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Integration of Simulation Techniques: System Dynamics and Intelligent Agents Applied to a Case Study

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Computational Collective Intelligence (ICCCI 2019)

Abstract

Performing macro and microscopic analysis of a complex system, as in the case of measuring variables of quality of service provided by system of public passenger transport, is a problem, even more, if it is about integration of information produced in a minimum period of time that should serve as an input for realization of macroscopic analysis of this information for a longer period of time. The main goal of this paper is describe integration of two paradigms of simulation, one based on intelligent agents for microscopic analysis of the behaviour of selected system of urban public transport in one day of its activity, and another, based on system dynamics, to perform a macroscopic analysis, initially taking into account information from one day of system’s operation. Results of pilot study show that data obtained from the simulation with agents are the starting point for realization of wider analysis by allowing simulation of the system in a period of 180 days.

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References

  1. Saprykin, O., Saprykina, O.: Validation of transport infrastructure changes via microscopic simulation: a case study for the city of Samara, Russia. In: 2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, pp. 774–779. Napoles, Italy (2017)

    Google Scholar 

  2. Andelfinger, P., et al.: Incremental calibration of seat selection preferences in agent-based simulations of public transport scenarios. In: 2018 Winter Simulation Conference (WSC), pp. 833–844. Gothenburg, Sweden (2018)

    Google Scholar 

  3. Golan, B.-D., Eran, B.-E., Itzhak, B.: Assessing the impacts of dedicated bus lanes on urban traffic congestion and modal split with an agent-based model. Procedia Comput. Sci. 130, 824–829 (2018)

    Article  Google Scholar 

  4. Inturri, G., et al.: Multi-agent simulation for planning and designing new shared mobility services. Res. Transp. Econ. 73, 34–44 (2019)

    Article  Google Scholar 

  5. Shuwei, J., Guangle, Y., Aizhong, S., Jun, Z.: A system dynamics model for determining the traffic congestion charges and subsidies. Arab. J. Sci. Eng. 42(12), 5291–5304 (2017)

    Google Scholar 

  6. Sayyadi, R., Awasthi, A.: A system dynamics-based simulation model to evaluate regulatory policies for sustainable transportation planning. Int. J. Model. Simul. 37(1), 25–35 (2017). https://doi.org/10.1080/02286203.2016.1219806

    Article  Google Scholar 

  7. Alsobky, A., Hrkút, P., Mikušová, M.: A smart application for university bus routes optimization. In: Kováčiková, T., Buzna, Ľ., Pourhashem, G., Lugano, G., Cornet, Y., Lugano, N. (eds.) INTSYS 2017. LNICST, vol. 222, pp. 12–20. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-93710-6_2

    Chapter  Google Scholar 

  8. Mikusova, M.: Proposal of benchmarking methodology for the area of public passenger transport. Periodica Polytech. Transp. Eng. 47(2), 166–170 (2019). https://doi.org/10.3311/PPtr.10271

    Article  Google Scholar 

  9. Jankowska, D., Mikusova, M., Wacowska-Ślęzak, J.: Mobility issues in selected regions of poland and slovakia – outcomes of international project SOL (save our lives) survey. Periodica Polytech. Transp. Eng. 43(2), 67–72 (2015). https://doi.org/10.3311/PPtr.7580

  10. Mikusova, M.: Sustainable structure for the quality management scheme to support mobility of people with disabilities. Procedia – Soc. Behav. Sci. 160, 400–409 (2014). https://doi.org/10.1016/j.sbspro.2014.12.152

    Article  Google Scholar 

  11. Mikusova, M., Gnap, J.: Experiences with the implementation of measures and tools for road safety improvement. In: XII Congreso de ingeniería del transporte. 7, 8 y 9 de Junio, Valencia (Spain). Editorial Universitat Politècnica de València, pp. 1632–1638 (2016). https://doi.org/10.4995/cit2016.2015.2555

  12. Forrester, J.W.: Industrial Dynamics. Productivity Press, Cambridge (1986)

    Google Scholar 

  13. Berthet, S., Demazeau, Y., Boissier, O.: Knowing each other better. In: 11th International Workshop on Distributed Artificial Intelligence. Glen Arbor (1992)

    Google Scholar 

  14. Shoham, Y.: Agent-oriented programming. Technical Report STAN-CS-1335-90. Computer Science Department. Stanford University, Stanford. CA (1990)

    Google Scholar 

  15. Callejas-Cuervo, M., Valero-Bustos, H.A., Alarcón-Aldana, A.C., Mikušova, M.: Measurement of service quality of a public transport system, through agent-based simulation software. In: Huk, M., Maleszka, M., Szczerbicki, E. (eds.) ACIIDS 2019. SCI, vol. 830, pp. 335–347. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-14132-5_27

    Chapter  Google Scholar 

  16. Callejas-Cuervo, M., Valero-Bustos, H.A., Alarcón-Aldana, A.C.: Simulación basada en dinámica de sistemas y agentes inteligentes, aplicada a un sistema complejo. Edn. UPTC, Tunja, Boyacá, Colombia (2018)

    Google Scholar 

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Correspondence to Miroslava Mikusova .

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Mikusova, M., Callejas-Cuervo, M., Valero-Bustos, H.A., Alarcón-Aldana, A.C. (2019). Integration of Simulation Techniques: System Dynamics and Intelligent Agents Applied to a Case Study. In: Nguyen, N., Chbeir, R., Exposito, E., Aniorté, P., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2019. Lecture Notes in Computer Science(), vol 11684. Springer, Cham. https://doi.org/10.1007/978-3-030-28374-2_44

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  • DOI: https://doi.org/10.1007/978-3-030-28374-2_44

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