增强现实平视显示行人预警系统的视觉编码设计研究

目的 随着影像和雷达传感器技术的发展，车载预警系统可以更快、更广和更高精度地实现对于行人的识别与追踪。相较于其他预警方式，增强现实平视显示预警(Augmented Reality Head-up Display，AR-HUD)可以为用户提供实时、准确的预警信息并降低用户因视线切换而带来的驾驶风险，具有较大的应用潜力。已有研究表明，预警信息的编码方式对预警效果影响显著，然而目前AR-HUD预警方式的设计标准尚未制定，因此，探究AR-HUD的预警编码方式对其应用具有重要意义。方法 以AR-HUD行人预警为例，基于颜色、边框形状、闪烁等设计元素对预警信息进行编码设计，从眼动指标、行为指标和主观指标对各编码方式进行多模态的量化分析和评估，提出相应的设计建议。结论 采用颜色编码可以显著提升编码可识别性，保持低漏报率的同时有较短的反应时，而非颜色编码利用冗余编码可以增强编码可识别性;采用形状编码会降低编码可理解性，但会减小用户对预警的漏报率;闪烁编码会增大对预警的漏报率和反应时;用户主观上认为冗余编码比单维编码有更强的警示性。研究结论可为AR-HUD的交互设计和实车应用提供相关理论支撑。

Visual Coding Design of Augmented Reality Head-up Display Pedestrian Warning System

With the development of imaging and radar sensor technology, vehicle-mounted early warning systems can realize the recognition and tracking of pedestrians quickly and widely with higher accuracy. Compared with other warning methods, the Augmented Reality Head-up Display (AR-HUD) can provide real-time and accurate warning information for users and reduce the driving risk caused by the sight switch, so it has a strong application potential. Studies have revealed that the coding method of warning information has a significant impact on the effect of warning. However, the design standard of AR-HUD warning method has not been established yet, so there is of great significance to explore the coding method of AR-HUD for its application. With AR-HUD pedestrian warning as an example, the warning information was coded based on color, shape, flashing, and other design elements. The multi-modal quantitative analysis and evaluation of each coding method were carried out from the eye movement index, behavior index, and subjective index and the corresponding design suggestions were put forward. The color coding can significantly improve the identifiability of the code at the time of maintaining low failure rate and short response time, while non-color coding can enhance code identifiability by redundant coding. The shape coding will reduce the comprehensibility of coding but will reduce the failure rate and the flashing code can increase the failure rate and response time of warning. Subjectively, users believe that redundant coding is more warning than uni-dimensional coding. The research results can provide theoretical support for the interaction design of AR-HUD and the application of real vehicles.