Clustering reveals key behaviours driving human movement network structure
We analysed daily travel patterns from in-app GPS data in the United Kingdom to identify
characteristic modes of travel behaviour, and the relative importance of different behaviours …
characteristic modes of travel behaviour, and the relative importance of different behaviours …
FairMobi-Net: A Fairness-aware Deep Learning Model for Urban Mobility Flow Generation
Generating realistic human flows across regions is essential for our understanding of urban
structures and population activity patterns, enabling important applications in the fields of …
structures and population activity patterns, enabling important applications in the fields of …
[HTML][HTML] Identifying the shifting sources to predict the dynamics of COVID-19 in the US
Mobility restriction is a crucial measure to control the transmission of the COVID-19.
Research has shown that effective distance measured by the number of travelers instead of …
Research has shown that effective distance measured by the number of travelers instead of …
RecSys Model to Infer Missing Transportation Mobility Data
Y Zhang, XJ Ban - 2023 IEEE 26th International Conference on …, 2023 - ieeexplore.ieee.org
Passively collected mobile data, particularly large-scale datasets, have become increasingly
popular in transportation studies for understanding human mobility patterns and evaluating …
popular in transportation studies for understanding human mobility patterns and evaluating …
A Big-Data-Driven Framework for Spatiotemporal Travel Demand Estimation and Prediction
S Hu - 2023 - search.proquest.com
Traditional travel demand models heavily rely on travel surveys, simplify future demand
forecasting, and show low sensitivity in response to spatiotemporal dynamics. This study …
forecasting, and show low sensitivity in response to spatiotemporal dynamics. This study …
Data sharing and collaborations with Telco data during the COVID-19 pandemic: A Vodafone case study
PR Lourenco, G Kaur, M Allison, T Evetts - Data & Policy, 2021 - cambridge.org
With the outbreak of COVID-19 across Europe, anonymized telecommunications data
provides a key insight into population level mobility and assessing the impact and …
provides a key insight into population level mobility and assessing the impact and …
[HTML][HTML] A machine learning approach for predicting hurricane evacuee destination location using smartphone location data
Evacuation destination choice modeling is an integral aspect of evacuation planning.
Outputs from such models are required to estimate the clearance times on which evacuation …
Outputs from such models are required to estimate the clearance times on which evacuation …
Are big mobility data reliable for assessing the performance of transit systems during covid-19?
F Wang, E Umeibe, M Zhang, X Ban - Available at SSRN 4179757, 2022 - papers.ssrn.com
The COVID-19 pandemic has been causing tremendous impacts on travel and
transportation systems. A growing number of studies employed big mobility datasets (BMD) …
transportation systems. A growing number of studies employed big mobility datasets (BMD) …
Inferring inter-city trip purpose from the perspective of the group
Although trip purpose inference based on passively collected data has long been
investigated, less attention has been paid to inter-city trips. The reason is, except using ticket …
investigated, less attention has been paid to inter-city trips. The reason is, except using ticket …
Mobility Analysis Workflow (MAW): An accessible, interoperable, and reproducible container system for processing raw mobile data
Mobility analysis, or understanding and modeling of people's mobility patterns in terms of
when, where, and how people move from one place to another, is fundamentally important …
when, where, and how people move from one place to another, is fundamentally important …