Modeling Accessibility-Constrained Networks with Time-Weighted Graphs

TL;DR

This paper presents a pipeline that models campus accessibility using time-weighted graphs and algorithms to identify optimal wheelchair-accessible paths, aiming to improve mobility for disabled individuals.

Contribution

It introduces a novel pipeline combining APIs and graph algorithms to analyze and enhance campus accessibility for the physically disabled.

Findings

Wheelchair users face significant mobility constraints due to lack of accessible routes.

The custom Least Resistance algorithm outperforms Dijkstra's in finding optimal paths.

Key nodes on campus affecting accessibility are identified through centrality measures.

Abstract

Accessibility for the physically disabled is a prevalent issue on university campuses, where stairs and steep slopes make navigating campus arduous. Our work proposes a pipeline to model a college campus as a network by combining Strava and other APIs with depth-first search to derive insights into wheelchair-accessible paths. We then develop a custom Least Resistance algorithm to compute optimal paths between selected nodes and benchmark it against Dijkstra's algorithm. We highlight crucial nodes on campus using centrality measures, demonstrating that wheelchair users are significantly constrained by the lack of mobility options and accommodations. Our pipeline is designed to support future expansion in scope and accuracy, while enabling the proposal of engineering solutions to improve campus accessibility for physically disabled individuals.