A survey on deep learning for human mobility

M Luca, G Barlacchi, B Lepri… - ACM Computing Surveys …, 2021 - dl.acm.org
The study of human mobility is crucial due to its impact on several aspects of our society,
such as disease spreading, urban planning, well-being, pollution, and more. The …

[PDF][PDF] Deep learning for human mobility: a survey on data and models

M Luca, G Barlacchi, B Lepri… - arXiv preprint arXiv …, 2020 - openportal.isti.cnr.it
Urban population is increasing strikingly and human mobility is becoming more complex
and bulky, affecting crucial aspects of people lives such as the spreading of viral diseases …

Deeptransport: Prediction and simulation of human mobility and transportation mode at a citywide level

X Song, H Kanasugi, R Shibasaki - … of the twenty-fifth international joint …, 2016 - dl.acm.org
Traffic congestion causes huge economic loss worldwide in every year due to wasted fuel,
excessive air pollution, lost time, and reduced productivity. Understanding how humans …

Deepurbanmomentum: An online deep-learning system for short-term urban mobility prediction

R Jiang, X Song, Z Fan, T Xia, Q Chen… - Proceedings of the …, 2018 - ojs.aaai.org
Big human mobility data are being continuously generated through a variety of sources,
some of which can be treated and used as streaming data for understanding and predicting …

Human trajectory forecasting in crowds: A deep learning perspective

P Kothari, S Kreiss, A Alahi - IEEE Transactions on Intelligent …, 2021 - ieeexplore.ieee.org
Since the past few decades, human trajectory forecasting has been a field of active research
owing to its numerous real-world applications: evacuation situation analysis, deployment of …

[HTML][HTML] A deep gravity model for mobility flows generation

F Simini, G Barlacchi, M Luca, L Pappalardo - Nature communications, 2021 - nature.com
The movements of individuals within and among cities influence critical aspects of our
society, such as well-being, the spreading of epidemics, and the quality of the environment …

Urban human mobility: Data-driven modeling and prediction

J Wang, X Kong, F Xia, L Sun - ACM SIGKDD explorations newsletter, 2019 - dl.acm.org
Human mobility is a multidisciplinary field of physics and computer science and has drawn a
lot of attentions in recent years. Some representative models and prediction approaches …

Deepmove: Predicting human mobility with attentional recurrent networks

J Feng, Y Li, C Zhang, F Sun, F Meng, A Guo… - Proceedings of the 2018 …, 2018 - dl.acm.org
Human mobility prediction is of great importance for a wide spectrum of location-based
applications. However, predicting mobility is not trivial because of three challenges: 1) the …

Predicting human mobility via graph convolutional dual-attentive networks

W Dang, H Wang, S Pan, P Zhang, C Zhou… - Proceedings of the …, 2022 - dl.acm.org
Human mobility prediction is of great importance for various applications such as smart
transportation and personalized recommender systems. Although many traditional pattern …

Analyzing large-scale human mobility data: a survey of machine learning methods and applications

E Toch, B Lerner, E Ben-Zion, I Ben-Gal - Knowledge and Information …, 2019 - Springer
Human mobility patterns reflect many aspects of life, from the global spread of infectious
diseases to urban planning and daily commute patterns. In recent years, the prevalence of …