A nodal approach for estimating potential cycling demand

Establishing cycling as a prominent utility mode is recognised as central to creating sustainable transport systems in many cities around the world. Strategies of starter cycling cities are often biased to the supply of infrastructure along prominent corridors without acknowledging the nature, quantum or location of potential demand for cycling. Decisions are frequently left to local knowledge and experience of local needs, resulting in a bias with little opportunity for repeatability or reproducibility. This study proposes a data-driven approach to estimate the potential market for cycling geographically. Estimates are based on the number of potential cyclists in close proximity to the destinations they want to access. The paper demonstrates the method using Cape Town, South Africa as a case study. Given the virtual absence of utility cycling in the city, characteristics of cyclists in cities where cycling is popular are used to identify potential cyclists. Destination nodes are stratified in terms of the characteristics of their users, while home locations of persons with these characteristics are identified from a publicly available synthetic population for Cape Town. Analysis provides an order of magnitude indication of the cycling potential of selected nodes. It also shows areas with many potential cyclists that are not in proximity of desired destination. The results enable city authorities to focus detailed investigations and interventions where a critical mass of cycling may be achieved with the least effort and in the shortest time.