Improving estimates of capacity of populations to make journeys by walking and cycling: An individual modelling process applied to whole populations using spatial microsimulation

A novel approach to estimating a population‟s capacity to travel by walking and cycling (also referred to as active modes) is presented. Estimating capacity to walk and cycle is distinct from predicting future walking and cycling behaviour based upon current behaviour. Capacity is useful in developing anticipatory policy responses to transport scenarios which are not based on current trends or are attempting to encourage transformational policies. We identify several possible application areas for this method (an indicator of resilience to permanent reduction in fuel supply; assessing walking and cycling as a strategy to adapt to short term fuel disruptions; improvement of walking cycling targets; better estimation of the service area of public transport stops; integration into accessibility measures and better understanding transport based social exclusion). Current estimations of capacity to walk and cycle applied by practitioners are poor: Frequently a simple distance buffer is applied, or the whole population‟s capacity to travel is estimated based on the current behaviour of a small sample of existing cyclists. Factors such as the variation in physical capability between individuals and topography are ignored. The improved model we describe incorporates an estimate of the maximum distance that could physically be travelled by an individual given a time budget, given their physical health, age characteristics, topography, headwinds, constraints on travel such as bike availability and the need to incorporate escort trips on the way to activities. The focus of this paper is on explaining the method of estimating capacity of individuals to travel by active modes. However, we explain that the model can be implemented for the whole population of many small zones by using spatial microsimulation (also known as population synthesis) to generate the individual attributes required as inputs to the model. A simple example demonstrates that this modelling process can produce a considerable improvement in estimation of capacity to travel by active modes over simple buffer methods.