Abstract
Mobility, transportation and logistics are more and more influenced by a variety of indicators such as new technological developments, ecological and economic changes, political decisions and in particular humans’ mobility behavior. These indicators will lead to massive changes in our daily live with regards to mobility, transportation and logistics. New technologies will lead to a different mobility behavior with new constraints. These changes in mobility behavior and logistics require analytical systems to forecast the required information and probably appearing changes. These systems have to consider different perspectives and employ multiple indicators. Visual Analytics provides both, the analytical approaches by including machine learning approaches and interactive visualizations to enable such analytical tasks. In this paper the main indicators for Visual Analytics in the domain of mobility transportation and logistics are discussed and followed by exemplary case studies to illustrate the advantages of such systems. The examples are aimed to demonstrate the benefits of Visual Analytics in mobility.
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Acknowledgements
This work was partially funded by the Hessen State Ministry for Higher Education, Research and the Arts within the program “Forschung für die Praxis” and was conducted within the research group on Human-Computer Interaction and Visual Analytics (https://vis.h-da.de). The authors would like to thank the students Svenja Lehmann and Walter Oster for their implementation contributions.
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Nazemi, K., Burkhardt, D., Kaupp, L., Dannewald, T., Kowald, M., Ginters, E. (2020). Visual Analytics in Mobility, Transportation and Logistics. In: Ginters, E., Ruiz Estrada, M., Piera Eroles, M. (eds) ICTE in Transportation and Logistics 2019. ICTE ToL 2019. Lecture Notes in Intelligent Transportation and Infrastructure. Springer, Cham. https://doi.org/10.1007/978-3-030-39688-6_12
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DOI: https://doi.org/10.1007/978-3-030-39688-6_12
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