Quantifying Compliance and Reliance Trust Behaviors to Influence Trust in Human- Automation Teams

摘要

Abstract. Automation is utilized heavily in many domains to increase productivity. With new, more complexrnautomation, like the self-driving car, humans will be required to forego direct task performance in favor ofrnmaintaining a supervisory role over automation systems. While the use of these systems generally results in greaterrnperformance than humans performing alone, humans are reluctant to adopt these superior systems due to a lack ofrntrust. The United States Department of Defense is investigating trust in automation in order to influence the rate ofrnadoption of automation technology. Studying trust in automation systems requires a mechanism for quantifying andrnmeasuring trust. This paper proposes a method for measuring human trust behaviors with regard to humanautomationrnsystems through response rates of compliance and reliance. Using behavioral data from a humansubjectsrnexperiment involving automated agents, we create a system dynamics model which relates trust to otherrnsystem level variables. Using this trust model, engineers will be able to study trust in human-automation teamrnscenarios in order to design automation systems with higher rates of adoption.