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University of Washington

Data Visualization and Analytics to Support Accessible Pedestrian Planning and Decision-Making

Abstract

dc:description.abstract

Transportation planners cannot begin to address inaccessible pedestrian networks if they are not aware of the type and location of the network deficiencies. Unfortunately, planning tools that visualize these networks are not widely available and are only applicable to select jurisdictions. Therefore, we want to develop a flexible tool that can answer a diversity of planning questions and complete a range of PROW analyses all while incorporating accessibility considerations for people with mobility disabilities. We aim to improve our Walkshed Generator App tool by understanding what capacity-building tools we can provide urban and transportation planners to improve decision-making processes for accessibility projects and improvements to the PROW. To address this objective, we engaged active transportation planners via a pre-interview questionnaire that informed prototype visualizations developed with the Walkshed Generator App, and were subsequently demonstrated to the interviewees during a co-design interview. From these interviews, we developed 6 recommendations to guide the development of a useful and flexible planning tool to support the inclusion of accessibility in transportation planning.

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Vierstra, Rachel
Advisor dc:contributor.advisor
  • Vernez Moudon, Anne

Subjects

dc:subject × 9

Rights

dc:rights
Statement dc:rights
  • CC BY
Language dc:language.iso
en_US

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1773/50575
OAI identifier oai:identifier
oai:digital.lib.washington.edu:1773/50575

Chain of custody

source
Harvested from
University of Washington
Base URL
digital.lib.washington.edu/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Vierstra, Rachel. Data Visualization and Analytics to Support Accessible Pedestrian Planning and Decision-Making. 2023. http://hdl.handle.net/1773/50575