Graph neural network for traffic forecasting: A survey
Traffic forecasting is important for the success of intelligent transportation systems. Deep
learning models, including convolution neural networks and recurrent neural networks, have …
learning models, including convolution neural networks and recurrent neural networks, have …
Mobile phone location data for disasters: A review from natural hazards and epidemics
Rapid urbanization and climate change trends, intertwined with complex interactions of
various social, economic, and political factors, have resulted in an increase in the frequency …
various social, economic, and political factors, have resulted in an increase in the frequency …
scikit-mobility: A Python library for the analysis, generation and risk assessment of mobility data
The last decade has witnessed the emergence of massive mobility data sets, such as tracks
generated by GPS devices, call detail records, and geo-tagged posts from social media …
generated by GPS devices, call detail records, and geo-tagged posts from social media …
Machine learning on the COVID-19 pandemic, human mobility and air quality: A review
The ongoing COVID-19 global pandemic is touching every facet of human lives (eg, public
health, education, economy, transportation, and the environment). This novel pandemic and …
health, education, economy, transportation, and the environment). This novel pandemic and …
Evaluation of home detection algorithms on mobile phone data using individual-level ground truth
Inferring mobile phone users' home location, ie, assigning a location in space to a user
based on data generated by the mobile phone network, is a central task in leveraging …
based on data generated by the mobile phone network, is a central task in leveraging …
Exploring city digital twins as policy tools: A task-based approach to generating synthetic data on urban mobility
G Papyshev, M Yarime - Data & Policy, 2021 - cambridge.org
This article discusses the technology of city digital twins (CDTs) and its potential applications
in the policymaking context. The article analyzes the history of the development of the …
in the policymaking context. The article analyzes the history of the development of the …
Multimodal urban mobility and multilayer transport networks
L Alessandretti, LG Natera Orozco… - … and Planning B …, 2023 - journals.sagepub.com
Transportation networks, from bicycle paths to buses and railways, are the backbone of
urban mobility. In large metropolitan areas, the integration of different transport modes has …
urban mobility. In large metropolitan areas, the integration of different transport modes has …
Self-supervised human mobility learning for next location prediction and trajectory classification
Massive digital mobility data are accumulated nowadays due to the proliferation of location-
based service (LBS), which provides the opportunity of learning knowledge from human …
based service (LBS), which provides the opportunity of learning knowledge from human …
Modeling international mobility using roaming cell phone traces during COVID-19 pandemic
Most of the studies related to human mobility are focused on intra-country mobility. However,
there are many scenarios (eg, spreading diseases, migration) in which timely data on …
there are many scenarios (eg, spreading diseases, migration) in which timely data on …
Bi‐GRCN: A Spatio‐Temporal Traffic Flow Prediction Model Based on Graph Neural Network
W Jiang, Y Xiao, Y Liu, Q Liu, Z Li - Journal of Advanced …, 2022 - Wiley Online Library
Because traffic flow data has complex spatial dependence and temporal correlation, it is a
challenging problem for researchers in the field of Intelligent Transportation to accurately …
challenging problem for researchers in the field of Intelligent Transportation to accurately …