Lessons in Cooperation: Driver Sentiments Toward Real-Time Advisory Systems

Real-time advisory systems (RTASs) are a crucial milestone on the road toward fully autonomous driving. Current proof-of-concept RTASs, which observe drivers and their environment to provide advice, are effective in addressing fundamental traffic issues (e.g., congestion mitigation). However, interactions between these advisors and drivers have not yet been studied. In this article, we present insights from the first user study to explore drivers' interactions with these progressive systems. We query the reactions of 16 drivers to congestion mitigation advisors (CMAs) in a driving simulator. We discuss drivers' sentiments toward CMAs exhibiting diverse behaviors and their preferences for various aspects of the interactions such as the advice provided and the user interface. The effects of the behaviors on driver trust and adaption are also explored. We present recommendations to inform the design of cooperative advisory systems that will be ubiquitous as vehicle technology moves toward full automation.