Road Redesign Technique Achieving Enhanced Road Safety by Inpainting with a Diffusion Model
This addresses road safety for authorities and urban planners by providing a tool to redesign roads with minimal intervention, though it is incremental as it applies existing diffusion models to a new domain.
The paper tackles road safety by using a diffusion model to inpaint safe roadway elements into images, replacing accident-prone features, which reduces the likelihood of an image being classified as an accident hotspot by an average of 11.85% in about 2 minutes per image.
Road infrastructure can affect the occurrence of road accidents. Therefore, identifying roadway features with high accident probability is crucial. Here, we introduce image inpainting that can assist authorities in achieving safe roadway design with minimal intervention in the current roadway structure. Image inpainting is based on inpainting safe roadway elements in a roadway image, replacing accident-prone (AP) features by using a diffusion model. After object-level segmentation, the AP features identified by the properties of accident hotspots are masked by a human operator and safe roadway elements are inpainted. With only an average time of 2 min for image inpainting, the likelihood of an image being classified as an accident hotspot drops by an average of 11.85%. In addition, safe urban spaces can be designed considering human factors of commuters such as gaze saliency. Considering this, we introduce saliency enhancement that suggests chrominance alteration for a safe road view.