2017/07/10 by Lex Fridman, Fridman, Lex, Bruce Mehler +10 · 3 citations
Computer Science · Engineering · Psychology · #FOS: Computer and information sciences #Human-Automation Interaction and Safety #Human-Computer Interaction (cs.HC) #Safety Warnings and Signage #Traffic and Road Safety #cs.HC
paper · pdf · doi:10.48550/arxiv.1707.02698
arxiv created 2017/07/10 · openalex publication_date 2017/07/10 · arxiv updated 2017/07/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Researchers, technology reviewers, and governmental agencies have expressed concern that automation may necessitate the introduction of added displays to indicate vehicle intent in vehicle-to-pedestrian interactions. An automated online methodology for obtaining communication intent perceptions for 30 external vehicle-to-pedestrian display concepts was implemented and tested using Amazon Mechanic Turk. Data from 200 qualified participants was quickly obtained and processed. In addition to producing a useful early-stage evaluation of these specific design concepts, the test demonstrated that the methodology is scalable so that a large number of design elements or minor variations can be assessed through a series of runs even on much larger samples in a matter of hours. Using this approach, designers should be able to refine concepts both more quickly and in more depth than available development resources typically allow. Some concerns and questions about common assumptions related to the implementation of vehicle-to-pedestrian displays are posed.