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.