Visible to the public Hitting the Road: Exploring Human-Robot Trust for Self-Driving Vehicles

TitleHitting the Road: Exploring Human-Robot Trust for Self-Driving Vehicles
Publication TypeConference Paper
Year of Publication2020
AuthorsRazin, Y. S., Feigh, K. M.
Conference Name2020 IEEE International Conference on Human-Machine Systems (ICHMS)
Date PublishedSeptember 2020
ISBN Number978-1-7281-5871-6
Keywordsautomated vehicles, Automation, automobiles, Autonomous automobiles, Autonomous vehicles, cars, driving domain, expanded model, exploratory factor analysis, exploring human-robot trust, Fires, general trust theory support, Human Behavior, human computer interaction, human factors, human-automation interaction, human-robot interaction, human-robot interaction trust, intelligent transportation systems, mobile robots, pubcrawl, resilience, Resiliency, road, road safety, road vehicles, Roads, Robot Trust, Safety, self-driving vehicles, simulated driving, Standards, Traffic flow, trust scale, trust scale validation, vehicular safety

With self-driving cars making their way on to our roads, we ask not what it would take for them to gain acceptance among consumers, but what impact they may have on other drivers. How they will be perceived and whether they will be trusted will likely have a major effect on traffic flow and vehicular safety. This work first undertakes an exploratory factor analysis to validate a trust scale for human-robot interaction and shows how previously validated metrics and general trust theory support a more complete model of trust that has increased applicability in the driving domain. We experimentally test this expanded model in the context of human-automation interaction during simulated driving, revealing how using these dimensions uncovers significant biases within human-robot trust that may have particularly deleterious effects when it comes to sharing our future roads with automated vehicles.

Citation Keyrazin_hitting_2020