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Published in:
The Urgent Need for Advancing Urban Sustainability Read chapter Read first chapter

2018 | OriginalPaper | Chapter

5. Big Data for Sustainable Urban Transport

Authors : Stephen Jia Wang, Patrick Moriarty

Published in: Big Data for Urban Sustainability

Publisher: Springer International Publishing

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Abstract

This chapter re-examines the general solutions proposed to improve the environmental sustainability of transport discussed in Sect. 1.3.2, with a view to understanding the potential for big data in each of these approaches. How can big data be used to reduce transport energy and emissions in cities? Specifically, how can big data encourage modal shift from cars to more environmentally friendly modes, and reduce vehicular transport overall through better trip planning? The chapter also includes a case study of a ‘personal transport planner’ designed for use in Beijing, based on the idea of a monthly personal transport energy quota.

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previous chapter Barriers to the Implementation of Big Data
next chapter Big Data for Urban Energy Reductions
Footnotes
1
This section is a revised and updated version of Sect. 2.​2 in Ref. [51]. Used by permission of Elsevier.
 
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Metadata
Title
Big Data for Sustainable Urban Transport
Authors
Stephen Jia Wang
Patrick Moriarty
Copyright Year
2018
Book
Big Data for Urban Sustainability

Print ISBN: 978-3-319-73608-2

Electronic ISBN: 978-3-319-73610-5

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-73610-5_5