基于驾驶认知负荷的自动化车辆界面视觉舒适研究综述

Research Status of Visual Comfort about Driving Interface Based on Cognitive Load of Driving

中文关键词: 视觉舒适  驾驶界面  认知负荷  视觉疲劳  界面设计

英文关键词: s of the 90th Anniversary of the Chinese Psychological Society and the 14th National Psychology Academic Conference, China:Institute of Psychology, Chinese Academy Sciences, 2011:240.

中文摘要:

      目的 驾驶界面通过有效地将自动驾驶汽车的当前状态和驾驶意图传达给驾驶员，从而在基于人–机–环境的驾驶任务运行过程中创造安全性和舒适性。当前自动驾驶汽车的自动驾驶功能接受程度不高，驾驶员仍需监控驾驶界面，车辆内部驾驶界面视觉舒适性的重要性日益凸显。探讨该领域的主要研究成果、理论框架、研究方法、存在争议以及未来的研究方向。方法 基于 2021年至2024年期间在CNKI和Web of Science、Scopus以及Proquest数据库中已发表的论文，采用VOSviewer和CiteSpace工具对2021-2024年间的相关文献进行可视化分析。根据 PRISMA系统综述方法筛选近年来所有关于自动驾驶汽车的界面视觉舒适相关且合格的研究，以确保综述的全面性和准确性。结果 总结了视觉舒适与驾驶员视觉疲劳、认知负荷之间的关系和相关评估方法，包括主观和客观评价两类;提出了有用指标，例如界面信息增加时注视持续时间、瞳孔扩张程度和图标数量;根据自动车辆驾驶界面人–机–环境关系开发了基于驾驶认知负荷的视觉舒适因素框架，为人机界面的视觉舒适研究提供参考。

英文摘要:

      The driving interface effectively communicates the current state and driving intention of the autonomous vehicle to the driver, thereby creating safety and comfort during the operation of the autonomous vehicle based on the human-machine-environment. The current level of acceptance of the autonomous driving function of autonomous vehicles is not high. Drivers still need to monitor the driving interface. The importance of visual comfort in the driving interface has become increasingly prominent. The work aims to study the main research achievements, theoretical framework, research methods, existing controversies and future research directions in this field. Based on the papers published in CNKI and Web of Science, Scopus, and Proquest databases from 2021 to 2024, VOSviewer and CiteSpace tools were applied to conduct a visual analysis of the relevant literature from 2021 to 2024. All relevant and qualified studies on the visual comfort of the interface of autonomous vehicles in recent year were selected according to the PRISMA systematic review method to ensure the comprehensiveness and accuracy of the review. The relationship between visual comfort and driver visual fatigue and cognitive load and related evaluation methods are summarized, including two categories of subjective and objective evaluation; Useful indicators such as fixation duration, pupil dilation, and ICA increase when interface information increases are proposed. Finally, a multidimensional theoretical framework was developed based on the influencing factors of visual comfort and human-machine-environment relationship in the autonomous vehicle driving interface. This review can provide some reference for the study of visual comfort of interfaces.