Revealing an Inherently Limiting Factor in Human Mobility Prediction

Licia Amichi, Aline Viana Carneiro, Mark Crovella, Antonio Loureiro

Research output: Contribution to journalArticlepeer-review

Abstract

Predicting how humans move within space and time is a central topic in many scientific domains such as epidemic propagation, urban planning, and ride-sharing. However, current studies neglect individuals' preferences to explore and discover new areas. Yet, neglecting novelty-seeking activities at first glance appears to be inconsequential on the ability to understand and predict individuals' trajectories. We claim and show the opposite in this work: exploration-like visits strongly impact mobility understanding and anticipation. We start by proposing a new approach to identifying exploration visits. Based on that, we construct individuals' mobility profiles using their exploration inclinations - Scouters (i.e., extreme explorers), Routiners (i.e., extreme returners), and Regulars (i.e., with no extreme behavior). Finally, we evaluate the impacts of novelty-seeking, quality of the data, and the prediction task formulation on the theoretical and practical predictability extents. The results show the validity of our profiling and highlight the obstructive impacts of novelty-seeking activities on the predictability of human trajectories. In particular, in the next-place prediction task, from 40% to 90% of predicted locations are wrong, notably with Scouters.

Original languageEnglish
Pages (from-to)635-649
Number of pages15
JournalIEEE Transactions on Emerging Topics in Computing
Volume11
Issue number3
DOIs
StatePublished - Jul 1 2023
Externally publishedYes

Funding

This work was supported in part by CAPES, CNPq, FAPEMIG, and FAPESP under Grant 18/23064-8 and in part by INRIA, Sorbonne UPMC, LINCS, STIC AmSud LINT under Grant 22-STIC-07.

FundersFunder number
Sorbonne UPMC22-STIC-07
Institut national de recherche en informatique et en automatique (INRIA)
Fundação de Amparo à Pesquisa do Estado de São Paulo18/23064-8
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Conselho Nacional de Desenvolvimento Científico e Tecnológico
Fundação de Amparo à Pesquisa do Estado de Minas Gerais

    Keywords

    • Individual mobility analytic
    • mobility understanding and profiling
    • predictability
    • prediction

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