Modelling Road Saturation Dynamics on a Complex Transportation Network Based on GPS Navigation Software Data

Mariana Cubero-Corella; Esteban Durán-Monge; Warner Díaz; Esteban Meneses; Steffan Gómez-Campos

doi:10.1007/978-3-030-41005-6_10

Modelling Road Saturation Dynamics on a Complex Transportation Network Based on GPS Navigation Software Data

Mariana Cubero-Corella
, Esteban Durán-Monge
, Warner Díaz
, Esteban Meneses
, Steffan Gómez-Campos

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

High traffic concentration during weekdays in the Great Metropolitan Area of Costa Rica causes severe traffic congestion and high costs for the population. It is crucial to deeply understand the dynamics of traffic congestion to design and implement long term solutions. Given the lack of official data to study traffic congestion, we model it using a transportation network based on data captured throughout the year 2018 by a GPS navigation software application (Waze), provided by the Ministry of Public Works and Transportation (MOPT in Spanish). In this paper, we focus on the data transformation procedure to create the transportation network and propose a traffic congestion classification with the available data. We developed a practical methodology which consists of four main stages: data preparation, road network modelling, road saturation estimation, and saturation dynamics analysis. The results show it is possible to model road saturation level using the proposed methodology. We were able to classify road segments in five categories that effectively represent the levels of road saturation. This classification gives us a clear overview of the real-world conditions faced by road network users.

Original language	English
Title of host publication	High Performance Computing - 6th Latin American Conference, CARLA 2019, Revised Selected Papers
Editors	Juan Luis Crespo-Mariño, Esteban Meneses-Rojas
Publisher	Springer
Pages	136-149
Number of pages	14
ISBN (Print)	9783030410049
DOIs	https://doi.org/10.1007/978-3-030-41005-6_10
State	Published - 2020
Event	6th Latin American High Performance Computing Conference, CARLA 2019 - Turrialba, Costa Rica Duration: 25 Sep 2019 → 27 Sep 2019

Publication series

Name	Communications in Computer and Information Science
Volume	1087 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	6th Latin American High Performance Computing Conference, CARLA 2019
Country/Territory	Costa Rica
City	Turrialba
Period	25/09/19 → 27/09/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure
SDG 11 Sustainable Cities and Communities

Keywords

Delay
Traffic jam
Transportation network
Urban mobility
Waze

Access to Document

10.1007/978-3-030-41005-6_10

Cite this

Cubero-Corella, M., Durán-Monge, E., Díaz, W., Meneses, E., & Gómez-Campos, S. (2020). Modelling Road Saturation Dynamics on a Complex Transportation Network Based on GPS Navigation Software Data. In J. L. Crespo-Mariño, & E. Meneses-Rojas (Eds.), High Performance Computing - 6th Latin American Conference, CARLA 2019, Revised Selected Papers (pp. 136-149). (Communications in Computer and Information Science; Vol. 1087 CCIS). Springer. https://doi.org/10.1007/978-3-030-41005-6_10

Cubero-Corella, Mariana ; Durán-Monge, Esteban ; Díaz, Warner et al. / Modelling Road Saturation Dynamics on a Complex Transportation Network Based on GPS Navigation Software Data. High Performance Computing - 6th Latin American Conference, CARLA 2019, Revised Selected Papers. editor / Juan Luis Crespo-Mariño ; Esteban Meneses-Rojas. Springer, 2020. pp. 136-149 (Communications in Computer and Information Science).

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title = "Modelling Road Saturation Dynamics on a Complex Transportation Network Based on GPS Navigation Software Data",

abstract = "High traffic concentration during weekdays in the Great Metropolitan Area of Costa Rica causes severe traffic congestion and high costs for the population. It is crucial to deeply understand the dynamics of traffic congestion to design and implement long term solutions. Given the lack of official data to study traffic congestion, we model it using a transportation network based on data captured throughout the year 2018 by a GPS navigation software application (Waze), provided by the Ministry of Public Works and Transportation (MOPT in Spanish). In this paper, we focus on the data transformation procedure to create the transportation network and propose a traffic congestion classification with the available data. We developed a practical methodology which consists of four main stages: data preparation, road network modelling, road saturation estimation, and saturation dynamics analysis. The results show it is possible to model road saturation level using the proposed methodology. We were able to classify road segments in five categories that effectively represent the levels of road saturation. This classification gives us a clear overview of the real-world conditions faced by road network users.",

keywords = "Delay, Traffic jam, Transportation network, Urban mobility, Waze",

author = "Mariana Cubero-Corella and Esteban Dur{\'a}n-Monge and Warner D{\'i}az and Esteban Meneses and Steffan G{\'o}mez-Campos",

note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 6th Latin American High Performance Computing Conference, CARLA 2019 ; Conference date: 25-09-2019 Through 27-09-2019",

year = "2020",

doi = "10.1007/978-3-030-41005-6\_10",

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}

Cubero-Corella, M, Durán-Monge, E, Díaz, W, Meneses, E & Gómez-Campos, S 2020, Modelling Road Saturation Dynamics on a Complex Transportation Network Based on GPS Navigation Software Data. in JL Crespo-Mariño & E Meneses-Rojas (eds), High Performance Computing - 6th Latin American Conference, CARLA 2019, Revised Selected Papers. Communications in Computer and Information Science, vol. 1087 CCIS, Springer, pp. 136-149, 6th Latin American High Performance Computing Conference, CARLA 2019, Turrialba, Costa Rica, 25/09/19. https://doi.org/10.1007/978-3-030-41005-6_10

Modelling Road Saturation Dynamics on a Complex Transportation Network Based on GPS Navigation Software Data. / Cubero-Corella, Mariana; Durán-Monge, Esteban; Díaz, Warner et al.
High Performance Computing - 6th Latin American Conference, CARLA 2019, Revised Selected Papers. ed. / Juan Luis Crespo-Mariño; Esteban Meneses-Rojas. Springer, 2020. p. 136-149 (Communications in Computer and Information Science; Vol. 1087 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Modelling Road Saturation Dynamics on a Complex Transportation Network Based on GPS Navigation Software Data

AU - Cubero-Corella, Mariana

AU - Durán-Monge, Esteban

AU - Díaz, Warner

AU - Meneses, Esteban

AU - Gómez-Campos, Steffan

PY - 2020

Y1 - 2020

N2 - High traffic concentration during weekdays in the Great Metropolitan Area of Costa Rica causes severe traffic congestion and high costs for the population. It is crucial to deeply understand the dynamics of traffic congestion to design and implement long term solutions. Given the lack of official data to study traffic congestion, we model it using a transportation network based on data captured throughout the year 2018 by a GPS navigation software application (Waze), provided by the Ministry of Public Works and Transportation (MOPT in Spanish). In this paper, we focus on the data transformation procedure to create the transportation network and propose a traffic congestion classification with the available data. We developed a practical methodology which consists of four main stages: data preparation, road network modelling, road saturation estimation, and saturation dynamics analysis. The results show it is possible to model road saturation level using the proposed methodology. We were able to classify road segments in five categories that effectively represent the levels of road saturation. This classification gives us a clear overview of the real-world conditions faced by road network users.

AB - High traffic concentration during weekdays in the Great Metropolitan Area of Costa Rica causes severe traffic congestion and high costs for the population. It is crucial to deeply understand the dynamics of traffic congestion to design and implement long term solutions. Given the lack of official data to study traffic congestion, we model it using a transportation network based on data captured throughout the year 2018 by a GPS navigation software application (Waze), provided by the Ministry of Public Works and Transportation (MOPT in Spanish). In this paper, we focus on the data transformation procedure to create the transportation network and propose a traffic congestion classification with the available data. We developed a practical methodology which consists of four main stages: data preparation, road network modelling, road saturation estimation, and saturation dynamics analysis. The results show it is possible to model road saturation level using the proposed methodology. We were able to classify road segments in five categories that effectively represent the levels of road saturation. This classification gives us a clear overview of the real-world conditions faced by road network users.

KW - Delay

KW - Traffic jam

KW - Transportation network

KW - Urban mobility

KW - Waze

UR - https://www.scopus.com/pages/publications/85081174658

U2 - 10.1007/978-3-030-41005-6_10

DO - 10.1007/978-3-030-41005-6_10

M3 - Contribución a la conferencia

AN - SCOPUS:85081174658

SN - 9783030410049

T3 - Communications in Computer and Information Science

SP - 136

EP - 149

BT - High Performance Computing - 6th Latin American Conference, CARLA 2019, Revised Selected Papers

A2 - Crespo-Mariño, Juan Luis

A2 - Meneses-Rojas, Esteban

PB - Springer

T2 - 6th Latin American High Performance Computing Conference, CARLA 2019

Y2 - 25 September 2019 through 27 September 2019

ER -

Cubero-Corella M, Durán-Monge E, Díaz W, Meneses E, Gómez-Campos S. Modelling Road Saturation Dynamics on a Complex Transportation Network Based on GPS Navigation Software Data. In Crespo-Mariño JL, Meneses-Rojas E, editors, High Performance Computing - 6th Latin American Conference, CARLA 2019, Revised Selected Papers. Springer. 2020. p. 136-149. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-41005-6_10

Modelling Road Saturation Dynamics on a Complex Transportation Network Based on GPS Navigation Software Data

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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