01472429

Component

https://doi.org/10.3141/2393-02

http://scholar.google.com...Liao&publication_year=2013

People with vision impairment rely heavily on walking and public transit for their transportation needs. A major challenge for this population is crossing intersections safely. As a result of the Americans with Disabilities Act, accessible pedestrian signal systems at signalized intersections have improved significantly since 2000. However, these systems still have shortcomings for both users and municipalities, and new approaches are needed to serve pedestrians with low vision adequately. As part of the ongoing effort to develop a prototype mobile accessible pedestrian signals (MAPS) application for the blind and visually impaired, 10 blind and low-vision people were interviewed to understand better what types of information they use at intersection crossings and to identify the types of information that could assist them. With these survey results, a MAPS system was developed to provide signal and intersection geometry information to smartphone users at signalized intersections. User interaction was with simple tactile input (single or double tap) and text-to-speech technology. A field experiment at two signalized intersections was conducted with 18 visually impaired participants to validate the use and functioning of the MAPS system in a real-world application. The purpose was to identify whether the smartphone application could effectively provide geometry and signal timing information and thus provide decision support for visually impaired pedestrians. Objective and subjective measures were developed to evaluate the performance of visually impaired users of MAPS. Participants reported that the MAPS system provided helpful geometry information (82%) and helpful signal information (59%).

01518276

13-0231

English

pp 12–20

2013

Transportation Research Record: Journal of the Transportation Research Board

9780309287173

Print

Figures (5) ; References (33)

Audible pedestrian signals; Blind persons; Mobile telephones; Pedestrian movement; Pedestrian safety; Signalized intersections; Smartphones; Traffic signals; Visually impaired persons; Wayfinding

Mobile accessible pedestrian signals

Pedestrians and Bicyclists; Safety and Human Factors; Society; I83: Accidents and the Human Factor

PRP, TRIS, TRB, ATRI

Feb 5 2013 12:12PM

• Analysis of Pedestrian Performance in Shared-Space Environments
• Analysis of Pedestrian–Vehicle Traffic Conflicts in Street Designs with Elements of Shared Space
• Application of Computer Vision to Diagnosis of Pedestrian Safety Issues
• Considerations for Integrating Bicycling and Walking Facilities into Urban Infrastructure
• Development of Canadian National Pedestrian Crossing Control Guide
• Do All Roadway Users Want the Same Things? Results from Roadway Design Survey of San Francisco Bay Area Pedestrians, Drivers, Bicyclists, and Transit Users
• Do Complete Streets Cost More Than Incomplete Streets?
• Effect of Advance Yield Markings and Symbolic Signs on Vehicle–Pedestrian Conflicts: Field Evaluation
• Effect of Left-Turn Operational Mode on Pedestrian Safety: Development of Models and Guidelines
• Effectiveness of Audible and Tactile Heading Cues at Complex Intersections for Pedestrians Who Are Blind
• Effects of High-Visibility Enforcement on Driver Compliance with Pedestrian Yield Right-of-Way Laws
• Evaluation of Pedestrian Safety: Pedestrian Crash Hot Spots and Risk Factors for Injury Severity
• Feature Analysis and Operation Evaluation of Pedestrian Weaving Zone
• Improving Cyclist and Pedestrian Environment While Maintaining Vehicle Throughput: Before- and After-Construction Analysis
• Missing Links: How Social Paths Can Improve Pedestrian Accessibility to Light Rail
• Pedestrian Crash Risk on Boundary Roadways: University Campus Case Study
• Sight Distance for Disabled Pedestrians at Crossings: Methodology Comparison with Other Modes
• Study on Pedestrian Red-Time Crossing Behavior: Integrated Field Observation and Questionnaire Data
• Use of Spatiotemporal Parameters of Gait for Automated Classification of Pedestrian Gender and Age