Project overview
Active travel has received increased investment and interest in many countries both due to COVID-19 and to policies which promote a shift to active travel to support a wide range of public and individual goods. However, the majority of investment so far has been focused on physical infrastructure to facilitate active travel, rather than on the data infrastructure which can help enable people to shift trips to active modes.
There is no comprehensive geospatial representation of the active travel infrastructure network in the UK, and current fragmented data and data models and a lack of data standards pose a barrier to the development of the applications which are needed to support planners, users and journey planning. There is therefore a need for a more integrated, better-connected and more richly attributed active travel geospatial network model, linked to comprehensive datasets on the location and characteristics of active travel infrastructure. The RATIN project aimed to make a significant contribution towards meeting this need.
Phase 1 of the project (completed in 2022) undertook a comprehensive review of datasets and data models for active travel infrastructure, and developed a high level data framework for geospatial active travel infrastructure networks. Work in Phases 2 and 3 then built on this by developing methods to populate this framework for a case study area in England, building on the existing Ordnance Survey Mastermap transport networks.
There has been a particular focus on five strands of work:
- using crowd-sourced data from OS Maps provided GPS traces of actual active travel trips to fill gaps in the base OS path network
- extending the Mastermap data model to allow the representation of differential pavement presence
- characteristics and crossing points on individual road links
further enhancement of this pavement presence - information by calculating detailed information on pavement widths derived from OS Mastermap topography data
- using a range of methods to derive information on path surface type from remotely sensed data, focusing particularly on the use of high resolution aerial imagery
- linking together the datasets produced in the earlier stages of the research with other existing datasets on attributes relating to active travel infrastructure, such as street lighting, road safety and air pollution.
The outputs from the data processing have been integrated and presented in a demonstrator routing tool, allowing the benefits of the enhanced datasets to be easily demonstrated to key stakeholders. Information on the demonstrator tool can be accessed via the GeoData Institute website.
