VisionWay Accessibility

VisionWay: Accessibility-Aware Path Selection for Wayfinding

The challenge of outdoor wayfinding, critical for People with Visual Impairments (PVI), consists in helping users safely walk to a pre-determined nearby destination. The main focus of existing solutions from research and industry is to leverage the user's smartphone to receive safe moving directions either from a remote operator or smart app. However, multiple paths may exist to connect users with their destination, each one with unique characteristics in terms of accessibility and safety. Unfortunately, little to no attention has been paid in helping PVI decide, before even starting to walk, which path to take based on their accessibility. Thus, a barrier identified is that the followed path may not be accessible because sidewalk features such as potholes, uncontrolled crossing, interrupted sidewalks, and objects are not known in advance. The investigators' goal is to develop a mobile live, local, outside map framework called VisionWay, customized for PVI-user as a wayfinding tool to analyze, before starting to walk, the accessibility of candidate paths and choose one to the destination.

Study Overview

• Status: Recruiting
• Conditions: Persons With Visual Disabilities
• Intervention / Treatment: Behavioral: walking path

Detailed Description

Existing solutions include cognitive maps which can help PVI confidently walk in known locations but need to be built on experience, and thus cannot be used to determine the best path towards an unfamiliar location. In fact, previous research has found that PVI, to reduce stress and increase safety, before embarking on a new journey need to be informed about whether a specific path has a paved sidewalk, street crossing point, controlled or uncontrolled crosswalk, stairs, obstacles, and potholes. Knowing these characteristics ahead of time, i.e., before starting to walk, can help PVI make choices on which path to take, which is particularly beneficial in unfamiliar environments. Trained Orientation and Mobility (O&M) specialists often provide high-quality in-person help for PVI to walk in unfamiliar areas, notifying them of upcoming obstacles and turns on the path. However, a shortage of qualified specialists has increased the demand for remote instructors by leveraging smartphones as pointing devices. For example, services such as TappyGuide and WeAssist work by sharing the PVI's destination as well as smartphone camera and GPS data with a remote human operator, who can then consult a map to voice-guide the PVI to their destination. On the other hand, the remote directions depend on the availability of the remote operators. To alleviate this dependency, new technologies leverage mobile computing and Artificial Intelligence (AI) to sense the environment for obstacles and provide real-time navigation directions through audio or haptic feedback. For example, WeWalk's smart cane provides basic sensing and smart features to support navigation and obstacle detection alert; as part of USDOT's Inclusive Design Challenge, MPI Giudice, MPI Doore, and Co-I Fink developed the Autonomous Vehicle Assistant (AVA) app, which helps PVI safely walk towards an autonomous vehicle and accurately reach its door handle. Some recent projects target indoor localization and navigation or leverage augmented reality and haptic feedback to aid obstacle avoidance during navigation and reduce veering. While most funded projects focus on providing real-time navigation guidance given a certain path to follow, the reality is that more than one path may exist to reach a certain destination, especially in an outdoor context. Thus, they cannot help PVI and remote operators choose the best path to follow, which requires creating accessibility maps. The problem of creating accessibility maps has been widely studied for people in wheelchairs, whose main challenge is to ensure availability of accessible entrances or curbs on the path. WheelMap is an example of such a tool, but it does not help PVI, whose definition of accessible path can be quite different. For example, a wheelchair user may find it less problematic to handle an uncontrolled zebra crossing than someone with profound or total vision impairment. The most related solution focusing on finding accessible paths for PVI is that of Cohen and Dalyot, which leverages accessibility information already available in OpenStreetMap to evaluate the accessibility of different paths for totally blind users. However, it has three limitations. First, OpenStreetMap, similar to Google Maps and Apple's Maps, does not provide important information about many harmful and beneficial sidewalk features affecting accessibility such as tactile tech, potholes, tree branches, or sidewalk restrictions. Second, it remains unclear how to describe each path's features to PVI for selection. Third, it only focuses on blind pedestrians while the definition of accessibility and the features affect it can vary widely across severe, profound, and totally blind PVI.The goal of this project is to involve PVI with different impairment severity and mobility aids in the development of VisionWay, a mobile/cloud framework that helps PVI select a pedestrian path towards their destination based on three main innovations. This study focuses on the first of these by utilizing a user study designed to reveal how various sidewalk features affect accessibility and how to design an accessibility model able to estimate it. To address this challenge, barrier, and achieve our goal, the investigators assembled a team of men, women, trainees, and members who have lived experience with vision impairment (VI). Our strengths include engineering, computer science, human factor engineering, mixed methods research, human-computer interaction for PVI, clinicians including low vision and orientation and mobility specialists (OMS), as well as team members and participants with VI. The investigators' goal is to develop a mobile live, local, outside map framework called VisionWay, customized for PVI-user as a wayfinding tool to analyze, before starting to walk, the accessibility of candidate paths and choose one to the destination. The investigators designed aims for R61 technology development and feasibility. (Aim 1) Collect survey data and observations in pilot pathways to define and validate a PVI-facing metric to measure and detect the accessibility of a walk path from static and dynamic imagery.

• Study Type: Interventional
• Enrollment (Estimated): 100
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Abigail Larsen, MPH; Phone Number: 614-293-5287; Email: abigail.larsen@osumc.edu
• Study Contact Backup: Name: Matt Patton; Phone Number: 614-293-5287; Email: matthew.patton@osumc.edu

Study Locations

• United States
  • Maine
    • Orono, Maine, United States, 04469
      • Recruiting
      • University of Maine
      • Contact: Nicholas Giudice, PhD; Phone Number: 207.581.2151; Email: Nicholas.giudice@maine.edu
      • Contact: Justin Brown; Phone Number: 207.581.2151; Email: justin.r.brown@osumc.edu
  • Ohio
    • Columbus, Ohio, United States, 43212
      • Recruiting
      • Ohio State University
      • Contact: Abigail Larsen, MPH; Phone Number: 614-406-4423; Email: abigail.larsen@osumc.edu
      • Contact: Matthew Patton; Phone Number: 614-293-5287; Email: matthew.patton@osumc.edu
      • Principal Investigator: Sayoko Moroi, MD, PhD

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• At least 18 years old
• Able to provide informed consent
• Vision worse than 20/200, encompassing PVI with severe and profound impairment as well as total blindness.

Group 1 Inclusion:

- PVI meeting general inclusion criteria and without mobility aids

Group 2 Inclusion:

- PVI meeting general inclusion criteria and who use a cane as a mobility aid

Group 3 Inclusion:

- PVI meeting general inclusion criteria and who use guide dogs.

Exclusion Criteria:

• Conditions that prevent safe ambulation that include, but are not limited to, neuromuscular disorder, post-operative state (such as orthopedic surgeries or cardiac surgeries), balance issues, history of falls in the last 6 months, or at the discretion of the investigator.
• Use of walker or wheelchair

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Other
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm

Intervention / Treatment

Experimental: Recorded walks; The study team will record videos of a subset of users walking on selected paths on campus. Participants may be presented with the maps ahead of the walk. Such videos may include video recordings from the perspective of the study team monitoring the participant. Additionally, personal recording devices such as GoPro/action cameras, or recording eyeglasses may be provided to the participant to record walks from their perspective. From the preselected paths, the set and order will be randomized between participants. The study team will prompt participants after each path to identify and describe path features that affect accessibility, as well as to provide a perceived accessibility score (on a scale of 1 to 5, where 5 is highly accessible). The video recording may include audio description of these relevant sidewalk features and the score. The research team member will record their observations of the walking paths as well.

Behavioral: walking path; Participants will be asked to walk a defined pathway through campus. From the preselected paths, the set and order will be randomized between participants.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
PVI accessibility on sidewalks	Primary objectives are to collect prospective data in PVI groups to define which sidewalk features affect accessibility and how to design an accessibility model able to estimate accessibility. Twenty sidewalk (path) features were scored on a 5-point Likert scale (1 = not important, 5 = very important), and participants indicated the number of additional minutes they would be willing to walk to access a route containing each feature (5-point scale. 1 = up to one minute, to 5 = five or more minutes). A combined score for each feature was determined by summing the two values (for each feature) to generate an overall priority ranking. Higher scores indicate a greater perceived importance.	For a period over 2 hours

Collaborators and Investigators

• Sponsor: Ohio State University
• Collaborators: University of Maine
• Investigators: Study Director: Marco Brocanelli, PhD, Ohio State University; Principal Investigator: Sayoko Moroi, MD, PhD, Ohio State University

Study record dates

Study Major Dates

• Study Start (Actual): February 26, 2026
• Primary Completion (Estimated): September 1, 2027
• Study Completion (Estimated): September 1, 2027

Study Registration Dates

• First Submitted: July 9, 2026
• First Submitted That Met QC Criteria: July 14, 2026
• First Posted (Actual): July 20, 2026

Study Record Updates

• Last Update Posted (Actual): July 20, 2026
• Last Update Submitted That Met QC Criteria: July 14, 2026
• Last Verified: July 1, 2026

More Information

Terms related to this study

• Other Study ID Numbers: STUDY20251838

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No