Autonomous vehicle technology increasingly allows drivers to turn their primary attention to secondary tasks (e.g., eating or working). This dramatic behavior change thus requires new input modalities to support driver–vehicle interaction, which must match the driver’s in-vehicle activities and the interaction situation. Prior studies that addressed this question did not consider how acceptance for inputs was affected by the physical and cognitive levels experienced by drivers engaged in Non-driving Related Tasks (NDRTs) or how their acceptance varies according to the interaction situation. This study investigates naturalistic interactions with a fully autonomous vehicle system in different intervention scenarios while drivers perform NDRTs. We presented an online methodology to 360 participants showing four NDRTs with different physical and cognitive engagement levels, and tested the six most common intervention scenarios (24 cases). Participants evaluated our proposed seven natural input interactions for each case: touch, voice, hand gesture, and their combinations. Results show that NDRTs influence the driver’s input interaction more than intervention scenario categories. In contrast, variation of physical load has more influence on input selection than variation of cognitive load. We also present a decision-making model of driver preferences to determine the most natural inputs and help User Experience designers better meet drivers’ needs.

Virtual reality (VR) locomotion should allow users to move freely in the virtual space while staying within the tracking area in the real space. The redirected walking (RDW) technique enables users to walk naturally in an unlimited virtual space within a limited tracking area by rotating the virtual scene view. However, conflicting visual and vestibular signals during RDW can lead to user discomfort and decreased immersion. To avoid user discomfort, an RDW gain should be within the detection threshold (DT) range. However, a large angle of walking redirection is required when physically avoiding obstacles or escaping from a narrow space, so DT expansion is necessary. In this study, to change the curvature DT range and enhance RDW performance, we proposed an optical flow (OF)-generating vection in a virtual environment. Further, we investigate methods to reduce user discomfort and increase RDW efficiency considering familiar and unfamiliar VR users. The findings showed that the introduction of OF led to a reduction in the DT range for all users, irrespective of the OF’s direction. However, conditions with OF resulted in an extended DT range for users familiar with VR while concurrently diminishing the DT range for those who were VR unfamiliar. To delve further, our analysis indicated that when both the OF and redirecting directions were identical, the RDW performance was robust to VR familiarity, whereas in opposing directions, the DT range increased for VR-familiar users. Our study findings suggested using OF for the RDW technique and extending its applicability in virtual environments.

Autonomous vehicles (AV) increasingly allow drivers to engage in secondary tasks such as eating or working on a laptop and thus require easy and reliable interaction inputs to facilitate communication between the driver and the vehicle. However, drivers report feeling less in control when driving is no longer the primary task, which suggests that novel approaches for assessing satisfaction regarding AV decision-making are needed. Therefore, we propose an immediate experience sampling method (IESM) that learns driver preferences for AV actions. We also suggest gaze-head input (G-HI) as a novel input in an AV. G-HI provides a hands-free, remote, and intuitive input modality that allows drivers to interact with the AV while continuing to engage in non-driving related tasks. We compare G-HI with voice and touch inputs via IESM for two simulated driving scenarios. Our results report the differences among the three inputs in terms of system usability, reaction time, and perceived workload. It also reveals that G-HI is a promising candidate for AV input interaction, which could replace voice or touch inputs where those inputs could not be utilized. Variation in driver satisfaction and expectations for AV actions confirms the effectiveness of using IESM to increase drivers’ sense of control.

A major challenge in virtual reality (VR) is enabling users to navigate expansive virtual environments within confined real-world spaces. Although redirected walking (RDW) addresses this by manipulating users’ walking paths, it is hindered by visual-vestibular inconsistencies, leading to reduced immersion, discomfort, and constrained detection thresholds (DTs). We introduce ReD Shoes, redirecting shoes for VR locomotion with dynamically adjustable inclination designed to enhance multisensory integration by providing haptic feedback directly to the feet. This feedback mitigates visual-vestibular inconsistencies by enhancing proprioceptive cues and aligning tactile sensations with visual stimuli, thereby improving self-motion perception, presence, and gait stability. We conducted two experiments with 30 participants: 10 in a pilot study to optimize inclination parameters and 20 in a main study to evaluate the DT, gait stability, and user experience under No Inclination, Low Inclination (1 cm), and High Inclination (1.5 cm) conditions. Low Inclination considerably expanded the DT (43.64%), enhanced the user’s feel of presence, and maintained walking stability through effective multisensory alignment. In comparison, High Inclination showed a smaller DT expansion (33.86%), increased discomfort, reduced stability, and aggravated oculomotor symptoms due to intensified sensory conflicts. This study demonstrates the use of ReD Shoes in addressing key RDW limitations by enhancing DT, stability, and user presence through active haptic feedback. Our findings offer insights for developing advanced VR mobility solutions, supporting adaptive haptic footwear that improves RDW functionality and extends immersive VR applications in gaming, training, and rehabilitation.