Contagion spread modeling in transport networks and transport operation optimizations for containing epidemics
Kapitel i bok, 2022

COVID-19 has critically impacted many aspects of societies worldwide, particularly on mobility. This chapter summarizes impacts of the COVID-19 pandemic, reviews existing research, and identifies future research needs in the scope of traffic theory and modeling/optimization and traffic flow. We first review models on contagion spreading through transportation networks, including aggregated spatial metapopulation models and disaggregated individual-based models. Further research is needed to consider both intercity and intracity mobilities and leverage emerging multiple data resources for constructing individuals’ complete trip chains. Based on modeling contagion spreading, we further discuss transport operation needs in the aftermath of COVID-19. There remains a need for operating multimodal urban transport systems to satisfy basic travel demands while minimizing contagion risks. Relevant research needs are identified in optimizing transport operation via modern data acquisition technologies and advanced modeling methods. Practical intervention measures and policy implications are recommended for optimizing transport systems during the COVID-19 pandemic.

Transit management and control, system optimization

Big data

Transport networks

Countermeasures

Multimodal transportation

Contagion spread

Multisource data

Författare

Xiaobo Qu

Transportgruppen

Kun Gao

Transportgruppen

Xiaopeng Li

University of South Florida

Transportation Amid Pandemics: Lessons Learned from COVID-19

349-357
9780323997706 (ISBN)

Ämneskategorier

Annan data- och informationsvetenskap

Transportteknik och logistik

Annan samhällsbyggnadsteknik

DOI

10.1016/B978-0-323-99770-6.00009-0

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Senast uppdaterat

2023-10-26