Abstract

Connected vehicle technology relying on Human Machine Interface (HMI) achieve a dominant position in the overall safety improvement. However, the impact of HMI on the driver’s visual attention cannot be ignored, especially on the accident-prone foggy freeway. The objective of this paper is to evaluate the level of distraction caused by HMI in data analysis of drivers’ visual characteristics and to establish a generic evaluation methodology. A connected vehicle test platform has been established based on the driving simulator, in which visibility was set to the level of heavy fog and the technical condition was set in two conditions (with or without HMI). Measurement of driving behavior parameters include frequency of fixations and saccades and the proportion of fixation. The researchers compared and analyzed the driver’s visual characteristics and the degree of distraction in a combination of indices based on the AttenD algorithm, setting two technical conditions in a heavy fog. Drivers suffering more visual distraction and interference with HMI may have an impact on the driver’s driving safety. The results provide a generic approach to evaluate the HMI of a connected vehicle system and a safety assessment methodology for the connected vehicle system.

摘要

依托人机界面（HMI）的车联网技术在整体安全提升中占据主导地位。然而，人机界面对驾驶员视觉注意力的影响不容忽视，尤其是在事故多发的大雾高速公路上。本文的目的是评估 HMI 在驾驶员视觉特征数据分析中引起的分心程度，并建立通用的评估方法。建立了基于驾驶模拟器的车联网测试平台，其中能见度设置为大雾水平，技术条件设置为两种条件（有或无HMI）。驾驶行为参数的测量包括注视和扫视的频率以及注视的比例。研究人员基于AttenD算法，在大雾中设定了两项技术条件，结合指标对驾驶员的视觉特征和分心程度进行了对比分析。驾驶员遭受更多的视觉分心和对 HMI 的干扰可能会对驾驶员的驾驶安全产生影响。结果提供了一种通用的方法来评估联网车辆系统的 HMI 和联网车辆系统的安全评估方法。