Quantifying higher-order modal interactions in urban transportation: a visibility graph approach to extreme weather adaptation

Lin, Xuhui, Lu, Qiuchen, Chen, Long, Cheng, Tao, Broyd, Tim and Zhang, Xianghui 2025. Quantifying higher-order modal interactions in urban transportation: a visibility graph approach to extreme weather adaptation. Presented at: 32nd International Workshop on Intelligent Computing in Engineering, Glasgow, Scotland, 1-3 July 2025. Proceedings of the 32nd International Workshop on Intelligent Computing in Engineering. University of Stathclyde,

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Abstract

Climate change and extreme weather events increasingly challenge urban transportation systems' ability to maintain essential mobility services. While existing research has examined individual transportation modes or simplified interactions, the complex dynamics emerging from multi-modal interactions under stress remain poorly understood. This study introduces the Multi-modal Visibility Graph Irreversibility (MmVGI) framework to analyse transportation system behaviour during extreme weather events. By integrating concepts from non-equilibrium dynamics with visibility graph analysis, our approach quantifies complex interactions between different transportation modes and reveals the underlying mechanisms driving system non-equilibrium characteristics. Through a case study in the City of London during an extreme rainfall event, we demonstrate that transportation system adaptation exhibits clear hierarchical patterns across different road types, with cycling emerging as a crucial component in system adaptation. These findings offer valuable guidance for urban planners and transportation engineers in developing targeted resilience strategies during increasingly frequent extreme weather events.

Item Type:	Conference or Workshop Item (Paper)
Status:	In Press
Schools:	Schools > Engineering
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Publisher:	University of Stathclyde
Date of First Compliant Deposit:	9 June 2025
Last Modified:	23 Aug 2025 01:30
URI:	https://orca.cardiff.ac.uk/id/eprint/178861

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