Citation

Sobral T, Galvão T, Borges J. Sensors (Basel) 2019; 19(2): s19020332.

Affiliation

INESC TEC, Faculty of Engineering, University of Porto, Porto 4200-465, Portugal. jlborges@fe.up.pt.

Copyright

(Copyright © 2019, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/s19020332

PMID

30650641

Abstract

Intelligent Transportation Systems are an important enabler for the smart cities paradigm. Currently, such systems generate massive amounts of granular data that can be analyzed to better understand people's dynamics. To address the multivariate nature of spatiotemporal urban mobility data, researchers and practitioners have developed an extensive body of research and interactive visualization tools. Data visualization provides multiple perspectives on data and supports the analytical tasks of domain experts. This article surveys related studies to analyze which topics of urban mobility were addressed and their related phenomena, and to identify the adopted visualization techniques and sensors data types. We highlight research opportunities based on our findings.

Language: en

Keywords

data visualization; intelligent transportation sytems; spatiotemporal data; urban mobility