  In this paper, we introduce and test our algorithm to create a road network
representation for city-scale active transportation simulation models. The
algorithm relies on open and universal data to ensure applicability for
different cities around the world. In addition to the major roads, their
geometries and the road attributes typically used in transport modelling (e.g.,
speed limit, number of lanes, permitted travel modes), the algorithm also
captures minor roads usually favoured by pedestrians and cyclists, along with
road attributes such as bicycle-specific infrastructure, traffic signals, and
road gradient. Furthermore, it simplifies the network's complex geometries and
merges parallel roads if applicable to make it suitable for large-scale
simulations. To examine the utility and performance of the algorithm, we used
it to create a network representation for Greater Melbourne, Australia and
compared the output with a network created using an existing transport
simulation toolkit along with another network from an existing city-scale
transport model from the Victorian government. Through simulation experiments
with these networks, we illustrated that our algorithm achieves a very good
balance between simulation accuracy and run-time. For routed trips on our
network for walking and cycling it is of comparable accuracy to the common
network conversion tools in terms of travel distances of the shortest paths
while being more than two times faster when used for simulating different
sample sizes. Therefore, our algorithm offers a flexible solution for building
accurate and efficient road networks for city-scale active transport models for
different cities around the world.
