SurfaceAI: Automated creation of cohesive road surface quality datasets based on open street-level imagery
This addresses the problem of road unevenness affecting safety and comfort, especially for vulnerable road users, by providing data for infrastructure modeling, though it is incremental as it builds on existing imagery and methods.
The paper tackles the lack of detailed road surface data by introducing SurfaceAI, a pipeline that uses open street-level imagery to generate georeferenced datasets on road surface type and quality, achieving automated creation from crowdsourced Mapillary data.
This paper introduces SurfaceAI, a pipeline designed to generate comprehensive georeferenced datasets on road surface type and quality from openly available street-level imagery. The motivation stems from the significant impact of road unevenness on the safety and comfort of traffic participants, especially vulnerable road users, emphasizing the need for detailed road surface data in infrastructure modeling and analysis. SurfaceAI addresses this gap by leveraging crowdsourced Mapillary data to train models that predict the type and quality of road surfaces visible in street-level images, which are then aggregated to provide cohesive information on entire road segment conditions.