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The number of automated features in surface vehicles is increasing as new vehicles are released each year. Some features allow drivers to temporarily take their attention off the road to engage in other tasks. However, sometimes it is important for drivers to immediately take control of the vehicle. To take control safely, drivers must understand what is required of them and have the situation awareness (SA) to understand important changes or factors within the environment around them. To achieve this, drivers may be presented with necessary takeover information using a head-up display (HUD), which keeps the driver’s eyes on the road. This study investigated the impact of novel HUDs on driver SA during takeover on highways. Data collection included empirical data for takeover performance metrics, self-reported SA, and participant preferences. To investigate differences between conditions, statistical analyses utilized repeated measure analyses of variance (ANOVAs). The results indicated that HUDs can increase aspects of takeover performance on highways, with participants demonstrating lower response times and higher time-to-collision metrics. There was no significant impact of HUDs on driver SA. Results of this work identified potential use cases and design criteria for new designs of novel HUDs to deliver important information during takeover.

The 2nd International Workshop on the eXtended Reality for Industrial and Occupational Supports (XRIOS) aims to identify the current state of XR research and the gaps in the scope of human factors and ergonomics, mainly related to industrial and occupational tasks, and discuss potential future research directions. XRIOS was held for the first time at IEEE VR 2022, where it served as the first venue to build an interdisciplinary research community that bridges XR developers/practitioners and human factors and ergonomics researchers interested in industrial and occupational XR applications. XRIOS 2023 follows the success of XRIOS 2022 in response to society's growing needs by expanding the XRIOS community and providing more opportunities.

Hyungil Kim,1 Younghoon Jung,2 Mikio Inamura3 1Gyeongju St. Mary’s Eye Clinic, Gyeongju, Republic of Korea; 2Department of Ophthalmology, Pohang Naval Hospital, Pohang, Republic of Korea; 3Inamura Eye Clinic, Yokohama, JapanCorrespondence: Mikio Inamura, Inamura Eye Clinic, 5-125 Isesakicho, Naka-ku, Yokohama, Kanagawa, 231-0045, Japan, Email m-ina@sa2.so-net.ne.jpPurpose: To introduce an alternative prechop technique without or with the use of a modified universal chopper (AE-2591, HI Kim chopper, ASICO, Inc. USA).Methods: Patients who underwent cataract surgery using the phaco-chop technique and the modified prechop technique have been grouped and reviewed retrospectively. Endothelial cell count (ECC) and central corneal thickness (CCT) measured 7 days pre-operatively, and 1 month and 3 months post-operatively, were compared between the two groups. In modified prechop technique, a narrow 1.7 mm neck prechopper (AE-4298, HI Kim-Inamura chopper, ASICO, Inc., USA) was used with universal chopper (AE-2591, HI Kim chopper, ASICO, Inc., USA) as an additional device for grade 4 and above cataracts or without it for grade 2 to 3 cataracts. Details of the surgical technique is further described in the Method section.Results: A total of 104 eyes in the modified prechop group and 97 eyes in the phaco-chop group were enrolled in the study. Pre-operative nuclear opacity, ECC, and CCT as well as post-operative ECC (absolute value and the loss) and CCT (absolute value and the change) throughout the follow-up between the two groups did not show statistically significant differences.Conclusion: Counter prechop technique using the modified prechopper and universal chopper is a safe, easy, and versatile surgical technique that can be applied broadly in a wide range of cases with various complexities, including LOCS lll N1 to N6 nuclei, hypermature cataracts, small pupils, and fragile suspensory zonular ligaments, with post-operative result not inferior to that of the conve

Hyungil Kim,1 Sohee Jeon2 1Gyeongju St. Mary’s Eye Clinic, Gyeongju-si, Gyeongsangbuk-do, Republic of Korea; 2Keye Eye Center, Seoul, Republic of KoreaCorrespondence: Sohee JeonKeye Eye Center, 326 Teheran-ro, Gangnam-gu, Seoul, KoreaTel +82-02-6207-1236Fax +82-02-6207-1246Email soheeeee@gmail.comPurpose: To evaluate refractive outcomes after retropupillary iris-claw intraocular lens (IOL) implantation and to compare postoperative astigmatism from (1) a conventional 5.5-mm sclerocorneal incision, (2) an L-shaped scleral tunnel incision, and (3) a frown scleral tunnel incision.Methods: This was a retrospective study of eyes undergoing dislocated IOL exchange for a retropupillary iris-claw IOL. Uncorrected and corrected distance visual acuity (UDVA and CDVA) and postoperative complications were evaluated until postoperative months 24. The refractive outcomes and the surgically induced astigmatism (SIA) vector were compared between groups.Results: The medical records of 107 eyes from 107 patients with mean age of 65.31 ± 12.15 years were reviewed. Eyes with a frown incision showed the best UDVA, followed by those with L-shaped and conventional incisions (P = 0.003). Eyes with an L-shaped incision or frown incision had a lower SIA than that of the conventional incision group at postoperative 6 months (mean ± standard deviation [SD] SIA, 0.86 ± 0.85 D, 0.63 ± 0.37 D, and 1.70 ± 1.27 D for frown incision, L-shaped incision, and conventional incisions, respectively; P = 0.004).Conclusion: The frown incision and L-shaped incision induced a significantly smaller SIA than the conventional incisions, which was associated with better UDVA postoperatively.Keywords: aphakia, astigmatism, intraocular lens dislocation, retropupillary iris-claw intraocular lens, scleral tunnel incision, sclerocorneal incision

Automated driving systems (ADS) have the potential to fundamentally change transportation, and a growing number of these systems have entered the market and are currently in use on public roadways. However, drivers may not use ADS as intended due to misunderstandings about system capabilities and limitations. Moreover, the real-world use and effects of this novel technology on transportation safety are largely unknown. To investigate driver interactions with ADS, we examined existing naturalistic driving data collected from 50 participants who drove personally owned vehicles with partial ADS for 12 months. We found that 47 out of 235 safety-critical events (SCEs) involved ADS use. An in-depth analysis of these 47 SCEs revealed that people misused ADS in 57% of SCEs (e.g., engaged in secondary tasks, used the systems not on highways, or with hands off the wheel). During 13% of SCEs, the ADS neither reacted to the situation nor warned the driver. A post-study survey showed that drivers found ADS useful and usable and felt more comfortable engaging in secondary tasks when ADS were in use. This study also captured some scenarios where the ADS did not meet driver expectations. The findings of this report may help inform the development of human-machine interfaces and training programs and provide awareness of the potential for unintended use of ADS and their associated safety consequences.

Automated driving systems (ADS) have the potential to fundamentally change transportation, and a growing number of these systems have entered the market and are currently in use on public roadways. However, drivers may not use ADS as intended due to misunderstandings about system capabilities and limitations. Moreover, the real-world use and effects of this novel technology on transportation safety are largely unknown. To investigate driver interactions with ADS, we examined existing naturalistic driving data collected from 50 participants who drove personally owned vehicles with partial ADS for 12 months. We found that 47 out of 235 safety-critical events (SCEs) involved ADS use. An in-depth analysis of these 47 SCEs revealed that people misused ADS in 57% of SCEs (e.g., engaged in secondary tasks, used the systems not on highways, or with hands off the wheel). During 13% of SCEs, the ADS neither reacted to the situation nor warned the driver. A post-study survey showed that drivers found ADS useful and usable and felt more comfortable engaging in secondary tasks when ADS were in use. This study also captured some scenarios where the ADS did not meet driver expectations. The findings of this report may help inform the development of human-machine interfaces and training programs and provide awareness of the potential for unintended use of ADS and their associated safety consequences.

Automated driving systems (ADS) have the potential to fundamentally change transportation, and a growing number of these systems have entered the market and are currently in use on public roadways. However, drivers may not use ADS as intended due to misunderstandings about system capabilities and limitations. Moreover, the real-world use and effects of this novel technology on transportation safety are largely unknown. To investigate driver interactions with ADS, we examined existing naturalistic driving data collected from 50 participants who drove personally owned vehicles with partial ADS for 12 months. We found that 47 out of 235 safety-critical events (SCEs) involved ADS use. An in-depth analysis of these 47 SCEs revealed that people misused ADS in 57% of SCEs (e.g., engaged in secondary tasks, used the systems not on highways, or with hands off the wheel). During 13% of SCEs, the ADS neither reacted to the situation nor warned the driver. A post-study survey showed that drivers found ADS useful and usable and felt more comfortable engaging in secondary tasks when ADS were in use. This study also captured some scenarios where the ADS did not meet driver expectations. The findings of this report may help inform the development of human-machine interfaces and training programs and provide awareness of the potential for unintended use of ADS and their associated safety consequences.

Automated driving systems (ADS) have the potential to fundamentally change transportation, and a growing number of these systems have entered the market and are currently in use on public roadways. However, drivers may not use ADS as intended due to misunderstandings about system capabilities and limitations. Moreover, the real-world use and effects of this novel technology on transportation safety are largely unknown. To investigate driver interactions with ADS, we examined existing naturalistic driving data collected from 50 participants who drove personally owned vehicles with partial ADS for 12 months. We found that 47 out of 235 safety-critical events (SCEs) involved ADS use. An in-depth analysis of these 47 SCEs revealed that people misused ADS in 57% of SCEs (e.g., engaged in secondary tasks, used the systems not on highways, or with hands off the wheel). During 13% of SCEs, the ADS neither reacted to the situation nor warned the driver. A post-study survey showed that drivers found ADS useful and usable and felt more comfortable engaging in secondary tasks when ADS were in use. This study also captured some scenarios where the ADS did not meet driver expectations. The findings of this report may help inform the development of human-machine interfaces and training programs and provide awareness of the potential for unintended use of ADS and their associated safety consequences.

Optical see-through automotive head-up displays (HUDs) are a form of augmented reality (AR) that is quickly gaining penetration into the consumer market. Despite increasing adoption, demand, and competition among manufacturers to deliver higher quality HUDs with increased fields of view, little work has been done to understand how best to design and assess AR HUD user interfaces, and how to quantify their effects on driver behavior, performance, and ultimately safety. This paper reports on a novel, low-cost, immersive driving simulator created using a myriad of custom hardware and software technologies specifically to examine basic and applied research questions related to AR HUDs usage when driving. We describe our experiences developing simulator hardware and software and detail a user study that examines driver performance, visual attention, and preferences using two AR navigation interfaces. Results suggest that conformal AR graphics may not be inherently better than other HUD interfaces. We include lessons learned from our simulator development experiences, results of the user study and conclude with limitations and future work.

Optical see-through automotive head-up displays (HUDs) are a form of augmented reality (AR) that is quickly gaining penetration into the consumer market. Despite increasing adoption, demand, and competition among manufacturers to deliver higher quality HUDs with increased fields of view, little work has been done to understand how best to design and assess AR HUD user interfaces, and how to quantify their effects on driver behavior, performance, and ultimately safety. This paper reports on a novel, low-cost, immersive driving simulator created using a myriad of custom hardware and software technologies specifically to examine basic and applied research questions related to AR HUDs usage when driving. We describe our experiences developing simulator hardware and software and detail a user study that examines driver performance, visual attention, and preferences using two AR navigation interfaces. Results suggest that conformal AR graphics may not be inherently better than other HUD interfaces. We include lessons learned from our simulator development experiences, results of the user study and conclude with limitations and future work.

Many driving scenarios involve correctly perceiving road elements in depth and manually responding as appropriate. Of late, augmented reality (AR) head-up displays (HUDs) have been explored to assist drivers in identifying road elements, by using a myriad of AR interface designs that include world-fixed graphics perceptually placed in the forward driving scene. Volumetric AR HUDs purportedly offer increased accuracy of distance perception through natural presentation of oculomotor cues as compared to traditional HUDs. In this article, the authors quantify participant performance matching virtual objects to real-world counterparts at egocentric distances of 7-12 meters while using both volumetric and fixed-focal plane AR HUDs. The authors found the volumetric HUD to be associated with faster and more accurate depth judgements at far distance, and that participants performed depth judgements more quickly as the experiment progressed. The authors observed no differences between the two displays in terms of reported simulator sickness or eye strain.

Optical see-through automotive head-up displays (HUDs) are a form of augmented reality (AR) that is quickly gaining penetration into the consumer market. Despite increasing adoption, demand, and competition among manufacturers to deliver higher quality HUDs with increased fields of view, little work has been done to understand how best to design and assess AR HUD user interfaces, and how to quantify their effects on driver behavior, performance, and ultimately safety. This paper reports on a novel, low-cost, immersive driving simulator created using a myriad of custom hardware and software technologies specifically to examine basic and applied research questions related to AR HUDs usage when driving. We describe our experiences developing simulator hardware and software and detail a user study that examines driver performance, visual attention, and preferences using two AR navigation interfaces. Results suggest that conformal AR graphics may not be inherently better than other HUD interfaces. We include lessons learned from our simulator development experiences, results of the user study and conclude with limitations and future work.

Augmented reality (AR) has the potential to fundamentally change the way we interact with information. Direct perception of computer generated graphics atop physical reality can afford hands-free access to contextual information on the fly. However, as users must interact with both digital and physical information simultaneously, yesterday's approaches to interface design may not be sufficient to support the new way of interaction. Furthermore, the impacts of this novel technology on user experience and performance are not yet fully understood. Driving is one of many promising tasks that can benefit from AR, where conformal graphics strategically placed in the real-world can accurately guide drivers' attention to critical environmental elements. The ultimate purpose of this study is to reduce pedestrian accidents through design of driver interfaces that take advantage of AR head-up displays (HUD). For this purpose, this work aimed to (1) identify information requirements for pedestrian collision warning, (2) design AR driver interfaces, and (3) quantify effects of AR interfaces on driver performance and experience. Considering the dynamic nature of human-environment interaction in AR-supported driving, we took an ecological approach for interface design and evaluation, appreciating not only the user but also the environment. The requirement analysis examined environmental constraints imposed on the drivers' behavior, interface design translated those behavior-shaping constraints into perceptual forms of interface elements, and usability evaluations utilized naturalistic driving scenarios and tasks for better ecological validity. A novel AR driver interface for pedestrian collision warning, the virtual shadow, was proposed taking advantage of optical see-through HUDs. A series of usability evaluations in both a driving simulator and on an actual roadway showed that virtual shadow interface outperformed current pedestrian collision warning interfaces in guiding driver

Augmented reality (AR) has the potential to fundamentally change the way we interact with information. Direct perception of computer generated graphics atop physical reality can afford hands-free access to contextual information on the fly. However, as users must interact with both digital and physical information simultaneously, yesterday's approaches to interface design may not be sufficient to support the new way of interaction. Furthermore, the impacts of this novel technology on user experience and performance are not yet fully understood. Driving is one of many promising tasks that can benefit from AR, where conformal graphics strategically placed in the real-world can accurately guide drivers' attention to critical environmental elements. The ultimate purpose of this study is to reduce pedestrian accidents through design of driver interfaces that take advantage of AR head-up displays (HUD). For this purpose, this work aimed to (1) identify information requirements for pedestrian collision warning, (2) design AR driver interfaces, and (3) quantify effects of AR interfaces on driver performance and experience. Considering the dynamic nature of human-environment interaction in AR-supported driving, we took an ecological approach for interface design and evaluation, appreciating not only the user but also the environment. The requirement analysis examined environmental constraints imposed on the drivers' behavior, interface design translated those behavior-shaping constraints into perceptual forms of interface elements, and usability evaluations utilized naturalistic driving scenarios and tasks for better ecological validity. A novel AR driver interface for pedestrian collision warning, the virtual shadow, was proposed taking advantage of optical see-through HUDs. A series of usability evaluations in both a driving simulator and on an actual roadway showed that virtual shadow interface outperformed current pedestrian collision warning interfaces in guiding driver

69A3551747115, The number of automated features in surface vehicles is increasing as new vehicles are released each year. Some features allow drivers to temporarily take their attention off the road to engage in other tasks. However, sometimes it is important for drivers to immediately take control of the vehicle. To take control safely, drivers must understand what is required of them and have the situation awareness (SA) to understand important changes or factors within the environment around them. To achieve this, drivers may be presented with necessary takeover information using a head-up display (HUD), which keeps the driver’s eyes on the road. This study investigated the impact of novel HUDs on driver SA during takeover on highways. Data collection included empirical data for takeover performance metrics, self-reported SA, and participant preferences. To investigate differences between conditions, statistical analyses utilized repeated measure analyses of variance (ANOVAs). The results indicated that HUDs can increase aspects of takeover performance on highways, with participants demonstrating lower response times and higher time-to-collision metrics. There was no significant impact of HUDs on driver SA. Results of this work identified potential use cases and design criteria for new designs of novel HUDs to deliver important information during takeover.