LIPIcs.GIScience.2023.34.pdf
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Simulating and Validating the Traffic of Blackwall Tunnel Using TfL Jam Cam Data and Simulation of Urban Mobility (SUMO) (Short Paper)
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12th International Conference on Geographic Information Science (GIScience 2023)
Series: Leibniz International Proceedings in Informatics (LIPIcs)
Conference: International Conference on Geographic Information Science (GIScience) - License:
Creative Commons Attribution 4.0 International license
- Publication Date: 2023-09-07
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Acknowledgements
I would like to thank Transport for London for providing journey time data through its Open Data programme. I would also thank Dr Sarah Wise, my PhD supervisor, for her outstanding support during this research.
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Chukun Gao. Simulating and Validating the Traffic of Blackwall Tunnel Using TfL Jam Cam Data and Simulation of Urban Mobility (SUMO) (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 34:1-34:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/LIPIcs.GIScience.2023.34
Abstract
Blackwall Tunnel is one of the most congested roadways in London. By simulating the tunnel and the connecting roads, information can be obtained about the traffic conditions and bottlenecks. In this paper, a model will be created using the Simulation of Urban Mobility (SUMO) tool and traffic flow data gathered from Transport for London (TfL) traffic cameras. The result from the simulation will be compared to the journey time data of Blackwall Tunnel in order to determine the accuracy of simulation.
Subject Classification
ACM Subject Classification
- Information systems → Traffic analysis
Keywords
- Traffic simulation
- Validation
- SUMO
- Blackwall Tunnel
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Software (Source Code)
https://github.com/Chukun-Leo-Gao/Blackwall_Simulation_GIScience
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