Martí, P.; Jordán, J.; Palanca Cámara, J.; Julian, V. (2022). Charging Stations and Mobility Data Generators for Agent-based Simulations. Neurocomputing. 484:196-210. https://doi.org/10.1016/j.neucom.2021.06.098
Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/198864
Title:
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Charging Stations and Mobility Data Generators for Agent-based Simulations
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Author:
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Martí, Pasqual
Jordán, Jaume
Palanca Cámara, Javier
Julian, Vicente
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UPV Unit:
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Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica
Universitat Politècnica de València. Escuela Politécnica Superior de Gandia - Escola Politècnica Superior de Gandia
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Issued date:
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Abstract:
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[EN] Current traffic congestion and the resulting carbon emissions are two of the main problems threatening the sustainability of modern cities. The challenges facing today's cities focus primarily on the optimization of ...[+]
[EN] Current traffic congestion and the resulting carbon emissions are two of the main problems threatening the sustainability of modern cities. The challenges facing today's cities focus primarily on the optimization of traffic flow and the transition to electric vehicles. The latter aspect implies the need for an adequate deployment of the infrastructure of charging stations. The inherent complexity in today's cities and the difficulty in implementing new policies whose benefits are difficult to measure and predict has led in recent years to consider the enormous potential of simulation tools and in particular of the agent-based simulation (ABS). ABS allows the specification of complex models that reflect the complexity and dynamism of urban mobility. Current technology in ABS has evolved and matured sufficiently to provide very sophisticated tools but lacking facilities for a flexible and realistic generation of input data in the execution of the experiments. In line with this, this paper introduces two configurable generators that automatize the creation of experiments in agent-based simulations. The generators have been developed with the SimFleet simulation tool enhancing the simulation of realistic movements and location of vehicles, passengers and other users of the urban traffic system within a city. The generators proved to be useful for comparing different distributions of locations as well as different agent movement behaviors based on real city data.(c) 2021 Elsevier B.V. All rights reserved.
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Subjects:
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Multi-agent system
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Simulation
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Transportation
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Electric vehicle
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Smart city
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Urban fleets
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Copyrigths:
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Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
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Source:
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Neurocomputing. (issn:
0925-2312
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DOI:
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10.1016/j.neucom.2021.06.098
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Publisher:
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Elsevier
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Publisher version:
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https://doi.org/10.1016/j.neucom.2021.06.098
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Project ID:
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info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-095390-B-C31/ES/HACIA UNA MOVILIDAD INTELIGENTE Y SOSTENIBLE SOPORTADA POR SISTEMAS MULTI-AGENTES Y EDGE COMPUTING/
info:eu-repo/grantAgreement/GENERALITAT VALENCIANA//ACIF%2F2021%2F259//TECNICAS INTELIGENTES PARA LA OPTIMIZACION Y SOSTENIBILIDAD DE LA MOVILIDAD URBANA/
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Thanks:
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This work is partially supported by grant RTI2018-095390-BC31 funded by MCIN/AEI/10.13039/501100011033 and by "ERDF A way of making Europe". Pasqual Marti is supported by grant ACIF/2021/259 funded by the Conselleria de ...[+]
This work is partially supported by grant RTI2018-095390-BC31 funded by MCIN/AEI/10.13039/501100011033 and by "ERDF A way of making Europe". Pasqual Marti is supported by grant ACIF/2021/259 funded by the Conselleria de Innovacion, Universidades, Ciencia y Sociedad Digital de la Generalitat Valenciana and the European Social Fund.
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Type:
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Artículo
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