditions of simulation.

This paper presents a method to evaluate the robustness of a cooperating flexible transport system based on agents (taxis and clients) and simulated using NetLogo. Analysing a set of 124 scenarios of simulations on a range of synthetic populations (clients) and on various space networks organizations, we assess the sensitivity of a transportation model we proposed. Our main objective is to detect robustness thresholds in flow configurations and system efficiency. The research leads to two main results: (i) there exists an optimal balance between the frequency of system iterations (number of clients generations) and the total number of clients involved in simulations, (ii) to some extend, the network topological structure plays a non negligible role in transport efficiency.Cet article présente une méthode pour évaluer la robustesse d'un service de transport flexible modélisé en multi-agent et simulé sur la plate-forme Netlogo. Nous analysons la sensibilité du modèle grâce à 124 scénarios de simulation, chacun d'eux intégrant différentes quantités de population synthétique (les clients), combinées à quatre formes d'organisation spatiale théoriques.Notre objectif est de révéler des seuils de robustesse au delà desquels le système peut être considéré comme efficace ou non. À l'aide de plusieurs indicateurs, nous montrons qu'il existe un ratio optimal entre la fréquence et la quantité de client à créer. Nous expliquons aussi dans quelle mesure la forme des réseaux routiers influence l'efficacité du modèle

A Video Transmission Framework Using Components and Multi-Agent Systems

International audienceThis paper presents an application of video transmission over Internet, which goal is to be used in a cooperative plat- form. This application uses proxies during the transmission to adapt the video (changing the size, the framerate and/or the encoding format). Adaptation is a necessity in this kind of application, due to the diversity of receivers (computers, mobile phones, PDA . . . ). During the design process, we chose to use component ori- ented programming and multi-agent systems. We present here how these two paradigms help us to have a flexible and evolutive application, and, for each transmission?s step, what is the most appropriated solution. At the end, we also present tests that have been made to evaluate the power needed by the proxies in order to discuss about benefits that can be brought by our architecture

L’apport de la simulation multi-agent du trafic routier pour l’estimation des pollutions atmosphériques automobiles

National audienceLa pollution atmosphérique est aujourd’hui considérée comme cancérigène pour la santé humaine (OMS, 2013). Avec le bruit, elle est l’une des premières nuisances directement ressenties par les populations en milieu urbain. Son évaluation présente un véritable enjeu pour les pouvoirs publics afin de mieux en identifier ses sources, ses impacts en vue de définir des politiques territoriales (PDU, cadastre d’émission). A l’échelle locale, la pollution atmosphérique est à relier directement à l’intensité des sources d’émissions qui vont accentuer, ou non, la qualité de l’air extérieure (Elichegaray, 2010) . En milieu urbain, le premier contributeur en émission de NOx, CO, ou PM10 dans l’atmosphère est le trafic routier (CITEPA, 2014)

Formalismes de description des modèles agent

International audienceCe chapitre a pour but de présenter les bonnes pratiques et l’apport de la formalisationdans le domaine de la modélisation de systèmes multi-agents (SMA). Pour cela,les auteurs rappellent dans un premier temps l’intérêt de modéliser des systèmes enmettant en perspective les paradigmes associés à la démarche multi-agents. Il est alorsargumenté que l’utilisation des langages de modélisation graphique permettent unmeilleur échange entre les partenaires intervenant dans la conception d’un SMA (...)

Mapping and Describing Geospatial Data to Generalize Complex Models: The Case of LittoSIM-GEN

For some scientific questions, empirical data are essential to develop reliable simulation models. These data usually come from different sources with diverse and heterogeneous formats. The design of complex data-driven models is often shaped by the structure of the data available in research projects. Hence, applying such models to other case studies requires either to get similar data or to transform new data to fit the model inputs. It is the case of agent-based models (ABMs) that use advanced data structures such as Geographic Information Systems data. We faced this problem in the LittoSIM-GEN project when generalizing our participatory flooding model (LittoSIM) to new territories. From this experience, we provide a mapping approach to structure, describe, and automatize the integration of geospatial data into ABMs

Simulating Urban Growth with Raster and Vector models: A case study for the city of Can Tho, Vietnam

Urban growth has been widely studied and many models (in particular Cellular Automata and Agent-Based Models) have been developed. Most of these models rely on two representations of the geographic space: raster and vector. Both representations have their own strengths and drawbacks. The raster models are simpler to implement and require less data, which explains their success and why most of urban growth models are based on this representation. However, they are not adapted to microscopic dynamics such as, for example, the construction of buildings. To reach such goal, a vector-based representation of space is mandatory. However, very few vector models exist, and none of them is easily adaptable to different case studies. In this paper, we propose to use a simple raster model and to adapt it to a vector representation of the geographic space and processes allowing studying urban growth at fine scale. Both models have been validated by a case study concerning the city of Can Tho, Vietnam