Researchers at the University of Melbourne are looking for spatial data that will help them understand the way hazards affect road networks. This is particularly useful as vehicles develop greater autonomy in navigating these hazards.
Eight tags have been added to our list to help facilitate this research. We’re inviting you to take part and help us identify and tag these incidents in images.
Have you observed one or more of these incidents while capturing imagery in Mapillary:
The researchers are looking for incidents that actually affect the road network. Here is an example of such an incident and how it can be tagged.
More detailed instructions on tagging and searching tags is available on our help portal.
The researchers have provided some background on their objectives:
In pursuit of safer autonomous vehicles we are currently building a dataset that covers incidents that may occur on street networks. In this task we are looking to expand the following five categories of incidents: animals on or dangerously close to the road, snow, flooding, crashes, and treefall. Each of these should affect the driving surface in some way. For instance, snow is only relevant if the driving surface itself is covered in it. Likewise, a fallen tree that is not blocking the driving surface is not an incident either. We are interested in images from all across the globe, but images from the United Kingdom are particularly preferred.