Big Data for Sustainable Urban Transport

Stephen Jia Wang, Patrick Moriarty

Research output: Chapter in book / Conference proceedingChapter in an edited book (as author)Academic researchpeer-review

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.
Original languageEnglish
Title of host publicationBig Data for Urban Sustainability
PublisherSpringer International Publishing AG
Pages81-103
ISBN (Electronic)978-3-319-73610-5
ISBN (Print)978-3-319-73608-2
DOIs
Publication statusPublished - Mar 2018
Externally publishedYes

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