A framework for road change detection and map updating

Extracting road information from point clouds obtained through mobile laser scanning (MLS) is essential for autonomous vehicle navigation, and has hence garnered a growing amount of research interest...

Terrestrial laser scanning (TLS) is a promising tool for estimating leaf area index (LAI).

Research towards an innovative solution to the problem of automated updating of road network databases is presented.

It moves away from existing methods where vendors of road network databases either go through the time consuming and logistically challenging process of driving along roads to register changes or use update methods that rely on remote sensing images.

At a later stage, when sufficient information on road geometry and other characteristics has accumulated in order to have confidence in the classification, the probationary flag would be lifted and the new road permanently added to the road network database.

To investigate this novel approach, GPS-based trajectory data collected in London are analysed using a Snap-Drift Neural Network (SDNN) and categorised into different road class segments.