计算机科学
模式
更安全的
人机交互
可用性
工作量
事件(粒子物理)
模态(人机交互)
动作(物理)
驾驶模拟器
计算机安全
模拟
社会科学
物理
量子力学
社会学
操作系统
作者
Gyoungwon Ryu,Yeun Joo Lee,Yulim Kim,Yong Gu Ji
标识
DOI:10.1080/10447318.2024.2385193
摘要
Communicating effectively with autonomous vehicles requires contextualized visual and auditory cues to ensure clear message delivery. Evaluating the user experience involves assessing which types of information can be safely reacted to without additional monitoring and how it is presented. Validating the visual and auditory cues supports the driver's course of action. This study investigates message types and preferred modalities of driver-to-driver communication via vehicle-to-everything (V2X) in advanced driver assistance systems technologies for autonomous and manual driving and proposes efficient ways to respond to event situations. Four modalities, including baseline and three message types with different information were proposed to investigate the information required by drivers. Results indicate that providing notifications during autonomous driving is more helpful and less workload-intensive than during manual driving. Most notifications were highly visible and easy to recognize. Although behavioral messages in both autonomous and manual driving enhance usability, providing advice and behavioral messages is safer for autonomous driving. Designing V2X notification information based on future events is vital because of its highly pragmatic nature.
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