An Agent-Based Simulation to Explore Communication in a System to Control Urban Traffic with Smart Traffic Lights
Abstract Populational growth increases the number of cars and makes the transport infrastructure increasingly saturated. The control of traffic lights by intelligent software is a promising way to solve the problem caused by this situation. This article addresses this problem that occurs in urban traffic. An agent-based simulation of an urban traffic control system is proposed. The solution is offered as intelligent traffic lights as agents to alleviate traffic congestion at a given location. Each agent controls a crossing and maintains communication with agents from other corners. Thus, they can have greater control of a larger area and identify patterns that can help them to solve congestion problems. The results of our simulated experiments point to the improvement of the urban traffic when using the proposed Multiagent System, in comparison with an approach that uses crossing agents without communication and other that implements static traffic lights.
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Lopez, P. A., Behrisch, M., Bieker-Walz, L., Erdmann, J., Flötteröd, Y.-P., Hilbrich, R., Lücken, L., Rummel, J., Wagner, P., and WieBner, E., 2018. Microscopic traffic simulation using sumo. In 2018 21st International Conference on Intelligent Transportation Systems (ITSC), pages 2575–2582. IEEE.
Lupasc,A. et al., 2005. How to improve artificial intelligence through web. Acta Universitatis Danubius. Œconomica, 1(1):92–104.
Marín-Lora, C., Chover, M., Sotoca, J., and García, L., 2019. A game engine to make games as multiagent systems. Advances in Engineering Software, 140. doi:10.1016/j.advengsoft.2019.102732.
O’Brien, P. D. and Nicol, R. C., 1998. FIPA—towards a standard for software agents. BT Technology Journal, 16(3):51–59.
Timóteo, I. J., Araújo, M. R., Rossetti, R. J., and Oliveira, E. C., 2010. TraSMAPI: An API oriented towards Multi-Agent Systems real-time interaction with multiple Traffic Simulators. In 13th International IEEE Conference on Intelligent Transportation Systems, pages 1183–1188. IEEE.
Watkins, C. J. and Dayan, P., 1992. Q-learning. Machine learning, 8(3-4):279–292.
Wegener, A., Piórkowski, M., Raya, M., Hellbrück, H., Fischer, S., and Hubaux, J.-P., 2008. TraCI: an interface for coupling road traffic and network simulators. In Proceedings of the 11th communications and networking simulation symposium, pages 155–163.
Wu, Q., Wu, J., Shen, J., Yong, B., and Zhou, Q., 2020. An Edge Based Multi-Agent Auto Communication Method for Traffic Light Control. Sensors, 20(15). ISSN 1424-8220. doi:10.3390/s20154291.
Behrisch, M., Bieker, L., Erdmann, J., and Krajzewicz, D., 2011. SUMO–simulation of urban mobility: an overview. In Proceedings of SIMUL 2011, The Third International Conference on Advances in System Simulation. ThinkMind.
Bellifemine, F., Bergenti, F., Caire, G., and Poggi, A., 2005. JADE—a java agent development framework. In Multi-agent programming, pages 125–147. Springer.
Bennett, J., 2010. OpenStreetMap. Packt Publishing Ltd.
Bull, A., CEPAL, N. et al., 2003. Traffic Congestion: The Problem and how to Deal with it. ECLAC.
Chow, A. H., Santacreu, A., Tsapakis, I., Tanasaranond, G., and Cheng, T., 2014. Empirical assessment of urban traffic congestion. Journal of advanced transportation, 48(8):1000–1016.
Fernández-Isabel, A., Fuentes-Fernández, R., and Martín de Diego, I., 2020. Modeling multi-agent systems to simulate sensor-based Smart Roads. Simulation Modelling Practice and Theory, 99:101994. ISSN 1569-190X. doi:10.1016/j.simpat.2019.101994.
Fuelber, D. F. and Frozza, R., 2017. Gerenciamento de tráfego urbano empregando sistemas multiagentes: análise qualitativa de trabalhos relacionados. Enegep.
González-Briones, A., De La Prieta, F., Mohamad, M. S., Omatu, S., and Corchado, J. M., 2018. Multi-Agent Systems Applications in Energy Optimization Problems: A State-of-the-Art Review. Energies, 11(8). ISSN 1996-1073. doi:10.3390/en11081928.
Haklay, M. and Weber, P., 2008. Openstreetmap: User-generated street maps. IEEE Pervasive computing, 7(4):12–18.
Junior, G. D., Frozza, R., and Molz, R. F., 2015. Simulação de controle adaptativo de tráfego urbano por meio de sistema multiagentes e com base em dados reais. Revista Brasileira de Computação Aplicada, 7(3):65–81. doi:10.5335/rbca.2015.4697
Liu, J., Wan, J., Jia, D., Zeng, B., Li, D., Hsu, C.-H., and Chen, H., 2017. High-efficiency urban traffic management in context-aware computing and 5G communication. IEEE Communications Magazine, 55(1):34–40.
Lopez, P. A., Behrisch, M., Bieker-Walz, L., Erdmann, J., Flötteröd, Y.-P., Hilbrich, R., Lücken, L., Rummel, J., Wagner, P., and WieBner, E., 2018. Microscopic traffic simulation using sumo. In 2018 21st International Conference on Intelligent Transportation Systems (ITSC), pages 2575–2582. IEEE.
Lupasc,A. et al., 2005. How to improve artificial intelligence through web. Acta Universitatis Danubius. Œconomica, 1(1):92–104.
Marín-Lora, C., Chover, M., Sotoca, J., and García, L., 2019. A game engine to make games as multiagent systems. Advances in Engineering Software, 140. doi:10.1016/j.advengsoft.2019.102732.
O’Brien, P. D. and Nicol, R. C., 1998. FIPA—towards a standard for software agents. BT Technology Journal, 16(3):51–59.
Timóteo, I. J., Araújo, M. R., Rossetti, R. J., and Oliveira, E. C., 2010. TraSMAPI: An API oriented towards Multi-Agent Systems real-time interaction with multiple Traffic Simulators. In 13th International IEEE Conference on Intelligent Transportation Systems, pages 1183–1188. IEEE.
Watkins, C. J. and Dayan, P., 1992. Q-learning. Machine learning, 8(3-4):279–292.
Wegener, A., Piórkowski, M., Raya, M., Hellbrück, H., Fischer, S., and Hubaux, J.-P., 2008. TraCI: an interface for coupling road traffic and network simulators. In Proceedings of the 11th communications and networking simulation symposium, pages 155–163.
Wu, Q., Wu, J., Shen, J., Yong, B., and Zhou, Q., 2020. An Edge Based Multi-Agent Auto Communication Method for Traffic Light Control. Sensors, 20(15). ISSN 1424-8220. doi:10.3390/s20154291.
de Oliveira, M., Teixeira, R. ., Sousa, R., & Tavares Gonçalves, E. J. (2021). An Agent-Based Simulation to Explore Communication in a System to Control Urban Traffic with Smart Traffic Lights. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 10(3), 209–225. https://doi.org/10.14201/ADCAIJ2021103209225
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