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 …

[HTML][HTML] Agent-based modeling in urban human mobility: A systematic review

A Divasson-J, AM Macarulla, JI Garcia, CE Borges - Cities, 2025 - Elsevier
Urban mobility is a complex system influenced by various factors such as infrastructure,
technology, and human behavior. Agent-based modeling (ABM) has emerged as a valuable …

[HTML][HTML] Combining heterogeneous data sources for spatio-temporal mobility demand forecasting

II Prado-Rujas, E Serrano, A García-Dopico… - Information …, 2023 - Elsevier
There is a growing need to optimize mobility in medium to large-size cities. The use of a car
for one-person trips is widely established as a common trend, which combined with the age …

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

M Luca, G Barlacchi, B Lepri, L Pappalardo - ar**
prosperous, sustainable, and resilient urban futures. Existing SLRTP decision support tools …

Quantitative and Qualitative Evaluation of Reinforcement Learning Policies for Autonomous Vehicles

L Ferrarotti, M Luca, G Santin, G Previati… - arxiv preprint arxiv …, 2023 - arxiv.org
Optimizing traffic dynamics in an evolving transportation landscape is crucial, particularly in
scenarios where autonomous vehicles (AVs) with varying levels of autonomy coexist with …

Enhancing crowd flow prediction in various spatial and temporal granularities

M Cardia, M Luca, L Pappalardo - Companion Proceedings of the Web …, 2022 - dl.acm.org
The diffusion of the Internet of Things allows nowadays to sense human mobility in great
detail, fostering human mobility studies and their applications in various contexts, from traffic …

Trajectory test-train overlap in next-location prediction datasets

M Luca, L Pappalardo, B Lepri, G Barlacchi - Machine Learning, 2023 - Springer
Next-location prediction, consisting of forecasting a user's location given their historical
trajectories, has important implications in several fields, such as urban planning, geo …

A mechanistic data-driven approach to synthesize human mobility considering the spatial, temporal, and social dimensions together

G Cornacchia, L Pappalardo - ISPRS International Journal of Geo …, 2021 - mdpi.com
Modelling human mobility is crucial in several areas, from urban planning to epidemic
modelling, traffic forecasting, and what-if analysis. Existing generative models focus mainly …