  We propose a new method for inferring roads from GPS trajectories to map
construction sites. This task presents a unique challenge due to the erratic
and non-standard movement patterns of construction machinery, which
significantly diverge from typical vehicular traffic on established roads. Our
proposed method first identifies intersections in the road network that serve
as critical decision points, and then connects them with edges to produce a
graph, which can subsequently be used for planning and task-allocation. We
demonstrate the approach by mapping roads at a real-life construction site in
Norway. The method is validated on four increasingly complex segments of the
map. In our tests, the method achieved perfect accuracy in detecting
intersections and inferring roads in data with no or low noise, while its
performance was reduced in map areas with significant noise and consistently
missing GPS updates.
