Data Science for Transport Planning
- Start date: 18th September 2025
- End date: 19th September 2025
- Duration: 2 days
Course overview
Based on demand, we’re organising a 2-day course teaching modern data science skills for transport planning, focussed on transport planning practitioners. This course will take place on the 18th and 19th of September 2025.
Course structure
Day 1: Introduction to R/RStudio
- 10:00 - 11:00 Introduction to Data Science for Transport Planning
- 11:00 - 12:30 Finding, importing and cleaning transport datasets
– Origin-destination datasets
– OpenStreetMap (OSM) and Ordnance Survey (OS) OpenRoads datasets
– Stats19 road safety data
- 12:30 - 13:30: lunch
- 13:30 - 15:00 Origin-destination data analysis
- 15:00 - 15:15 break and refreshments
- 15:15 - 17:00 Routing and route network analysis
- This will cover setting up an OpenTripple API and using it to calculate routes and distances using GTFS data.
Day 2:
Schedule
- 09:00 - 10:45 spatio-temporal data
– Demonstration of open-access OD data with hourly resolution
– Demonstration with stats19 data for road safety analysis
- 10:45 - 11:15 break and refreshments
- 11:15 - 12:30 OD Transport data visualisation
- 12:30 - 13:30 lunch
- 13:30 - 15:00 Best practices for data science in transport planning
– Version control with Git and GitHub
– Reproducible research with Quarto
- 15:00 - 16:00 Advanced topics
– Visualising large datasets
– Route network integration
• We’ll present ways to join different networks, e.g. OSM networks
– Deploying your work as web applications
Who should attend?
Prerequisites
- Experience with transport planning concepts and datasets, such as origin-destination data and route networks.
- Basic programming skills in R, Python or similar.
- A laptop with R and RStudio (recommended) or a Python distribution such as Anaconda and an editor such as VS Code or Jupyter Notebook set-up.
Speakers
Robin Lovelace is a researcher at the Leeds Institute for Transport Studies (ITS) and the Leeds Institute for Data Analytics (LIDA). Robin has many years of experience of using R for academic research and has taught numerous R courses at all levels. He has developed popular R resources including the popular books Efficient R Programming (Gillespie and Lovelace 2016), Spatial Microsimulation with R (Lovelace and Dumont 2016), and Geocomputation with R (Lovelace et al. 2019).
These skills have been applied on a number of projects with real-world applications, including the Propensity to Cycle Tool, a nationally scalable interactive online mapping application, and the stplanr package.
Fee information
£950
Venue details
ITS 1.11
The course will be held in the Institute for Transport Studies, Room 1.11. It is open to students, academic staff and external delegates. Please note the fee includes learning materials, lunch and refreshments during the course.
The course is also available as bespoke or in-company training.
Contact us
Institute for Transport Studies
Leeds LS2 9JT
Email: cpd@its.leeds.ac.uk