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首页> 外文会议>International conference on human-computer interaction;International conference on digital human modeling >Driving Process' Analysis and HUD Design Based on Conditional Autonomous Traffic Safety
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Driving Process' Analysis and HUD Design Based on Conditional Autonomous Traffic Safety

机译：基于条件自主交通安全的驾驶过程分析与HUD设计

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With the rapid increasing of car quantity, traffic safety problem has become more and more serious. Traffic crash is also a major world public health problem; hence, it has become a topic of interest among many scholars. This study intends to analyze the factors that affect driving safety under different driving scenarios. The results of this study are based on conditional autonomous driving. The context-aware conditional autonomous safety driving process and the relationships among three elements, namely, the environment, the driver and the car, are analyzed based on the Haddon matrix and the system attribution model. The vehicle used is a conditional autonomous car capable of context awareness; it can send useful information as feedback to the driver and interact with driver behavior. Afterward, the results are applied in parking scenario and lane changing scenario, and the factors that influence safety during parking and lane changing are analyzed. Then, the obtained information is validated based on driver perspective, and a design concept for head-up display is proposed. This design is expected to assist drivers in parking and lane changing without accident.
机译：随着汽车数量的快速增长，交通安全问题变得越来越严重。交通事故也是世界主要的公共卫生问题。因此，它已经成为许多学者感兴趣的话题。本研究旨在分析影响不同驾驶场景下驾驶安全的因素。这项研究的结果基于条件自动驾驶。基于Haddon矩阵和系统归因模型，分析了情境感知条件自动驾驶安全驾驶过程以及环境，驾驶员和汽车三个要素之间的关系。使用的车辆是能够感知环境的有条件自动驾驶汽车;它可以将有用的信息作为反馈发送给驾驶员，并与驾驶员的行为进行交互。然后，将结果应用于停车场景和换道场景，分析了影响停车和换道时安全性的因素。然后，基于驾驶员的观点对获得的信息进行验证，并提出了用于平视显示器的设计概念。预期该设计将有助于驾驶员在停车和换道时不会发生意外。

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