Augmented reality HMI for distracted drivers in a level 3 automation: Effects on takeover performance and safety

Abstract

With an increased level of automation, drivers can divert attention from the road environment and engage in non-driving-related tasks, thus reducing situation awareness, which could impact safety in cases of manual takeover requests. In this research, an augmented reality situation-adaptive human–machine interface (HMI) was simulated in a virtual environment. The HMI aimed to improve the quality of takeovers by boosting the reconstruction of situation awareness in distracted drivers following a takeover request in a Level 3 automated driving situation. To this end, the HMI displayed salient visual cues (bottom-up process) for important elements that drivers should pay attention to. Instructions from a user manual were also provided, detailing how to regain situation awareness by presenting the ideal takeover sequence (top-down process), which was necessary for the use of the HMI. For this purpose, an experiment was conducted using a medium-fidelity static driving simulator with a sample of 35 participants distributed according to three between-subjects conditions: “control – basic user manual without HMI,” “ideal takeover sequence focused user manual without HMI,” and “ideal takeover sequence focused user manual with HMI.” According to the results, the augmented reality HMI improved safety in takeovers involving lane changes in heavy traffic and emergency braking, with better traffic insertion and higher time to collision. Participants who only received the user manual dedicated to the ideal takeover sequence (top-down process) exhibited less visual exploration of the driving environment in the takeover situations, which could lead to safety issues. These results are discussed regarding existing literature and possible implementations of such an HMI in a simpler device, such as a head-up display, for provide wider application.