Royal Statistical Society Bradford, 2017-01-25, University of Leeds Geography Department.

Talk structure

  1. Computing needs of transport planners

  2. Open source tools in statistics/transport

  3. Case studies (stplanr + PCT)

  • But first some context
  • Then let's talk solutions



  • The transport system is not working well for anyone
  • To 'fix' it, policy interventions are needed
  • Policy interventions can be more effective when locally targetted
  • However, there are infinite potential interventions at the local level
  • Evidence is needed to prioritise among the infinity of options
  • Only a systematic and objective evidence base will do
  • And that means data + statistics! 🔢
  • And that means computing 🖥️
  • And that means human-computer interaction 👨👩💻
  • And that means software is vital for sustainable transport policy

What's wrong with the transport system?

"Works fine for me"

Locally targetted vs national interventions

  • Nationally uniform transport policies have several advantages
    • Avoid 'mixed messages'
    • In some cases essential (e.g. fuel prices)
    • We're all in it together
  • BUT, locally specific transport policies can boost cost-effectiveness
    • Should walking/cycle paths be the same width throughout?
    • Point facilities will be used more if they're located sensibly (e.g. bus stops)
    • Cycle share schemes much more effective when spatial configuration matches urban form

Some transport statistics

  • Transport eats time. We spend on average 6% of our lives (sleeping/resting: 37%; commuting: 1%; paid work: 25%) (King and Bergh 2017).

  • Transport eats space. More than half many US cities spaces are occupied by parking (~20%) and streets (~40%). In Texas, for example, 21.3% of land space was taken by surface parking (Source:

  • Transport eats energy. In 2015 it accounted for 39.9% of final energy consumption (DECC).

Space used by transport (USA)

Energy use in transport (UK)

Energy use in Transport nationally

Final energy consumption (excluding non-energy use) was 1.9 per cent higher than in
2014 [0.3% seasonally adjusted], with rises in the domestic, transport and services sectors but with a fall in the industrial sector. The rise in consumption was due to increased
transport demand likely due to lower petroleum prices.

(DECC 2016)

Transport fuel prices

Source: DECC 2016

Computational needs of transport planners

Tools for the trade