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  • Presentation | A51R: Decision-Relevant Understanding of Impactful Weather and Extremes III Poster
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  • A51R-0994: Structural changes in weather sensitivity of public transit using Bayesian models
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Author(s):
Lele Zhang, (First Author, Presenting Author)
Xin Wu, Villanova University
Alireza Ermagun, George Mason University Fairfax
Chenfeng Xiong, Villanova University


Public transportation becomes less reliable during extreme weather, but understanding of how the COVID-19 pandemic changed these patterns was limited. This study analyzed five years of ridership data from Philadelphia's buses, trains, and trolleys to understand how weather affects different types of transit.


Results show that snow causes the biggest problems (especially for trains), while rain affects almost all routes. Surprisingly, after the pandemic, transit became more resistant to bad weather because mainly essential workers continued riding ,they cannot avoid transit during storms like other passengers can.


This research helps cities plan better transit systems that work even during extreme weather, which is becoming more common due to climate change.




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