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Using SUMO towards Proactive Public Mobility: Some Lessons Learned

Authors:

Franca Rocco Di Torrepadula,

Sergio Di Martino,

Nicola Mazzocca,

Paolo SanninoAuthors Info & Claims

SuMob '23: Proceedings of the 1st ACM SIGSPATIAL International Workshop on Sustainable Mobility

Pages 51 - 58

https://doi.org/10.1145/3615899.3627932

Published: 19 December 2023 Publication History

Abstract

Transportation causes several adverse environmental effects, including the emissions of air pollutants and greenhouse gases. Thus, shifting global mobility towards novel and more sustainable solutions is needed, for instance by enhancing public transports, promoting active modes, or adopting more sustainable technologies. In this context, simulators of urban mobility offer a valuable tool for assessing the impact of new policies, by providing support in designing traffic circulation plans and assessing the effectiveness of new transportation modes. However, building realistic scenarios is challenging due to data reliability issues.

In this paper, we present some lessons learned on the use of the SUMO simulator for sustainable mobility. Through a case study in the city of Genoa, Italy, we described the challenges we faced, which lead us to a significant discrepancy between simulated and real data. Despite manual data cleansing/refinement improved the accuracy, data quality remains still a concern. Thus, in this paper we highlight to the ITS community the need for improving data reliability to preliminary assess eco-friendly transportation solutions.

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Cited By

Ramadhan WAndani Syarif S(2024)Method for Determining Node Position in Vehicle Ad-Hoc Network Based on Generator Simulation Urban Mobility (SUMO) Optimization2024 11th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)10.1109/EECSI63442.2024.10776399(526-531)Online publication date: 26-Sep-2024
https://doi.org/10.1109/EECSI63442.2024.10776399
Arefe CSakib NRahman MIslam K(2024)Optimization of semi-synchronized multi-modal urban traffic signal through stochastic computer simulationKSCE Journal of Civil Engineering10.1016/j.kscej.2024.100135(100135)Online publication date: Dec-2024
https://doi.org/10.1016/j.kscej.2024.100135
Rocco di Torrepadula F(2024)Enhancing Efficiency and Privacy of Intelligent Public Transportation Systems Through Federated Learning and EdgeAIWeb and Wireless Geographical Information Systems10.1007/978-3-031-60796-7_15(205-210)Online publication date: 9-May-2024
https://doi.org/10.1007/978-3-031-60796-7_15

Index Terms

Using SUMO towards Proactive Public Mobility: Some Lessons Learned
1. Computing methodologies
  1. Modeling and simulation
    1. Simulation support systems
      1. Simulation tools

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cover image ACM Conferences

SuMob '23: Proceedings of the 1st ACM SIGSPATIAL International Workshop on Sustainable Mobility

November 2023

74 pages

ISBN:9798400703614

DOI:10.1145/3615899

Copyright © 2023 Owner/Author(s).

This work is licensed under a Creative Commons Attribution International 4.0 License.

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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 December 2023

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SuMob '23: 1st ACM SIGSPATIAL International Workshop on Sustainable Mobility

November 13, 2023

Hamburg, Germany

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Overall Acceptance Rate 5 of 9 submissions, 56%

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Cited By

Ramadhan WAndani Syarif S(2024)Method for Determining Node Position in Vehicle Ad-Hoc Network Based on Generator Simulation Urban Mobility (SUMO) Optimization2024 11th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)10.1109/EECSI63442.2024.10776399(526-531)Online publication date: 26-Sep-2024
https://doi.org/10.1109/EECSI63442.2024.10776399
Arefe CSakib NRahman MIslam K(2024)Optimization of semi-synchronized multi-modal urban traffic signal through stochastic computer simulationKSCE Journal of Civil Engineering10.1016/j.kscej.2024.100135(100135)Online publication date: Dec-2024
https://doi.org/10.1016/j.kscej.2024.100135
Rocco di Torrepadula F(2024)Enhancing Efficiency and Privacy of Intelligent Public Transportation Systems Through Federated Learning and EdgeAIWeb and Wireless Geographical Information Systems10.1007/978-3-031-60796-7_15(205-210)Online publication date: 9-May-2024
https://doi.org/10.1007/978-3-031-60796-7_15

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