  Random networks are increasingly used to analyse complex transportation
networks, such as airline routes, roads and rail networks. So far, this
research has been focused on describing the properties of the networks with the
help of random networks, often without considering their spatial properties. In
this article, a methodology is proposed to create random networks conserving
their spatial properties. The produced random networks are not intended to be
an accurate model of the real-world network being investigated, but are to be
used to gain insight into the functioning of the network taking into
consideration its spatial properties, which has potential to be useful in many
types of analysis, e.g. estimating the network related risk. The proposed
methodology combines a spatial non-homogeneous point process for vertex
creation, which accounts for the spatial distribution of vertices, considering
clustering effects of the network and a hybrid connection model for the edge
creation. To illustrate the ability of the proposed methodology to be used to
gain insight into a real world network, it is used to estimate standard
structural statistics for part of the Swiss road network, and these are then
compared with the known values.
