Abstract
Management and control of transportation systems benefit from simulation modeling. The design of the corresponding models is difficult because of their complexity. Multi-agent systems cope with this problem by a divide-and-conquer approach. However, agent model design is still quite a challenge. In this paper, we propose a layered architecture for agents where each component is a kind of a stack-based state machine of our own. This model complements extended finite-state machines with some basic state stack operations that enable not only dealing with hierarchy but also with planning, which is a key element for belief-desire-intention (BDI) agents. Special care was taken to make the representation of these extended finite-state stack machines (EFS2M) simple so that their programming is straightforward. Through an educational example we show how such class of models are, and the potentiality of the solution. The taxi fleet simulation model is a metaphor for transportation systems in structured environments like factories or warehouses but can also be used as a vehicle traffic simulator. As for the latter case, we illustrate how it can be used to determine the efficiency and the quality of service of a taxi fleet in an urban area.
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Data have been obtained from simulation with the software that has been developed and which is publicly available.
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The software [22] is available at: https://sourceforge.net/projects/maslua
References
Berry G (2004) The Esterel v5 Language Primer Version v5 91. Collège de France.
Boukredera D, Aknine S, Maamri R (2012) Modeling temporal aspects of contract net protocol using timed colored petri nets. STAIRS. https://doi.org/10.3233/978-1-61499-096-3-83
Casas J, Ferrer JL, Garcia D, Perarnau J, Torday A (2010) Traffic Simulation with Aimsun. In: Barceló J (ed) Fundamentals of Traffic Simulation International Series in Operations Research & Management Science, vol 145. Springer, New York
Hörl S (2017) Agent-based simulation of autonomous taxi services with dynamic demand responses. In: Hörl S (ed) 6th Int’l. Wkshp. on Agent-based Mobility Traffic and Transportation Models, Methodologies and Applications (ABMTrans), Procedia Computer Science 109C. Elsevier, Amsterdam, pp 899–904
Kim H, Oh J-S, Jayakrishnan R (2005) Effect of taxi information system on efficiency and quality of taxi services. Transp Res Rec. https://doi.org/10.3141/1903-11
Kim KH, Jeon SM, Ryu KR (2011) Deadlock prevention for automated guided vehicles in automated container terminals. In: Kim KH, Günther HO (eds) Container Terminals and Cargo Systems. Springer, Berlin
Li ZW, Zhou MC (2009) Deadlock resolution in automated manufacturing systems– A novel Petri net approach. Int J Prod Res 48:5541–5542
Nguyen J, Powers S T, Urquhart N, Farrenkopf T, Guckert M (2021) An Overview of Agent-based Traffic Simulators 51-56 15 Feb. 2021.
Perronnet F, Buisson J, Lombard A, Abbas-Turki A, Ahmane M, Moudni A (2018) Deadlock prevention of self-driving vehicles in a network of intersections. IEEE Trans Intell Transport Syst. https://doi.org/10.1109/TITS.2018.2886247
Postorino M, Sarné G (2016) Agents meet Traffic Simulation, Control and Management: A Review of Selected Recent Contributions. In: 17th Workshop “From Objects to Agents”, vol. 1664, CEUR Workshop Proceedings, pp. 112–117. Catania (Italy), July 2016.
Ptolemaeus C, Editor (2014) System Design, Modeling, and Simulation Using Ptolemy II, Ptolemy.org.
Qin G, Li T, Yu B, Wang Y, Huang Z, Sun J (2017) Mining factors affecting taxi drivers’ incomes using GPS trajectories. Transp Res Part C Emerg Technol 79:103–118. https://doi.org/10.1016/j.trc.2017.03.013
Ribas-Xirgo Ll (2020) MASLua Homepage, https://sourceforge.net/projects/maslua, created 2020/09/03.
Ribas-Xirgo Ll (2021) Multi-agent System Model of Taxi Fleets. In: Bergasa LM, Ocaña M, Barea R, López-Guillén E, Revenga P (eds) Advances in Physical Agents II WAF 2020 Advances in Intelligent Systems and Computing, vol 1285. Springer, Cham
Rivas-Alonso D, Das P, Saiz-Alcaine J, Ribas-Xirgo Ll (2018) Synthesis of Controllers from Finite State Stack Machine Diagrams. In: IEEE 23rd Int’l. Conf. on Emerging Technologies and Factory Automation (ETFA), pp. 1179–1182, Turin (Italy).
Rivas-Alonso D, Jiménez-Jané J, Ll Ribas-Xirgo (2018) Auction Model for Transport Order Assignment in AGV Systems. In: Pizán RF, Olaya ÁG, Lorente MPS, Martínez JAI, Espino AL (eds) Advances in Physical Agents Proceedings of the 19th International Workshop of Physical Agents (WAF 2018), November 22-23, 2018, Madrid, Spain. Springer, Cham
Rivas-Alonso D, Ribas-Xirgo Ll (2019) Agent-based Model for Transport Order Assignment in AGV Systems. In: IEEE 24th Int’l. Conf. on Emerging Technologies and Factory Automation (ETFA), pp. 947–954, DOI: https://doi.org/10.1109/ETFA.2019.8869302.
Sakellariou I, Kefalas P, Stamatopoulou, I (2009) MAS coursework design in NetLogo. In: Beer, M., Fasli, M., Richards, D. (eds.) Proc. of the Int’l. Wkshp. on the Educational Uses of Multi-Agent Systems (EDUMAS’09), pp. 47–54.
Salanova-Grau JM, Estrada M, Aifadopoulou G, Mitsakis E (2011) A review of the modeling of taxi services. Procedia Soc Behav Sci 20:150–161. https://doi.org/10.1016/j.sbspro.2011.08.020
Smith RG (1980) The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver. IEEE Trans Comput. https://doi.org/10.1109/TC.1980.1675516
Yeung WL (2018) Efficiency of task allocation based on contract net protocol with audience restriction in a manufacturing control application. Int J Comput Integr Manuf 31(10):1005–1017. https://doi.org/10.1080/0951192X.2018.1493227
Zhang R, Ghanem R (2019) Demand, supply, and performance of street-hail taxi. IEEE Trans Intell Transport Syst. https://doi.org/10.1109/TITS.2019.2938762
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Ribas-Xirgo, L. A state-based multi-agent system model of taxi fleets. Multimed Tools Appl 81, 3515–3534 (2022). https://doi.org/10.1007/s11042-021-11607-3
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DOI: https://doi.org/10.1007/s11042-021-11607-3