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Transport Data Science Reading List

Transport Data Science, 2019/20, Semester 2
Dr Robin Lovelace
Tutor information is taken from the Module Catalogue


  • Paper on the stplanr paper for transport planning (available online) (Lovelace and Ellison 2017)
  • Introductory and advanced content on geographic data in R, especially the transport chapter (available free online) (Lovelace, Nowosad, and Meunchow 2018)
  • Paper on analysing OSM data in Python (available online) (Boeing 2017)

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  • Introduction to data science with R (available free online) (Grolemund and Wickham 2016)

  • Introductory textbook introducing machine learning with lucid prose and worked examples in R (available free online) (James et al. 2013)

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  • Book on transport data science in Python (Fox 2018)
  • For context, a report on the ‘transport data revolution’ (Transport Systems Catapult 2015)
  • Seminal text on visualisation (available online, style available in the tufte R package) (Tufte 2001)   
  • A paper on the use of SmartCard data (Gschwender, Munizaga, and Simonetti 2016)
  • An academic paper describing the development of a web application for the Department for Transport (Lovelace et al.

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Specific/online resources

  • It’s worth thinking about what you want to do next so I recommend taking a look for ‘data science’ and transport jobs on sites such as

  • For a refresher on maths it may be useful to have a maths text book on hand. This should cover mathematical concepts including vectors, matrices, eigenvectors, numerical parameter optimization, calculus, dierential equations, Gaussian distributions, Bayes’ rule, covariance matrices.

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Boeing, Geoff. 2017. “OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks.” Computers, environment and urban systems. ISSN: 0198-9715 65 (September): 126–39.

Fox, Charles. 2018. Data science for transport : a self-study guide with computer exercises ISBN: 9783319729527. 1st ed. 2018 edition. New York, NY: Springer.

Grolemund, Garrett, and Hadley Wickham. 2016. R for data science : import, tidy, transform, visualize, and model data ISBN: 9781491910368 (e-book) 1 edition. O’Reilly Media.

Gschwender, Antonio, Marcela Munizaga, and Carolina Simonetti. 2016. “Using Smart Card and GPS Data for Policy and Planning: The Case of Transantiago.” Research in Transportation Economics, Competition and ownership in land passenger transport (selected papers from the thredbo 14 conference), 59 (November): 242–49.

James, Gareth, Daniela Witten, Trevor Hastie, and Robert Tibshirani. 2013. An introduction to statistical learning : with applications in R ISBN: 9781461471370 (acid-free paper); 1461471370 (acid-free paper); 9781461471387 (eBook); 1461471389 (eBook). Springer Science & Business Media.

Lovelace, Robin, and Richard Ellison. 2017. “Stplanr: A Package for Transport Planning.” The R Journal.

Lovelace, Robin, Anna Goodman, Rachel Aldred, Nikolai Berkoff, Ali Abbas, and James Woodcock. 2017. “The Propensity to Cycle Tool: An Open Source Online System for Sustainable Transport Planning.” Journal of Transport and Land Use 10 (1).

Lovelace, Robin, Jakub Nowosad, and Jannes Meunchow. 2018. Geocomputation with R. CRC Press.

Transport Systems Catapult. 2015. “The Transport Data Revolution.” Government. Transport Systems Catapult.

Tufte, Edward R. 2001. The Visual Display of Quantitative Information. 2nd ed. Cheshire, Conn: Graphics Press.

This list was last updated on 08/10/2018