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Engineering and Applied Sciences Optimization pp 107–128Cite as

Computational Intelligence and Optimization for Transportation Big Data: Challenges and Opportunities

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Part of the book series: Computational Methods in Applied Sciences ((COMPUTMETHODS,volume 38))

Abstract

With the overwhelming amount of transportation data being gathered worldwide, Intelligent Transportation Systems (ITS) are faced with several modeling challenges. New modeling paradigms based on Computational Intelligence (CI) that take advantage of the advent of big datasets have been systematically proposed in literature. Transportation optimization problems form a research field that has systematically benefited from CI. Nevertheless, when it comes to big data applications, research is still at an early stage. This work attempts to review the unique opportunities provided by ITS and big data and discuss the emerging approaches for transportation modeling. The literature dedicated to big data transportation applications related to CI and optimization is reviewed. Finally, the challenges and emerging opportunities for researchers working with such approaches are also acknowledged and discussed.

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Acknowledgments

This work is part of research co-financed by the European Union (European Social Fund—ESF) and the Hellenic National Funds, through the Operational Program “Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF)—Research Funding Program “Aristeia I”. This paper is dedicated to the memory of my mentor and friend, Professor Matthew G. Karlaftis.

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  1. Department of Transportation Planning and Engineering, School of Civil Engineering, National Technical University of Athens, Athens, Greece

    Eleni I. Vlahogianni

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  1. Eleni I. Vlahogianni
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Correspondence to Eleni I. Vlahogianni .

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  1. Institute of Structural Analysis & Seismic Research, National Technical University of Athens, Athens, Greece

    Nikos D. Lagaros

  2. Institute of Structural Analysis & Antiseismic Research, National Technical University of Athens, Athens, Greece

    Manolis Papadrakakis

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Vlahogianni, E.I. (2015). Computational Intelligence and Optimization for Transportation Big Data: Challenges and Opportunities. In: Lagaros, N., Papadrakakis, M. (eds) Engineering and Applied Sciences Optimization. Computational Methods in Applied Sciences, vol 38. Springer, Cham. https://doi.org/10.1007/978-3-319-18320-6_7

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  • DOI: https://doi.org/10.1007/978-3-319-18320-6_7

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