Road Redesign Technique Achieving Enhanced Road Safety by Inpainting with a Diffusion Model

TL;DR

This paper presents a diffusion model-based image inpainting technique to enhance road safety by replacing accident-prone features with safer elements, enabling quick and effective roadway redesign.

Contribution

It introduces a novel inpainting method for roadway images that reduces accident hotspot likelihood and incorporates saliency enhancement for safer urban space design.

Findings

Average inpainting time is 2 minutes.

Accident hotspot classification likelihood decreases by 11.85%.

Saliency enhancement improves safe road view design.

Abstract

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.