CHS: SMALL: Methods to Assess Automotive Augmented Reality Head-up Display Effects on Driver Performance

增强现实（AR）挡风玻璃显示器有可能通过直接在道路上显示计算机图形来提供全新的驾驶体验，随着AR技术的日益商业化，它可能会在汽车中变得更加普遍。如果设计得当，AR有可能提高驾驶和驾驶员的安全性。然而，我们目前还不知道如何评估新兴的AR驾驶界面的安全性，因为用于评估其他车载信息显示（如导航和娱乐系统）的现有方法不够丰富，无法捕捉AR显示对驾驶员性能的影响。该项目将开发新的方法来评估驾驶员在使用AR显示器时的视觉分散。这些方法将专门用于开发AR驾驶用户界面，以减少伤害并最大限度地减少生命和财产损失。如果成功，该项目将帮助汽车制造商更快地创建和发布新的、安全的AR驾驶应用程序，并可能对其他使用AR的领域产生积极影响，例如建筑和制造业。该项目还将通过培训能够更好地考虑系统设计和评价中的人力和技术因素的研究人员，以及通过努力招收传统上在工程领域代表性不足的学生，来支持教育影响。该项目将解决AR平视显示器（hud）提供的视野预期增加所带来的开放性问题。这将支持比当前显示器更广泛的可能接口和信息位置；然而，我们目前还不知道如何有效地量化AR用户界面对驾驶的影响。该项目将评估配备AR HUD的驾驶员的目光分配和视觉注意力能力，并将这些知识应用于AR HUD评估的新方法。具体来说，该团队将建立AR HUD浏览持续时间的阈值，以及一组生态有效的视觉AR HUD任务，这些任务可以被汽车AR HUD的研究人员和设计师广泛采用。该团队将进一步创建一套方法，以评估AR HUD视觉需求对驾驶员检测驾驶员中心和外围视野中发生事件的能力的影响。最后，本研究将采用用户研究，在实际道路上测试改进的方法，并推荐应用这些方法的最佳实践。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Augmented Reality (AR) windshield displays have the potential to provide fundamentally new driving experiences by displaying computer graphics directly on the roadway, and with the increasing commercialization of AR technologies are likely to become more common in cars. If designed properly, AR has the potential to enhance driving and driver safety. However, we currently do not know how to evaluate the safety of emerging AR driving interfaces, as existing methods used for evaluating other in-vehicle information displays (such as navigation and entertainment systems) are not rich enough to capture effects of AR displays on driver performance. This project will develop new methods for assessing drivers' visual distraction when using AR displays. These methods will be specifically tuned for developing AR user interfaces for driving that reduce injuries and minimize loss of life and property. If successful, this project will help auto manufacturers more quickly create and release new and safe AR driving applications, and may have a positive impact on other areas where AR is used, such as in construction and manufacturing. The project will also support educational impacts, through the training of researchers better able to consider both human and technical factors in system design and evaluation, and through efforts to recruit students who are members of populations traditionally underrepresented in engineering.The project will address open questions that arise from expected increases in the field of view provided by AR heads-up displays (HUDs). This will support a wider variety of possible interfaces and information locations than current displays; however, we currently do not know how to effectively quantify the effects of AR user interfaces on driving. This project will evaluate glance allocation and visual attention capabilities of drivers with AR HUDs, and apply this knowledge to inform new methods of AR HUD assessment. Specifically, the team will establish thresholds for AR HUD glance durations along with a set of ecologically valid visual AR HUD tasks that can be broadly adopted by both researchers and designers of automotive AR HUDs. The team will further create a set of methods to assess the effects of AR HUD visual demand on drivers' ability to detect events occurring in both the drivers' central and peripheral fields of view. Lastly, the research will employ user studies to test the refined methods on an actual roadway and recommend best practices for applying the methods.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.