Overview
City Science was commissioned by Cornwall County Council to provide a comprehensive mode choice and trip demand forecasts for Truro, to understand trip demand scenarios through to 2030 and to undertake accessibility analysis to evaluate gaps in current and future transport provision.
Our Work
Our work involved consolidation of local plan data, geospatial tagging of sites and development of incremental population projections by LSOA. Additional datasets were collected to inform the model, including transport network, transport models and travel demand data.
This included:
- Consolidation, sifting and analysis of local plan data, such as geospatial tagging of residential and employment sites, as well as development of incremental population projections by LSOA
- Collection and evaluation of land use against disparate datasets including modal transport networks, models and travel demand data, to evaluate each site’s transport provision
- Development of a 2030 baseline, reflecting the region’s Masterplan, estimating demographic mixes, future network provision and local job accessibility statistics
- Application of a multi-variate model to establish the modal share and modal trip rates from each land use zone
- Analysis and spatial data visualisation such as heatmaps, desire lines and network assignment
Finally, the future demand matrix was made available to the Council to access through our web-based Cadence modelling tool, enabling users to immediately test impacts on a variety of infrastructure enhancement and interventions. The matrix is fully integrated with the Council’s existing SATURN model, enabling automated conversion to agent-based simulation. The model goes beyond their existing road-based model, incorporating alternative modes, such as public transport.
Outcomes
Our visualised, easy to use and understand outline demand model enabled the council to understand future trip demand scenarios and to undertake accessibility analysis to evaluate gaps in current and future transport provision, for Truro’s expected significant housing growth with an additional 3,900 homes allocated in the Local Plan to 2030.
The project also provided a foundation to enable additional analytics reports and tools for the Council in the future.

