Exploring the Impacts of Background Noise on Auditory Stimuli of Audio-Visual eHMIs for Hearing, Deaf, and Hard-of-Hearing People

TL;DR

The paper investigates how background noise interacts with auditory stimuli in audio-visual eHMIs for AV-pedestrian communication, focusing on Hearing and Deaf/Hard-of-Hearing (DHH) pedestrians. Using a VR-based crossing study with 36 participants (25 Hearing, 11 DHH), it employs a 2×3 within-subjects design varying Background Noise (Quiet vs Loud) and Auditory Stimuli (Baseline, Bell, Speech) to measure subjective experiences (trust, acceptance, perceived safety, mental workload) and objective behaviours (eye gaze, crossing timing). The key findings are that loud background noise degrades subjective crossing experiences, while adding auditory cues (Bell or Speech) improves subjective experience but does not robustly alter crossing behaviours; DHH participants’ experiences differ more, and audibility of cues varies with hearing technology. The work offers four practical implications for inclusive eHMI design and highlights the need for further research on accessibility, diverse disabled groups, and field validation to ensure safe, equitable AV-pedestrian interactions.

Abstract

External Human-Machine Interfaces (eHMIs) have been proposed to enhance communication between automated vehicles (AVs) and pedestrians, with growing interest in multi-modal designs such as audio-visual eHMIs. Just as poor lighting can impair visual cues, a loud background noise may mask the auditory stimuli. However, its effects within these systems have not been examined, and little is known about how pedestrians -- particularly Deaf and Hard-of-Hearing (DHH) people -- perceive different types of auditory stimuli. We conducted a virtual reality study (Hearing N=25, DHH N=11) to examine the effects of background noise (quiet and loud) on auditory stimuli (baseline, bell, speech) within an audio-visual eHMI. Results revealed that: (1) Crossing experiences of DHH pedestrians significantly differ from Hearing pedestrians. (2) Loud background noise adversely affects pedestrians' crossing experiences. (3) Providing an additional auditory eHMI (bell/speech) improves crossing experiences. We outlined four practical implications for future eHMI design and research.

Figures (7)

• Figure 1: Setup of the virtual simulation environment: The left figure shows a top-down view, while the right figure shows a leftward view. a) The starting position of the participant, which is 4.7 m from the road. b) The 2 m wide grey pavement area, which has a trigger to inform one of the AVs to yield for the participant. c) The 6.8 m wide two-lane road that the participant needed to cross. d) The waypoint (i.e., green surface with downward arrow indicated), which is 2.5 m away from the road. Please note that the human model of the player was only a visual aid to help understand the location; the human model was disabled in the environment, and participants do not have their own avatars.
• Figure 2: The appearance of the AV used in our study, where a human avatar sits in the driver's seat but does not engage with the vehicle. Active mode of i) the Light Strip and ii) the Display when the AV was fully stopped.
• Figure 3: Mean Trust ratings of audio stimuli types under Quiet vs. Loud background noise across a) Hearing participants and b) DHH participants. Data are shown with 95% confidence intervals.
• Figure 4: Mean Usefulness ratings of audio stimuli types under Quiet vs. Loud background noise across a) Hearing participants and b) DHH participants. Data are shown with 95% confidence intervals.
• Figure 5: Mean Satisfying ratings of audio stimuli types under Quiet vs. Loud background noise across a) Hearing participants and b) DHH participants. Data are shown with 95% confidence intervals.