Quantifying accuracy on distance estimation tasks: A Monte Carlo study.

An important aspect of perceptual learning involves understanding how well individuals can perceive distances, sizes, and time-to-contact. Oftentimes, the primary goal in these experiments is to assess participants' errors (i.e., how accurately participants perform these tasks). However, the manner in which researchers have quantified error, or task accuracy, has varied. The use of different measures of task accuracy, to include error scores, ratios, and raw estimates, indicates that the interpretation of findings depends on the measure of task accuracy utilized. In an effort to better understand this issue, we used a Monte Carlo simulation to evaluate five dependent measures of accuracy: raw distance judgments, a ratio of true to estimated distance judgments, relative error, signed error, and absolute error. We simulated data consistent with prior findings in the distance perception literature and evaluated how findings and interpretations vary as a function of the measure of accuracy used. We found there to be differences in both statistical findings (e.g., overall model fit, mean square error, Type I error rate) and the interpretations of those findings. The costs and benefits of utilizing each accuracy measure for quantifying accuracy in distance estimation studies are discussed.

Can I Squeeze Through? Effects of Self-Avatars and Calibration in a Person-Plus-Virtual-Object System on Perceived Lateral Passability in VR.

With the popularity of Virtual Reality (VR) on the rise, creators from a variety of fields are building increasingly complex experiences that allow users to express themselves more naturally. Self-avatars and object interaction in virtual worlds are at the heart of these experiences. However, these give rise to several perception based challenges that have been the focus of research in recent years. One area that garners most interest is understanding the effects of self-avatars and object interaction on action capabilities or affordances in VR. Affordances have been shown to be influenced by the anthropometric and anthropomorphic properties of the self-avatar embodied. However, self-avatars cannot fully represent real world interaction and fail to provide information about the dynamic properties of surfaces in the environment. For example, pressing against a board to feel its rigidity. This lack of accurate dynamic information can be further amplified when interacting with virtual handheld objects as the weight and inertial feedback associated with them is often mismatched. To investigate this phenomenon, we looked at how the absence of dynamic surface properties affect lateral passability judgments when carrying virtual handheld objects in the presence or absence of gender matched body-scaled self-avatars. Results suggest that participants can calibrate to the missing dynamic information in the presence of self-avatars to make lateral passability judgments, but rely on their internal body schema of a compressed physical body depth in the absence of self-avatars.

Did I Hit the Door? Effects of Self-Avatars and Calibration in a Person-Plus-Virtual-Object System on Perceived Frontal Passability in VR.

The availability of new and improved display, tracking and input devices for Virtual Reality experiences has facilitated the use of partial and full body self-avatars in interaction with virtual objects in the environment. However, scaling the avatar to match the user's body dimensions remains to be a cumbersome process. Moreover, the effect of body-scaled self-avatars on size perception of virtual handheld objects and related action capabilities has been relatively unexplored. To this end, we present an empirical evaluation investigating the effect of the presence or absence of body-scaled self-avatars and visuo-motor calibration on frontal passability affordance judgments when interacting with virtual handheld objects. The self-avatar's dimensions were scaled to match the participant's eyeheight, arms length, shoulder width and body depth along the mid section. The results indicate that the presence of body-scaled self-avatars produce more realistic judgments of passability and aid the calibration process when interacting with virtual objects. Also, participants rely on the visual size of virtual objects to make judgments even though the kinesthetic and proprioceptive feedback of the object is missing or mismatched.

The effects of testing environment, experimental design, and ankle loading on calibration to perturbed optic flow during locomotion.

Calibration is the process by which the execution of actions becomes scaled to the (changing) relationship between environmental features and the actor's action capabilities. Though much research has investigated how individuals calibrate to perturbed optic flow, it remains unclear how different experimental factors contribute to the magnitude of calibration transfer. In the present study, we assessed how testing environment (Experiment 1), an adapted pretest-calibration-posttest design (Experiment 2), and bilateral ankle loading (Experiment 3) affected the magnitude of calibration to perturbed optic flow. We found that calibration transferred analogously to real-world and virtual environments. Although the magnitude of calibration transfer found here was greater than that reported by previous researchers, it was evident that calibration occurred rapidly and quickly plateaued, further supporting the claim that calibration is often incomplete despite continued calibration trials. We also saw an asymmetry in calibration magnitude, which may be due to a lack of appropriate perceptual-motor scaling prior to calibration. The implications of these findings for the assessment of distance perception and calibration in real-world and virtual environments are discussed.

Time-to-arrival estimations to simulated pedestrians.

Driving a vehicle requires individuals' awareness of their surroundings to prevent collisions with other vehicles, objects, and pedestrians. While previous research has investigated time-to-arrival (TTA) in real-world and simulated driving situations, there is little information on how pedestrian reflectance and time of day impact TTA. The present study investigated how vehicle velocity, viewing time, pedestrian reflectance, and time of day affected individuals' estimates of TTA. We used recorded driver-perspective footage of a vehicle approaching simulated pedestrians at different velocities during daytime and nighttime. We found that TTA was consistently underestimated, with the most accurate TTA estimates occurring at the lowest vehicle velocity. We also found TTA accuracy was better during daytime conditions. Pedestrian reflectance did not produce a significant main effect, but it did interact significantly with both velocity and time of day. These results suggest that multiple variables are responsible for TTA estimation. A better understanding of what factors may affect TTA estimates helps both researchers who investigate the phenomenon and laypersons who strive for safe driving practices.