PREPRINT

Determining Accessible Sidewalk Width by Extracting Obstacle Information from Point Clouds

Cláudia Fonseca Pinhão, Chris Eijgenstein, Iva Gornishka, Shayla Jansen, Diederik M. Roijers, Daan Bloembergen

Submitted on 8 November 2022

Abstract

Obstacles on the sidewalk often block the path, limiting passage and resulting in frustration and wasted time, especially for citizens and visitors who use assistive devices (wheelchairs, walkers, strollers, canes, etc). To enable equal participation and use of the city, all citizens should be able to perform and complete their daily activities in a similar amount of time and effort. Therefore, we aim to offer accessibility information regarding sidewalks, so that citizens can better plan their routes, and to help city officials identify the location of bottlenecks and act on them. In this paper we propose a novel pipeline to estimate obstacle-free sidewalk widths based on 3D point cloud data of the city of Amsterdam, as the first step to offer a more complete set of information regarding sidewalk accessibility.

Preprint

Comment: 4 pages, 9 figures. Presented at the workshop on "The Future of Urban Accessibility" at ACM ASSETS'22. Code for this paper is available at https://github.com/Amsterdam-AI-Team/Urban_PointCloud_Sidewalk_Width

Subjects: Computer Science - Computer Vision and Pattern Recognition; I.4.6; I.4.8

URL: http://arxiv.org/abs/2211.04108