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In mixed traffic environments that involve conventional vehicles (CVs) andautonomous vehicles (AVs), it is crucial for CV drivers to maintain anappropriate level of situation awareness to ensure safe and efficientinteractions with AVs. This study investigates how AV communication throughhuman-machine interfaces (HMIs) affects CV drivers' situation awareness (SA) inmixed traffic environments, especially at intersections. Initially, we designedeight HMI concepts through a human-centered design process. The twohighest-rated concepts were selected for implementation as external andinternal HMIs (eHMIs and iHMIs). Subsequently, we designed a within-subjectsexperiment with three conditions, a control condition without any communicationHMI, and two treatment conditions utilizing eHMIs and iHMIs as communicationmeans. We investigated the effects of these conditions on 50 participantsacting as CV drivers in a virtual environment (VR) driving simulator.Self-reported assessments and eye-tracking measures were employed to evaluateparticipants' situation awareness, trust, acceptance, and mental workload.Results indicated that the iHMI condition resulted in superior SA amongparticipants and improved trust in AV compared to the control and eHMIconditions. Additionally, iHMI led to a comparatively lower increase in mentalworkload compared to the other two conditions. Our study contributes to thedevelopment of effective AV-CV communications and has the potential to informthe design of future AV systems.

Investigating HMIs to Foster Communications between Conventional Vehicles and Autonomous Vehicles in Intersections