Economic benefits of cycling infrastructure

Primary Author: Robyn Davies (Qld Department of Transport and Main Roads)

Co-Authors: Adam Rogers (Qld Department of Transport and Main Roads) Craig Lawrence (Lytton Advisory) and Ben Vardon (Aurecon Australasia)

Organisation: Per Aurecon Australasia


There is a growing evidence base to suggest that cycling infrastructure is a sound investment which can produce positive returns, however there is little to go on locally to understand from a network perspective the financial benefits to Government.

Given the local gap in research, the authors formulated a methodology, principally based on findings in the Australian Transport System Management Assessment and Planning (ATAP) Guidelines for Active Transport, to quantify the benefits of cycling.


More cycling tackles morbidity, obesity and mental health issues and that means a reduced burden on the public health system. The benefits compound as cycling networks are completed, or made denser, or separated from traffic.

We’ve known about the health benefits of cycling for a long time, but have you ever wondered whether the benefits actually outweigh the capital cost of the infrastructure required to support this activity? Recent research has quantified a range of benefits of cycling and walking which are now encapsulated in Australia’s Transport and Infrastructure Council Australian Transport System Management Assessment and Planning (ATAP) Guidelines for Active Transport.

The economic benefits of this type of investment are real, quantifiable and measurable. When the benefits are monetised, and the number of users are taken into account (sometimes through population forecasting) the benefit cost ratios can rival those of significant road projects. In ageing western countries, that’s of profound interest to policymakers at all tiers of Government, and will ensure that the planning and design of this type of infrastructure remains at the forefront.

This paper details a methodology for determining the economic return on cycling networks based on population data, user profiles and separated/unseparated paths.