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TRAN5340M
Transport Data Science Reading List

Transport Data Science, 2021/22, Semester 2
Dr Robin Lovelace
r.lovelace@leeds.ac.uk
Tutor information is taken from the Module Catalogue

Core

  • The transport chapter of Geocompution with R (available free online) (Lovelace, Nowosad, and Muenchow 2019)
  • Introduction to data science with R (available free online) (Grolemund and Wickham 2016)

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Optional

  • Paper on open source tools for geographic analysis in transport planning (Lovelace 2021)
  • Papers describing the use of data science to solve transport planning problems (e.g. Szell et al. 2021; Orozco et al. 2020)
  • Academic paper describing the development of a web application for the Department for Transport (Goodman et al. 2019)
  • Paper on analysing OSM data in Python (available online) (Boeing 2017)

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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 www.cwjobs.co.uk

  • 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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Bibliography

Boeing, Geoff. 2017. “OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks.” Computers, Environment and Urban Systems 65 (September): 126–39. https://doi.org/10.1016/j.compenvurbsys.2017.05.004.

Goodman, Anna, Ilan Fridman Rojas, James Woodcock, Rachel Aldred, Nikolai Berkoff, Malcolm Morgan, Ali Abbas, and Robin Lovelace. 2019. “Scenarios of Cycling to School in England, and Associated Health and Carbon Impacts: Application of the ‘Propensity to Cycle Tool’.” Journal of Transport & Health 12 (March): 263–78. https://doi.org/10.1016/j.jth.2019.01.008.

Graells-Garrido, Eduardo, Vanessa Peña-Araya, and Loreto Bravo. 2020. “Adoption-Driven Data Science for Transportation Planning: Methodology, Case Study, and Lessons Learned.” Sustainability  12 (15, 15): 6001. https://doi.org/10.3390/su12156001.

Grolemund, Garrett, and Hadley Wickham. 2016. R for Data Science. 1 edition. O’Reilly Media.

Lovelace, Robin. 2021. “Open Source Tools for Geographic Analysis in Transport Planning.” Journal of Geographical Systems, January. https://doi.org/10.1007/s10109-020-00342-2.

Lovelace, Robin, Jakub Nowosad, and Jannes Muenchow. 2019. Geocomputation with R. CRC Press. https://geocompr.robinlovelace.net/.

Lovelace, Robin, John Parkin, and Tom Cohen. 2020. “Open Access Transport Models: A Leverage Point in Sustainable Transport Planning.” Transport Policy 97 (October): 47–54. https://doi.org/10.1016/j.tranpol.2020.06.015.

Olmos, Luis E., Maria Sol Tadeo, Dimitris Vlachogiannis, Fahad Alhasoun, Xavier Espinet Alegre, Catalina Ochoa, Felipe Targa, and Marta C. González. 2020. “A Data Science Framework for Planning the Growth of Bicycle Infrastructures.” Transportation Research Part C: Emerging Technologies 115 (June): 102640. https://doi.org/10.1016/j.trc.2020.102640.

Orozco, Luis, Federico Battiston, Gerardo Iñiguez, and Michael Szell. 2020. “Data-Driven Strategies for Optimal Bicycle Network Growth.” Royal Society Open Science 7 (December): 201130. https://doi.org/10.1098/rsos.201130.

Szell, Michael, Sayat Mimar, Tyler Perlman, Gourab Ghoshal, and Roberta Sinatra. 2021. “Growing Urban Bicycle Networks.” July 5, 2021. http://arxiv.org/abs/2107.02185.

This list was last updated on 08/12/2021