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Exploring the Impact of Extreme Weather on Urban Road Traffic Networks Based on Percolation Theory
https://orcid.org/0009-0009-0320-6470
https://orcid.org/0000-0001-9803-4206
https://orcid.org/0000-0001-9393-2701
Urban transportation, a vital artery for production and daily life, often suffers severe disruption during extreme weather events. Specifically, coastal cities often face the brunt of extreme weather events, including typhoons, heavy rainfall, and other extreme conditions, which can cause significant damage to urban transportation networks. These events often result in acute traffic congestion, with the distribution of bottleneck road sections differing from those under normal weather conditions. Most existing methodologies for identifying urban traffic bottlenecks predominantly utilize data obtained under normal weather conditions, with scant consideration for analysis under extreme weather scenarios. In this study, we invoke percolation theory from statistical physics, introducing the traffic percolation threshold () as an indicator of network analysis and scrutinizing the traffic connectivity under extreme weather conditions. Our statistical analysis of bottleneck road section distribution reveals that the location distribution of bottleneck roads within the city under extreme weather differs from that under normal weather conditions. Three roads are identified as bottleneck sections under both weather conditions. The method proposed herein offers a valuable reference for urban traffic management and the prevention of traffic paralysis under extreme weather conditions.
Exploring the Impact of Extreme Weather on Urban Road Traffic Networks Based on Percolation Theory
https://orcid.org/0009-0009-0320-6470
https://orcid.org/0000-0001-9803-4206
https://orcid.org/0000-0001-9393-2701
Urban transportation, a vital artery for production and daily life, often suffers severe disruption during extreme weather events. Specifically, coastal cities often face the brunt of extreme weather events, including typhoons, heavy rainfall, and other extreme conditions, which can cause significant damage to urban transportation networks. These events often result in acute traffic congestion, with the distribution of bottleneck road sections differing from those under normal weather conditions. Most existing methodologies for identifying urban traffic bottlenecks predominantly utilize data obtained under normal weather conditions, with scant consideration for analysis under extreme weather scenarios. In this study, we invoke percolation theory from statistical physics, introducing the traffic percolation threshold () as an indicator of network analysis and scrutinizing the traffic connectivity under extreme weather conditions. Our statistical analysis of bottleneck road section distribution reveals that the location distribution of bottleneck roads within the city under extreme weather differs from that under normal weather conditions. Three roads are identified as bottleneck sections under both weather conditions. The method proposed herein offers a valuable reference for urban traffic management and the prevention of traffic paralysis under extreme weather conditions.
Exploring the Impact of Extreme Weather on Urban Road Traffic Networks Based on Percolation Theory
https://orcid.org/0009-0009-0320-6470
https://orcid.org/0000-0001-9803-4206
https://orcid.org/0000-0001-9393-2701
Urban transportation, a vital artery for production and daily life, often suffers severe disruption during extreme weather events. Specifically, coastal cities often face the brunt of extreme weather events, including typhoons, heavy rainfall, and other extreme conditions, which can cause significant damage to urban transportation networks. These events often result in acute traffic congestion, with the distribution of bottleneck road sections differing from those under normal weather conditions. Most existing methodologies for identifying urban traffic bottlenecks predominantly utilize data obtained under normal weather conditions, with scant consideration for analysis under extreme weather scenarios. In this study, we invoke percolation theory from statistical physics, introducing the traffic percolation threshold () as an indicator of network analysis and scrutinizing the traffic connectivity under extreme weather conditions. Our statistical analysis of bottleneck road section distribution reveals that the location distribution of bottleneck roads within the city under extreme weather differs from that under normal weather conditions. Three roads are identified as bottleneck sections under both weather conditions. The method proposed herein offers a valuable reference for urban traffic management and the prevention of traffic paralysis under extreme weather conditions.
Exploring the Impact of Extreme Weather on Urban Road Traffic Networks Based on Percolation Theory
J. Transp. Eng., Part A: Systems
Chen, Zhen (author) / Xing, Yingying (author) / Fang, Kexin (author) / Lang, Hong (author) / Peng, Yichuan (author) / Wang, Hongwei (author)
2025-05-01
Article (Journal)
Electronic Resource
English
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