  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.
