This article showcases a perceived safety analysis framework to assess the awareness of connected vehicles (CVs) of surrounding safety-critical vehicles. We study two classes of messages that a CV can transmit: 1) messages containing information about the transmitter only [e.g., standardized basic safety messages (BSMs) and cooperative awareness messages (CAMs)], and 2) messages that aggregate information about the transmitter and surrounding objects detected by their onboard sensors [e.g., collective perception messages (CPMs)]. We show how the proposed framework allows one to identify safety-critical vehicles and the effect of the type of transmitted messages on the awareness of these critical vehicles. To evaluate the performance, we use experimental data with mixed traffic of unconnected vehicles and CVs at different penetration ratios. Results show that CPMs are significantly more effective at providing awareness of safety-critical vehicles at low-to-mid-connectivity penetrations. At high-connectivity penetrations, messages with only information about the transmitter are sufficient to provide full awareness without burdening the wireless channel.

中文翻译：

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公路驾驶中联网车辆的意识评估：感知安全方法

本文展示了一个感知安全分析框架，用于评估对周围安全关键车辆的联网车辆 (CV) 的意识。我们研究了 CV 可以传输的两类消息：1) 仅包含有关发射器的信息的消息 [例如，标准化的基本安全消息 (BSM) 和协作意识消息 (CAM)]，以及 2) 聚合有关发射器的信息的消息以及由其机载传感器检测到的周围物体[例如，集体感知信息 (CPM)]。我们展示了提议的框架如何允许人们识别安全关键车辆以及传输的消息类型对这些关键车辆的意识的影响。为了评估性能，我们使用具有不同渗透率的未连接车辆和 CV 混合交通的实验数据。结果表明，CPM 在提供中低连接渗透率的安全关键车辆意识方面明显更有效。在高连接渗透率下，仅包含有关发射器的信息的消息足以提供完整的感知，而不会增加无线信道的负担。