The NTA’s Cycle Propensity Scenarios are designed to provide transport planners and policy makers with information on the impact of changes to levels of cycling which are driven by factors currently not captured in traditional four stage transport models. These scenarios utilise the NTA’s suite of transport models, Regional Modelling System, to assess the impact of such changes on:

  • Levels of cycling
  • Route choice
  • Impact on other modes

The approach leverages the NTA’s Regional Modelling System behavioural models which have been estimated with data from the National Household Travel Survey and the CSO’s POWSCAR dataset, and account for factors such as:

  • User class
  • Cycle speed
  • Trip distance
  • Competing modes
  • Time period
  • Region specific factors

To use the tool, click on the relevant geographic model in the menu list.

What is Cycle Propensity?

Transport models are designed to explain and forecast individuals’ transport choices based upon a number of factors such as travel time, trip distance, available modes, public transport fares, and origin and destination characteristics.

As the factors behind such choices are varied and complex, modellers cannot capture all factors with specific model inputs. Such unmodelled factors include things such as an individual’s perception of a given mode or their own personal preferences.

However, while such factors are not explicitly included in a model, they are known to impact mode, route and destination choices and must still be accounted for. These factors are, therefore, grouped together to create a propensity for a given mode, and included as input variable.

Cycle Propensity in the NTA Models

The NTA models explicitly model the following factors with regard to cycling based upon POWSCAR and NHTS estimations:

  • Trip length
  • Route quality
  • Competing modes, including
    • Walking
    • Public transport services
    • Driving
    • Park and Ride
  • User class and user class speed
  • Trip purposes

Cycle Propensity therefore captures other important factors such as:

  • Perceived safety
  • Weather conditions
  • Cycle parking
  • Interactions with traffic
  • Experience cycling etc.

Adjusting Cycle Propensity

Research has shown that to use propensity for any mode may change over time, and therefore there is a need to consider how this would impact upon transport choices.

The Cycle Propensity Scenarios provide examples of the impact of different potential changes in propensity to cycle, due to changes to factors currently not explicitly captured in the NTA Regional Modelling System. Each Cycle Propensity Scenario uses the powerful suite of transport models to forecast likely cycling mode shares taking account of the proposed propensity level being tested, and how this would interact with other modes of transport available to users. The Scenario captures corresponding changes in other mode shares, showing how changes to cycling can impact multiple modes. This approach builds on the demand forecasting capabilities already built into the suite of transport models and therefore is rooted in well-established transport modelling practices.

Cycle Propensity Scenarios

This site provides three potential scenarios with varying levels of propensity to cycle, being:

  • Medium Propensity: A significant attraction of additional cyclists;
  • High Propensity: A high attraction of additional cyclists;
  • High+ Propensity: A high attraction of additional cyclists coupled with high e-bike uptake.

These scenarios allow exploration of the increased cycling levels that could be achieved through the implementation of appropriate supporting measures to increase cycling uptake. They should be treated as examples of potential cycling futures, rather than definitive forecasts.

Users of the Cycle Propensity Viewer can adjust various parameters in each scenario, allowing examination of the impact of changes in cycle propensity by:

  • Mode Share
  • Trip origin or destination
  • User class
  • Time period