Simulação baseada em agentes para o estudo de políticas de diminuição de congestionamentos
Resumo
O congestionamento é um crescente problema do cotidiano das pessoas. Diversas políticas têm sido propostas para sua minimização, desde mudanças na infra-estrutura, até medidas para controlar o número de veículos nas ruas. O estudo dessas políticas torna-se complexo a medida que seu custo e impacto aumentam. Simulações baseadas em agentes constituem uma importante ferramenta, pois permitem estudar diferentes estratégias de melhoria no trânsito com baixo custo e tempo. Este trabalho propõe um ambiente simulação baseada em agentes, com o objetivo de estudar políticas de minimização de congestionamentos, como o posicionamento de postos de pedágio e a implantação de pistas exclusivas para veículos de alta ocupação.Referências
Barceló, J. (2010). Fundamentals of Traffic Simulation. Springer-Verlag New York.
Burghout, W., Koutsopoulos, H. N., and Andreasson, I. (2006). A discrete-event mesoscopic traffic simulation model for hybrid traffic simulation. In Intelligent Transportation Systems Conference, 2006. ITSC’06. IEEE, pages 1102–1107. IEEE.
Champion, A., Mandiau, R., Kolski, C., Heidet, A., and Kemeny, A. (1999). Traffic generation with the scaner ii simulator: towards a multi-agent architecture. In Driving Simulation Conference, pages 311–324.
Clark, J. and Daigle, G. (1997). The importance of simulation techniques in its research and analysis. In Proceedings of the 29th conference on Winter simulation, pages 1236–1243. IEEE Computer Society.
Erick, M., Suppasri, A., Imamura, F., and Koshimura, S. (2012). Agent-based simulation of the 2011 great east japan earthquake/tsunami evacuation: An integrated model of tsunami inundation and evacuation. Journal of Natural Disaster Science, 34(1):41–57.
Kesting, A. and Treiber, M. (2008). Calibrating car-following models by using trajectory data: Methodological study. Transportation Research Record: Journal of the Transportation Research Board, (2088):148–156.
Patriksson, M. (2015). The traffic assignment problem: models and methods. Courier Dover Publications.
Pipes, L. (1966). Car following models and the fundamental diagram of road traffic. Transportation Research 1.
Smock, R. (1962). An iterative assignment approach to capacity restraint on arterial networks. Highway Research Board Bulletin, (347).
Sutiono, A. B., Suwa, H., and Ohta, T. (2007). Multi agent based simulation for typhoid fever with complications: An epidemic analysis. In Proceedings of the 51st Annual Meeting of the ISSS-2007, Tokyo, Japan, volume 51.
Wooldridge, m. (2002). An Introduction to MultiAgent Systems. John Wiley and Sons Ltd.
Burghout, W., Koutsopoulos, H. N., and Andreasson, I. (2006). A discrete-event mesoscopic traffic simulation model for hybrid traffic simulation. In Intelligent Transportation Systems Conference, 2006. ITSC’06. IEEE, pages 1102–1107. IEEE.
Champion, A., Mandiau, R., Kolski, C., Heidet, A., and Kemeny, A. (1999). Traffic generation with the scaner ii simulator: towards a multi-agent architecture. In Driving Simulation Conference, pages 311–324.
Clark, J. and Daigle, G. (1997). The importance of simulation techniques in its research and analysis. In Proceedings of the 29th conference on Winter simulation, pages 1236–1243. IEEE Computer Society.
Erick, M., Suppasri, A., Imamura, F., and Koshimura, S. (2012). Agent-based simulation of the 2011 great east japan earthquake/tsunami evacuation: An integrated model of tsunami inundation and evacuation. Journal of Natural Disaster Science, 34(1):41–57.
Kesting, A. and Treiber, M. (2008). Calibrating car-following models by using trajectory data: Methodological study. Transportation Research Record: Journal of the Transportation Research Board, (2088):148–156.
Patriksson, M. (2015). The traffic assignment problem: models and methods. Courier Dover Publications.
Pipes, L. (1966). Car following models and the fundamental diagram of road traffic. Transportation Research 1.
Smock, R. (1962). An iterative assignment approach to capacity restraint on arterial networks. Highway Research Board Bulletin, (347).
Sutiono, A. B., Suwa, H., and Ohta, T. (2007). Multi agent based simulation for typhoid fever with complications: An epidemic analysis. In Proceedings of the 51st Annual Meeting of the ISSS-2007, Tokyo, Japan, volume 51.
Wooldridge, m. (2002). An Introduction to MultiAgent Systems. John Wiley and Sons Ltd.
Publicado
04/05/2017
Como Citar
HABITZREUTER, Jandir Luiz; SOUZA, Marcelo de.
Simulação baseada em agentes para o estudo de políticas de diminuição de congestionamentos. In: WORKSHOP-ESCOLA DE SISTEMAS DE AGENTES, SEUS AMBIENTES E APLICAÇÕES (WESAAC), 11. , 2017, São Paulo/SP.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2017
.
p. 239-244.
ISSN 2326-5434.
DOI: https://doi.org/10.5753/wesaac.2017.33249.
