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1. Augmented reality head-up displays effect on drivers’ spatial knowledge acquisition

   https://doi.org/10.1177/1071181319631287  

   de Oliveira Faria, Nayara ; Kandil, Dina ; Gabbard, Joseph L. ( November 2019 , Proceedings of the Human Factors and Ergonomics Society Annual Meeting)

   Background: Drivers gather most of the information they need to drive by looking at the world around them and at visual displays within the vehicle. Navigation systems automate the way drivers navigate. In using these systems, drivers offload both tactical (route following) and strategic aspects (route planning) of navigational tasks to the automated SatNav system, freeing up cognitive and attentional resources that can be used in other tasks (Burnett, 2009). Despite the potential benefits and opportunities that navigation systems provide, their use can also be problematic. For example, research suggests that drivers using SatNav do not develop as much environmental spatial knowledge as drivers using paper maps (Waters & Winter, 2011; Parush, Ahuvia, & Erev, 2007). With recent growth and advances of augmented reality (AR) head-up displays (HUDs), there are new opportunities to display navigation information directly within a driver’s forward field of view, allowing them to gather information needed to navigate without looking away from the road. While the technology is promising, the nuances of interface design and its impacts on drivers must be further understood before AR can be widely and safely incorporated into vehicles. Specifically, an impact that warrants investigation is the role of AR HUDS in spatial knowledge acquisition while driving. Acquiring high levels of spatial knowledge is crucial for navigation tasks because individuals who have greater levels of spatial knowledge acquisition are more capable of navigating based on their own internal knowledge (Bolton, Burnett, & Large, 2015). Moreover, the ability to develop an accurate and comprehensive cognitive map acts as a social function in which individuals are able to navigate for others, provide verbal directions and sketch direction maps (Hill, 1987). Given these points, the relationship between spatial knowledge acquisition and novel technologies such as AR HUDs in driving is a relevant topic for investigation. Objectives: This work explored whether providing conformal AR navigational cues improves spatial knowledge acquisition (as compared to traditional HUD visual cues) to assess the plausibility and justification for investment in generating larger FOV AR HUDs with potentially multiple focal planes. Methods: This study employed a 2x2 between-subjects design in which twenty-four participants were counterbalanced by gender. We used a fixed base, medium fidelity driving simulator for where participants drove while navigating with one of two possible HUD interface designs: a world-relative arrow post sign and a screen-relative traditional arrow. During the 10-15 minute drive, participants drove the route and were encouraged to verbally share feedback as they proceeded. After the drive, participants completed a NASA-TLX questionnaire to record their perceived workload. We measured spatial knowledge at two levels: landmark and route knowledge. Landmark knowledge was assessed using an iconic recognition task, while route knowledge was assessed using a scene ordering task. After completion of the study, individuals signed a post-trial consent form and were compensated $10 for their time. Results: NASA-TLX performance subscale ratings revealed that participants felt that they performed better during the world-relative condition but at a higher rate of perceived workload. However, in terms of perceived workload, results suggest there is no significant difference between interface design conditions. Landmark knowledge results suggest that the mean number of remembered scenes among both conditions is statistically similar, indicating participants using both interface designs remembered the same proportion of on-route scenes. Deviance analysis show that only maneuver direction had an influence on landmark knowledge testing performance. Route knowledge results suggest that the proportion of scenes on-route which were correctly sequenced by participants is similar under both conditions. Finally, participants exhibited poorer performance in the route knowledge task as compared to landmark knowledge task (independent of HUD interface design). Conclusions: This study described a driving simulator study which evaluated the head-up provision of two types of AR navigation interface designs. The world-relative condition placed an artificial post sign at the corner of an approaching intersection containing a real landmark. The screen-relative condition displayed turn directions using a screen-fixed traditional arrow located directly ahead of the participant on the right or left side on the HUD. Overall results of this initial study provide evidence that the use of both screen-relative and world-relative AR head-up display interfaces have similar impact on spatial knowledge acquisition and perceived workload while driving. These results contrast a common perspective in the AR community that conformal, world-relative graphics are inherently more effective. This study instead suggests that simple, screen-fixed designs may indeed be effective in certain contexts. 

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2. The slow emergence of gaze‐ and point‐following: A longitudinal study of infants from 4 to 12 months

   https://doi.org/10.1111/desc.13457  

   Tang, Yueyan ; Gonzalez, Marybel Robledo ; Deák, Gedeon O. ( November 2023 , Developmental Science)

   Acquisition of visual attention‐following skills, notably gaze‐ and point‐following, contributes to infants' ability to share attention with caregivers, which in turn contributes to social learning and communication. However, the development of gaze‐ and point‐following in the first 18 months remains controversial, in part because of different testing protocols and standards. To address this, we longitudinally testedN = 43 low‐risk, North American middle‐class infants' tendency to follow gaze direction, pointing gestures, and gaze‐and‐point combinations. Infants were tested monthly from 4 to 12 months of age. To control motivational differences, infants were taught to expect contingent reward videos in the target locations. No‐cue trials were included to estimate spontaneous target fixation rates. A comparison sample (N = 23) was tested at 9 and 12 months to estimate practice effects. Results showed gradual increases in both gaze‐ and point‐following starting around 7 months, and modest month‐to‐month individual stability from 8 to 12 months. However, attention‐following did not exceed chance levels until after 6 months. Infants rarely followed cues to locations behind them, even at 12 months. Infants followed combined gaze‐and‐point cues more than gaze alone, and followed points at intermediate levels (not reliably different from the other cues). The comparison group's results showed that practice effects did not explain the age‐related increase in attention‐following. The results corroborate and extend previous findings that North American middle‐class infants' attention‐following in controlled laboratory settings increases slowly and incrementally between 6 and 12 months of age.

   A longitudinal experimental study documented the emergence and developmental trajectories of North American middle‐class infants' visual attention‐following skills, including gaze‐following, point‐following, and gaze‐and‐point‐following.

   A new paradigm controlled for factors including motivation, attentiveness, and visual‐search baserates. Motor development was ruled out as a predictor or limiter of the emergence of attention‐following.

   Infants did not follow attention reliably until after 6 months, and following increased slowly from 7 to 12 months.

   Infants' individual trajectories showed modest month‐to‐month stability from 8 to 12 months of age.

    

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3. Automatic ML-based vestibular gait classification: examining the effects of IMU placement and gait task selection

   https://doi.org/10.1186/s12984-022-01099-z  

   Jabri, Safa ; Carender, Wendy ; Wiens, Jenna ; Sienko, Kathleen H. ( December 2022 , Journal of NeuroEngineering and Rehabilitation)

   Vestibular deficits can impair an individual’s ability to maintain postural and/or gaze stability. Characterizing gait abnormalities among individuals affected by vestibular deficits could help identify patients at high risk of falling and inform rehabilitation programs. Commonly used gait assessment tools rely on simple measures such as timing and visual observations of path deviations by clinicians. These simple measures may not capture subtle changes in gait kinematics. Therefore, we investigated the use of wearable inertial measurement units (IMUs) and machine learning (ML) approaches to automatically discriminate between gait patterns of individuals with vestibular deficits and age-matched controls. The goal of this study was to examine the effects of IMU placement and gait task selection on the performance of automatic vestibular gait classifiers.

   Thirty study participants (15 with vestibular deficits and 15 age-matched controls) participated in a single-session gait study during which they performed seven gait tasks while donning a full-body set of IMUs. Classification performance was reported in terms of area under the receiver operating characteristic curve (AUROC) scores for Random Forest models trained on data from each IMU placement for each gait task.

   Several models were able to classify vestibular gait better than random (AUROC > 0.5), but their performance varied according to IMU placement and gait task selection. Results indicated that a single IMU placed on the left arm when walking with eyes closed resulted in the highest AUROC score for a single IMU (AUROC = 0.88 [0.84, 0.89]). Feature permutation results indicated that participants with vestibular deficits reduced their arm swing compared to age-matched controls while they walked with eyes closed.

   These findings highlighted differences in upper extremity kinematics during walking with eyes closed that were characteristic of vestibular deficits and showed evidence of the discriminative ability of IMU-based automated screening for vestibular deficits. Further research should explore the mechanisms driving arm swing differences in the vestibular population.

    

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4. Analysis of Driver Behavior in Mixed Autonomous and Non-autonomous Traffic Flows

   https://doi.org/10.1177/1071181322661305  

   Liu, Jundi ; Boyle, Linda Ng ( September 2022 , Proceedings of the Human Factors and Ergonomics Society Annual Meeting)

   Autonomous vehicles are expected to improve road safety and efficiency in future transportation systems. A driving simulator study was designed to identify driving styles and the cooperation between human drivers and other AVs. The study captured driver’s following behavior in a fully autonomous driving environment at unsignalized intersections. Participants were asked to make a series of maneuvers (straight through intersection, left turn, and right turn) in two different speed conditions (30, 40 mph) and two different traffic density conditions (with or without other traffic). Analysis of Variance showed that drivers had a significantly larger deviation (defined as the area between two trajectories) during left turn maneuvers when they were traveling at higher speeds. Moreover, the first turning operation had smaller deviation than the second turning operation. The findings have implications for the design of driver-assistance guidance systems in future mixed autonomous and non-autonomous traffic flows. 

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5. Post Take-Over Performance Varies in Drivers of Automated and Connected Vehicle Technology in Near-Miss Scenarios

   https://doi.org/10.1177/00187208231219184  

   Yamani, Yusuke ; Glassman, Jeffrey ; Alruwaili, Abdalziz ; Yahoodik, Sarah E. ; Davis, Emily ; Lugo, Samantha ; Xie, Kun ; Ishak, Sherif ( December 2023 , Human Factors: The Journal of the Human Factors and Ergonomics Society)

   This study examined the impact of monitoring instructions when using an automated driving system (ADS) and road obstructions on post take-over performance in near-miss scenarios.

   Past research indicates partial ADS reduces the driver’s situation awareness and degrades post take-over performance. Connected vehicle technology may alert drivers to impending hazards in time to safely avoid near-miss events.

   Forty-eight licensed drivers using ADS were randomly assigned to either the active driving or passive driving condition. Participants navigated eight scenarios with or without a visual obstruction in a distributed driving simulator. The experimenter drove the other simulated vehicle to manually cause near-miss events. Participants’ mean longitudinal velocity, standard deviation of longitudinal velocity, and mean longitudinal acceleration were measured.

   Participants in passive ADS group showed greater, and more variable, deceleration rates than those in the active ADS group. Despite a reliable audiovisual warning, participants failed to slow down in the red-light running scenario when the conflict vehicle was occluded. Participant’s trust in the automated driving system did not vary between the beginning and end of the experiment.

   Drivers interacting with ADS in a passive manner may continue to show increased and more variable deceleration rates in near-miss scenarios even with reliable connected vehicle technology. Future research may focus on interactive effects of automated and connected driving technologies on drivers’ ability to anticipate and safely navigate near-miss scenarios.

   Designers of automated and connected vehicle technologies may consider different timing and types of cues to inform the drivers of imminent hazard in high-risk scenarios for near-miss events.

    

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