Quantifying Network Resilience

Project Outline

City Science was awarded a Department for Transport Innovation Grant (T-TRIG) to utilise their modelling expertise to develop a toolkit that enables Local Authorities to identify, quantify and predict network resilience issues within transport networks.


City Science Response

Using the team’s transport data and analytics expertise, City Science developed a toolkit to answer the key burning questions:

  • How often and how badly are specific road segments affected in the network?

  • What routes are most problematic and how bad does it often get?

  • What is the impact of an incident? How should we prepare a re-routing strategy?

  • Which resilience improvements should we prioritise from a range of policy objectives?

Using TrafficMaster speed data captured every 15 minutes over the course of 3 years City Science developed statistical metrics to answer these key questions. Using these metrics - the “Link Event”, the "347 Day Event" (looking at the worst 5% of cases) and the “Volatility of Congestion” – cities can build up a comprehensive picture of their network and the key resilience issues. In particular, the toolkit allows cities to visualise and prioritise key resilience issues between Areas of Economic Importance (AEIs) with the goal of improving connectivity and productivity.

To utilise the large geospatial and temporal dataset, City Science developed network pruning and robust interpolation processes to seamlessly manage the data. Analyses were developed in Python and outputs communicated through a series of geospatial and graphical visualisations.


A unique series of metrics to quantify and understand resilience were developed. The metrics can be aggregated using economic, population or other data to drive key policy responses to resilience. The toolkit can also be used to monitor changes to resilience over time. The Department for Transport received a series of visualisations and a high-quality report.
“City Science brought an innovative new approach to transport modelling by developing techniques to analyse network resilience. Delivering a suite of tools, enabled increased end-user understanding of resilience and how it relates to specific economic corridors or the entire road network. This resulted for example, to greater understanding on the positive or negative effects of proposed remedial works, thereby influencing future investment decisions. Innovation like this opens new opportunities and can deliver palpable change, we look forward to seeing the adoption of this work into mainstream transport planning practice."
- Simon Yarwood, Knowledge Transfer Manager
The road network in and around the city of Exeter was used as the project demonstrator. Some sample outputs are shown below.
Frequency of congestion events on key routes in and around Exeter. Basemap: © OpenStreetMap Contributors.
3D Space-time plot for modal route between Honiton Road and Cowick Street (September 2014 - September 2017, Wednesdays 16:00-17:00)