A Collaborative System for Suitable Wheelchair Route Planning

Author:

Barczyszyn Guilherme L.1ORCID,Camenar Letícia M. De O.1ORCID,Nascimento Diego De F. Do1ORCID,Kozievitch Nádia P.1ORCID,Silva Ricardo D. Da1ORCID,Almeida Leonelo D. A.1ORCID,Santi Juliana De1ORCID,Minetto Rodrigo1ORCID

Affiliation:

1. Federal University of Technology-Paraná (UTFPR), Brazil

Abstract

Route planning is a challenging problem for urban computing that usually involves the processing of a huge amount of data and collaborative user feedback. Traditionally, route planning services are street-based, that is, even paths for a pedestrian are suggested in terms of streets. However, such models are not suitable for users with certain disabilities. To address this problem, we have performed a requirement analysis with a group of wheelchair-users and their companions to understand their urban mobility experience. Given that perspective, we describe in this article a sidewalk-based model to accommodate the needs for a wheelchair route planning service. The model is mathematically defined as a graph, where the vertices are the city block corners and the edges are the sidewalks or crosswalks. The edge costs are derived from important accessibility features, such as distance, path inclination, and existence and maintenance conditions of curb ramps, crosswalks, and sidewalks. The model has been designed so that user feedback is considered to help updating the model when accessibility issues are detected, by wheelchair-users and companions, or solved, by the department of city planning. We also present a route planning algorithm that provides a set of alternative routes based on accessibility conditions, and a shortcut recommender algorithm to support accessibility-related decision making by the department of city planning. Experiments, by using PgRouting and PostGIS with open data, are reported for a Brazilian city neighborhood to validate the model and the route planning service.

Funder

EU-BR EUBra-BigSea project

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Science Applications,Human-Computer Interaction

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Estimating the Bitumen Ratio to be Used in Highway Asphalt Concrete by Machine Learning;The Baltic Journal of Road and Bridge Engineering;2024-06-28

2. Exploring Information Needs for Tracking to Support Using Wheelchairs in Everyday Life;Extended Abstracts of the CHI Conference on Human Factors in Computing Systems;2024-05-11

3. A Systematic Review of Ability-diverse Collaboration through Ability-based Lens in HCI;Proceedings of the CHI Conference on Human Factors in Computing Systems;2024-05-11

4. Influence of the built environment on community mobility of people living with visual disabilities: a scoping review;Urban, Planning and Transport Research;2024-01-02

5. Inaccessibility maps to support sighted people using visually impaired people’s white cane data;Technology and Disability;2023-12-27

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3