Interactions Between Human-Driven and Autonomous Vehicles on Public Roads

Abstract

To achieve the level of safety and efficiencies promised by autonomous vehicles (AVs), understanding of interactions between human driven vehicles and AVs is crucial. The limited access to publicly available AV data in the field has been the main source of challenge to explore these questions. Using recently released annotated AV data released by Waymo, we investigate interactions between AVs with Human-driven manual vehicles (MVs) in a public road environment. A scalable methodology is presented to study interactions between AVs and MVs. This research reports two main findings (a) AVs tend to be more conservative than MVs at higher speeds on arterials and at lower speeds on freeways (b) No statistical differences in the mean reaction times between MVs and AVs, however, MVs following MVs were found to have statistically significantly lower variance in reaction times. These findings demonstrate the broader impacts of AVs on traffic flow and capacity.