Honorable Mention
People with vision impairments (VIP) are among the most vulnerable road users in traffic. Autonomous vehicles are believed to reduce accidents but still demand some form of external communication signaling relevant information to pedestrians. Recent research on the design of vehicle-pedestrian communication (VPC) focuses strongly on concepts for a non-disabled population. Our work presents an inclusive user-centered design for VPC, beneficial for both vision impaired and seeing pedestrians. We conducted a workshop with VIP (N=6), discussing current issues in road traffic and comparing communication concepts proposed by literature. A thematic analysis unveiled two important themes: number of communicating vehicles and content (affecting duration). Subsequently, we investigated these in a second user study in virtual reality (N=33, 8 VIP) comparing the VPC between groups of abilities. We found that trust and understanding is enhanced and cognitive load reduced when all relevant vehicles communicate; high content messages also reduce cognitive load.
https://doi.org/10.1145/3313831.3376472
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2020.acm.org/)