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Sound Transit

Eye-Tracking: At-Grade Crossing Safety

Sound Transit has been investigating system-wide strategies to enhance the safety of at-grade crossings, which are any location where a road or pedestrian pathway crosses the rail tracks. This student team worked closely with Sound Transit to thoroughly evaluate existing design and placement of Link light rail signage in the Rainier Valley Corridor and applied innovative research methodologies (e.g., eye-tracking) to understand passenger/pedestrian behavior. Students also worked to draw upon secondary research from peer agencies and best practices to build an understanding of industry best practices of at-grade crossings. Students worked to build the domain specific knowledge and to utilize UX and Human Factors research and design principles to brainstorm, prototype, and validate a solution to enhance safety at at-grade crossings. The designed solution this student team worked to consider included the following requirements: - Built on an understanding of real-world users needs and challenges - Comprehensible to people from different cultural backgrounds and with different levels of English proficiency - Works for users with different mobility impairments and physical disabilities - Closely follows human factors and user-centered design principles to design the best experience The deliverables this student team worked to achieve include: - Research documentation, summaries, actionable insights, and recommendations - Secondary research: Heuristic evaluation of MUTCD standards and the current state of at-grade crossing features; review of industry best practices, peer agencies, and related literature; UX and human factors evaluation - Primary research: Qualitative studies, building persona and journey map, and conducting eye-tracking research at at-grade crossings - Design enhancement ideas, validation research report, and final presentation - Prototyping: Design and prototype enhancement ideas - Design validation: User testing (including eye-tracking studies), iteration, and recommend a final design

Faculty Adviser

Daniela Rosner, Associate Professor, Human Centered Design & Engineering

Students

Josh Strohschein
Rohini Mohandoss
Sushmidha Jawahar
Swati Sachdeva