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A Collaborative System for Suitable Wheelchair Route Planning

Published:28 August 2018Publication History
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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.

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          cover image ACM Transactions on Accessible Computing
          ACM Transactions on Accessible Computing  Volume 11, Issue 3
          Special Issue on Fabrication Technologies and Do-It-Yourself Accessibility and Regular Papers
          September 2018
          156 pages
          ISSN:1936-7228
          EISSN:1936-7236
          DOI:10.1145/3271479
          Issue’s Table of Contents

          Copyright © 2018 ACM

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          Publication History

          • Published: 28 August 2018
          • Accepted: 1 July 2018
          • Revised: 1 June 2018
          • Received: 1 December 2016
          Published in taccess Volume 11, Issue 3

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