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Data for travel behaviour research: recent advances, challenges and opportunities in the era of smart cities

In: Handbook of Travel Behaviour

Author

Listed:
  • Sylvia Y. He
  • Sui Tao
  • Zhenzhen Wang
  • Shuli Luo

Abstract

Travel behaviour is a field that relies heavily on empirical data, especially data representing people’s movement and usage of different transport systems and networks in the city. This chapter will summarise the traditional data used for travel behaviour research and then considers the discourse surrounding the development of smart cities and the associated new (and often big) data and analytical methods that enable the exploration of uncharted territory in travel behaviour research. We will review recent advances to travel behaviour research that utilise new and emerging data. These studies are grouped by four main types of new and emerging data: Global Positioning System and trajectory data, smart card data, mobile phone data and social media data. In addition, we will identify the potential value of other types of data in smart cities, such as charging data derived from e-mobilities, and present a visualisation analysis of an example dataset. Finally, we will summarise key common challenges and opportunities related to data in the context of travel behaviour research in the era of smart cities. We will conclude the chapter with a brief recapitulation and discussion of potential future research directions.

Suggested Citation

  • Sylvia Y. He & Sui Tao & Zhenzhen Wang & Shuli Luo, 2024. "Data for travel behaviour research: recent advances, challenges and opportunities in the era of smart cities," Chapters, in: Dimitris Potoglou & Justin Spinney (ed.), Handbook of Travel Behaviour, chapter 11, pages 197-218, Edward Elgar Publishing.
  • Handle: RePEc:elg:eechap:19696_11
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    File URL: https://www.elgaronline.com/doi/10.4337/9781839105746.00018
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