Understanding traffic congestion via network analysis, agent modeling, and the trajectory of urban expansion: a coastal city case.

The study of patterns of urban mobility is of utter importance for city growth projection and development planning. In this paper, we analyze the topological aspects of the street network of the coastal city of Cartagena de Indias employing graph theory and spatial syntax tools. We find that the res...

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Autores:
Amézquita-López, Julio
Valdés-Atencio, Jorge
Angulo-García, David
Tipo de recurso:
Article of investigation
Fecha de publicación:
2021
Institución:
Universidad de Cartagena
Repositorio:
Repositorio Universidad de Cartagena
Idioma:
spa
OAI Identifier:
oai:repositorio.unicartagena.edu.co:11227/17730
Acceso en línea:
https://hdl.handle.net/11227/17730
Palabra clave:
Urban mobility
traffic analysis
Cartagena de Indias
Rights
openAccess
License
2021 by the authors. Licensee MDPI, Basel, Switzerland.
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network_name_str Repositorio Universidad de Cartagena
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dc.title.spa.fl_str_mv Understanding traffic congestion via network analysis, agent modeling, and the trajectory of urban expansion: a coastal city case.
title Understanding traffic congestion via network analysis, agent modeling, and the trajectory of urban expansion: a coastal city case.
spellingShingle Understanding traffic congestion via network analysis, agent modeling, and the trajectory of urban expansion: a coastal city case.
Urban mobility
traffic analysis
Cartagena de Indias
title_short Understanding traffic congestion via network analysis, agent modeling, and the trajectory of urban expansion: a coastal city case.
title_full Understanding traffic congestion via network analysis, agent modeling, and the trajectory of urban expansion: a coastal city case.
title_fullStr Understanding traffic congestion via network analysis, agent modeling, and the trajectory of urban expansion: a coastal city case.
title_full_unstemmed Understanding traffic congestion via network analysis, agent modeling, and the trajectory of urban expansion: a coastal city case.
title_sort Understanding traffic congestion via network analysis, agent modeling, and the trajectory of urban expansion: a coastal city case.
dc.creator.fl_str_mv Amézquita-López, Julio
Valdés-Atencio, Jorge
Angulo-García, David
dc.contributor.author.none.fl_str_mv Amézquita-López, Julio
Valdés-Atencio, Jorge
Angulo-García, David
dc.contributor.editor.none.fl_str_mv Ana Vulevic
Gualter Couto
José Manuel Naranjo Gómez
Higinio González Jorge
dc.contributor.datamanager.none.fl_str_mv Rui Castanho
dc.subject.armarc.none.fl_str_mv Urban mobility
traffic analysis
Cartagena de Indias
topic Urban mobility
traffic analysis
Cartagena de Indias
description The study of patterns of urban mobility is of utter importance for city growth projection and development planning. In this paper, we analyze the topological aspects of the street network of the coastal city of Cartagena de Indias employing graph theory and spatial syntax tools. We find that the resulting network can be understood on the basis of 400 years of the city’s history and its peripheral location that strongly influenced and shaped the growth of the city, and that the statistical properties of the network resemble those of self-organized cities. Moreover, we study the mobility through the network using a simple agent-based model that allows us to study the level of street congestion depending on the agents’ knowledge of the traffic while they travel through the network. We found that a purely shortest-path travel scheme is not an optimal strategy and that assigning small weights to traffic avoidance schemes increases the overall performance of the agents in terms of arrival success, occupancy of the streets, and traffic accumulation. Finally, we argue that localized congestion can be only partially ascribed to topological properties of the network and that it is important to consider the decision-making capability of the agents while moving through the network to explain the emergence of traffic congestion in the system.
publishDate 2021
dc.date.issued.none.fl_str_mv 2021
dc.date.accessioned.none.fl_str_mv 2024-05-30T14:36:48Z
dc.date.available.none.fl_str_mv 2024-05-30T14:36:48Z
dc.type.spa.fl_str_mv Articulo.
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url https://hdl.handle.net/11227/17730
dc.language.iso.spa.fl_str_mv spa
language spa
dc.rights.spa.fl_str_mv 2021 by the authors. Licensee MDPI, Basel, Switzerland.
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https://creativecommons.org/licenses/by-nc/4.0/
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dc.publisher.spa.fl_str_mv Universidad de Huelva.
dc.publisher.place.spa.fl_str_mv Spain
dc.source.spa.fl_str_mv Texto
institution Universidad de Cartagena
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spelling Amézquita-López, Julio0a13137f868071a0f912038ba65a41c2Valdés-Atencio, Jorge319f2400c2ceeb20ab68970324792a4fAngulo-García, David40a452033ec9c390c047fba9428f2cc2Ana VulevicGualter CoutoJosé Manuel Naranjo GómezHiginio González JorgeRui Castanho2024-05-30T14:36:48Z2024-05-30T14:36:48Z2021https://hdl.handle.net/11227/17730The study of patterns of urban mobility is of utter importance for city growth projection and development planning. In this paper, we analyze the topological aspects of the street network of the coastal city of Cartagena de Indias employing graph theory and spatial syntax tools. We find that the resulting network can be understood on the basis of 400 years of the city’s history and its peripheral location that strongly influenced and shaped the growth of the city, and that the statistical properties of the network resemble those of self-organized cities. Moreover, we study the mobility through the network using a simple agent-based model that allows us to study the level of street congestion depending on the agents’ knowledge of the traffic while they travel through the network. We found that a purely shortest-path travel scheme is not an optimal strategy and that assigning small weights to traffic avoidance schemes increases the overall performance of the agents in terms of arrival success, occupancy of the streets, and traffic accumulation. Finally, we argue that localized congestion can be only partially ascribed to topological properties of the network and that it is important to consider the decision-making capability of the agents while moving through the network to explain the emergence of traffic congestion in the system.application/pdfspaUniversidad de Huelva.Spain2021 by the authors. Licensee MDPI, Basel, Switzerland.https://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccessAtribución-NoComercial 4.0 Internacional (CC BY-NC 4.0)http://purl.org/coar/access_right/c_abf2TextoUnderstanding traffic congestion via network analysis, agent modeling, and the trajectory of urban expansion: a coastal city case.Articulo.info:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttps://purl.org/redcol/resource_type/TMhttp://purl.org/coar/version/c_970fb48d4fbd8a85Urban mobilitytraffic analysisCartagena de IndiasPumain, D.; Saint-Julien, T. Análisis Espacial: Las Interacciones; Universidad de Concepción-Facultad de Arquitectura, Urbanisme y Geografía: Concepción, Chile, 2014.Barthélemy, M. Spatial networks. Phys. Rep. 2011, 499, 1–101. [CrossRef]Crucitti, P.; Latora, V.; Porta, S. Centrality measures in spatial networks of urban streets. Phys. Rev. E 2006, 73, 036125. [CrossRef]Crucitti, P.; Latora, V.; Porta, S. Centrality in networks of urban streets. Chaos Interdiscip. J. Nonlinear Sci. 2006, 16, 015113. [CrossRef] [PubMed]Duan, Y.; Lu, F. Robustness of city road networks at different granularities. Phys. A Stat. Mech. Appl. 2014, 411, 21–34. [CrossRef]Manley, E.; Cheng, T. Understanding road congestion as an emergent property of traffic networks. In Proceedings of the 14th WMSCI, Orlando, FL, USA, 29 June–2 July 2010.ORIGINALinfrastructures-06-00085-v2 (3) (6).pdfinfrastructures-06-00085-v2 (3) (6).pdfapplication/pdf9796810https://repositorio.unicartagena.edu.co/bitstream/11227/17730/1/infrastructures-06-00085-v2%20%283%29%20%286%29.pdf76a0488b81e8eb49fe73a24cb5e693d0MD51metadata only accessTEXTinfrastructures-06-00085-v2 (3) (6).pdf.txtinfrastructures-06-00085-v2 (3) (6).pdf.txtExtracted texttext/plain54861https://repositorio.unicartagena.edu.co/bitstream/11227/17730/2/infrastructures-06-00085-v2%20%283%29%20%286%29.pdf.txt2b5ca4058bc0790a94cb7bc042d23399MD52metadata only accessTHUMBNAILinfrastructures-06-00085-v2 (3) (6).pdf.jpginfrastructures-06-00085-v2 (3) (6).pdf.jpgGenerated Thumbnailimage/jpeg16334https://repositorio.unicartagena.edu.co/bitstream/11227/17730/3/infrastructures-06-00085-v2%20%283%29%20%286%29.pdf.jpg2c08b52be4eef043b583c417b9236b40MD53metadata only access11227/17730oai:repositorio.unicartagena.edu.co:11227/177302024-06-01 03:38:25.99An error occurred on the license name.|||https://creativecommons.org/licenses/by-nc/4.0/metadata only accessBiblioteca Digital Universidad de Cartagenabdigital@metabiblioteca.com